cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.OS - 操作系统 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.AT - 代数拓扑 math.CO - 组合数学 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.flu-dyn - 流体动力学 q-bio.NC - 神经元与认知 q-bio.QM - 定量方法 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]EvoMan: Game-playing Competition
    • [cs.AI]Learning Variable Ordering Heuristics for Solving Constraint Satisfaction Problems
    • [cs.AI]Questions to Guide the Future of Artificial Intelligence Research
    • [cs.AI]SensAI+Expanse Adaptation on Human Behaviour Towards Emotional Valence Prediction
    • [cs.AI]Sum-Product Network Decompilation
    • [cs.CL]”The Squawk Bot”: Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering
    • [cs.CL]A Machine Learning Framework for Authorship Identification From Texts
    • [cs.CL]AdvCodec: Towards A Unified Framework for Adversarial Text Generation
    • [cs.CL]BioConceptVec: creating and evaluating literature-based biomedical concept embeddings on a large scale
    • [cs.CL]Combining Context and Knowledge Representations for Chemical-Disease Relation Extraction
    • [cs.CL]Exploring Context, Attention and Audio Features for Audio Visual Scene-Aware Dialog
    • [cs.CL]Harnessing Evolution of Multi-Turn Conversations for Effective Answer Retrieval
    • [cs.CL]Hunt Protagonist of Sentiment: Sentiment Analysis via Capsule Network with Sentiment-Aspect Reconstruction
    • [cs.CL]Hybrid Machine Learning Models of Classifying Residential Requests for Smart Dispatching
    • [cs.CL]Knowledge-guided Convolutional Networks for Chemical-Disease Relation Extraction
    • [cs.CL]Modeling Intent, Dialog Policies and Response Adaptation for Goal-Oriented Interactions
    • [cs.CL]Predicting Heart Failure Readmission from Clinical Notes Using Deep Learning
    • [cs.CL]Probing the phonetic and phonological knowledge of tones in Mandarin TTS models
    • [cs.CL]Recurrent Hierarchical Topic-Guided Neural Language Models
    • [cs.CL]SberQuAD - Russian Reading Comprehension Dataset: Description and Analysis
    • [cs.CL]Siamese Networks for Large-Scale Author Identification
    • [cs.CL]Tag-less Back-Translation
    • [cs.CL]What do Asian Religions Have in Common? An Unsupervised Text Analytics Exploration
    • [cs.CR]Dispel: Byzantine SMR with Distributed Pipelining
    • [cs.CV]2DR1-PCA and 2DL1-PCA: two variant 2DPCA algorithms based on none L2 norm
    • [cs.CV]5D Light Field Synthesis from a Monocular Video
    • [cs.CV]A Compared Study Between Some Subspace Based Algorithms
    • [cs.CV]A Robust Non-Linear and Feature-Selection Image Fusion Theory
    • [cs.CV]A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D images
    • [cs.CV]A sparse resultant based method for efficient minimal solvers
    • [cs.CV]Active Learning for Segmentation Based on Bayesian Sample Queries
    • [cs.CV]Adversarial Cross-Domain Action Recognition with Co-Attention
    • [cs.CV]Adversarial Feature Distribution Alignment for Semi-Supervised Learning
    • [cs.CV]Analysis of the hands in egocentric vision: A survey
    • [cs.CV]Assessing Data Quality of Annotations with Krippendorff Alpha For Applications in Computer Vision
    • [cs.CV]CNN-generated images are surprisingly easy to spot… for now
    • [cs.CV]Candidate Fusion: Integrating Language Modelling into a Sequence-to-Sequence Handwritten Word Recognition Architecture
    • [cs.CV]Continuity, Stability, and Integration: Novel Tracking-Based Perspectives for Temporal Object Detection
    • [cs.CV]Convolutional Neural Networks: A Binocular Vision Perspective
    • [cs.CV]Cross-Modal Image Fusion Theory Guided by Subjective Visual Attention
    • [cs.CV]DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration
    • [cs.CV]DMCL: Distillation Multiple Choice Learning for Multimodal Action Recognition
    • [cs.CV]Decoupled Attention Network for Text Recognition
    • [cs.CV]Depth Completion via Deep Basis Fitting
    • [cs.CV]Do Facial Expressions Predict Ad Sharing? A Large-Scale Observational Study
    • [cs.CV]Eikonal Region-based Active Contours for Image Segmentation
    • [cs.CV]Eliminating cross-camera bias for vehicle re-identification
    • [cs.CV]Extracting urban water by combining deep learning and Google Earth Engine
    • [cs.CV]FasterSeg: Searching for Faster Real-time Semantic Segmentation
    • [cs.CV]From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality
    • [cs.CV]Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction
    • [cs.CV]Generalizing Deep Models for Overhead Image Segmentation Through Getis-Ord Gi* Pooling
    • [cs.CV]Geometry Sharing Network for 3D Point Cloud Classification and Segmentation
    • [cs.CV]Graph-Based Parallel Large Scale Structure from Motion
    • [cs.CV]Image Outpainting and Harmonization using Generative Adversarial Networks
    • [cs.CV]Jacobian Adversarially Regularized Networks for Robustness
    • [cs.CV]Joint Face Super-Resolution and Deblurring Using a Generative Adversarial Network
    • [cs.CV]Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
    • [cs.CV]Learning to Generate Dense Point Clouds with Textures on Multiple Categories
    • [cs.CV]Measuring Dataset Granularity
    • [cs.CV]Minimal Solutions for Relative Pose with a Single Affine Correspondence
    • [cs.CV]Multimodal Representation Model based on Graph-Based Rank Fusion
    • [cs.CV]Neural Outlier Rejection for Self-Supervised Keypoint Learning
    • [cs.CV]One-Shot Imitation Filming of Human Motion Videos
    • [cs.CV]Oriented Objects as pairs of Middle Lines
    • [cs.CV]Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling
    • [cs.CV]Progressive DARTS: Bridging the Optimization Gap for NAS in the Wild
    • [cs.CV]RPGAN: GANs Interpretability via Random Routing
    • [cs.CV]Research on Clustering Performance of Sparse Subspace Clustering
    • [cs.CV]Robust Pose Invariant Shape and Texture based Hand Recognition
    • [cs.CV]Saliency Based Fire Detection Using Texture and Color Features
    • [cs.CV]Scale Match for Tiny Person Detection
    • [cs.CV]Seek and You Will Find: A New Optimized Framework for Efficient Detection of Pedestrian
    • [cs.CV]Style-based Variational Autoencoder for Real-World Super-Resolution
    • [cs.CV]The Five Elements of Flow
    • [cs.CV]Tifinagh-IRCAM Handwritten character recognition using Deep learning
    • [cs.CV]Towards Efficient Training for Neural Network Quantization
    • [cs.CV]\emph{cm}SalGAN: RGB-D Salient Object Detection with Cross-View Generative Adversarial Networks
    • cs.CYInformation Operations: An Integrated Perspective
    • [cs.CY]Teaching Responsible Data Science: Charting New Pedagogical Territory
    • [cs.DC]Jupiter: A Networked Computing Architecture
    • [cs.DC]Microchain: a Light Hierarchical Consensus Protocol for IoT System
    • [cs.GT]How Quantum Information can improve Social Welfare
    • [cs.HC]Emotion Recognition Using Wearables: A Systematic Literature Review Work in progress
    • [cs.HC]Experience Report: Towards Moving Things with Types — Helping Logistics Domain Experts to Control Cyber-Physical Systems with Type-Based Synthesis
    • [cs.IT]A Survey of NOMA: Current Status and Open Research Challenges
    • [cs.IT]An Efficient Deep Learning Framework for Low Rate Massive MIMO CSI Reporting
    • [cs.IT]Channel Estimation Method and Phase Shift Design for Reconfigurable Intelligent Surface Assisted MIMO Networks
    • [cs.IT]Compressive Sensing Based Channel Estimation for Millimeter-Wave Full-Dimensional MIMO with Lens-Array
    • [cs.IT]Direct and Indirect Effects — An Information Theoretic Perspective
    • [cs.IT]Energy-Aware Multi-Server Mobile Edge Computing: A Deep Reinforcement Learning Approach
    • [cs.IT]Low-Complexity Random Rotation-based Schemes for Intelligent Reflecting Surfaces
    • [cs.IT]Non-Orthogonal eMBB-URLLC Radio Access for Cloud Radio Access Networks with Analog Fronthauling
    • [cs.IT]Overcoming the Channel Estimation Barrier in Massive MIMO Communication Systems
    • [cs.IT]Passive Beamforming and Information Transfer Design for Large Intelligent Surface Aided Multiuser MIMO Systems
    • [cs.IT]Power Control for Massive MIMO Systems with Nonorthogonal Pilots
    • [cs.IT]Progressive Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface with Discrete Phase Shifts
    • [cs.IT]Trellis-Coded Non-Orthogonal Multiple Access
    • [cs.LG]A Regression Framework for Predicting User’s Next Location using Call Detail Records
    • [cs.LG]A Survey of Deep Learning Applications to Autonomous Vehicle Control
    • [cs.LG]An optical diffractive deep neural network with multiple frequency-channels
    • [cs.LG]AutoML: Exploration v.s. Exploitation
    • [cs.LG]BackPACK: Packing more into backprop
    • [cs.LG]Bandit Multiclass Linear Classification for the Group Linear Separable Case
    • [cs.LG]Black Box Recursive Translations for Molecular Optimization
    • [cs.LG]Business Process Variant Analysis based on Mutual Fingerprints of Event Logs
    • [cs.LG]Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning
    • [cs.LG]Chart Auto-Encoders for Manifold Structured Data
    • [cs.LG]Closed Form Variances for Variational Auto-Encoders
    • [cs.LG]Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability
    • [cs.LG]Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data
    • [cs.LG]Data-Free Adversarial Distillation
    • [cs.LG]Deep Automodulators
    • [cs.LG]Deep Learning via Dynamical Systems: An Approximation Perspective
    • [cs.LG]Direct and indirect reinforcement learning
    • [cs.LG]EAST: Encoding-Aware Sparse Training for Deep Memory Compression of ConvNets
    • [cs.LG]Efficient Parameter Sampling for Neural Network Construction
    • [cs.LG]Estimation of Spectral Risk Measures
    • [cs.LG]Evaluating the Effectiveness of Margin Parameter when Learning Knowledge Embedding Representation for Domain-specific Multi-relational Categorized Data
    • [cs.LG]Exploring TD error as a heuristic for $σ$ selection in Q($σ$, $λ$)
    • [cs.LG]Finite-Time Analysis and Restarting Scheme for Linear Two-Time-Scale Stochastic Approximation
    • [cs.LG]Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction
    • [cs.LG]Hierarchical Target-Attentive Diagnosis Prediction in Heterogeneous Information Networks
    • [cs.LG]How Robust Are Graph Neural Networks to Structural Noise?
    • [cs.LG]Interpreting Predictive Process Monitoring Benchmarks
    • [cs.LG]Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
    • [cs.LG]Large Random Forests: Optimisation for Rapid Evaluation
    • [cs.LG]Latent Variables on Spheres for Sampling and Spherical Inference
    • [cs.LG]Layerwise Noise Maximisation to Train Low-Energy Deep Neural Networks
    • [cs.LG]Learn-able parameter guided Activation Functions
    • [cs.LG]Learning Improved Representations by Transferring Incomplete Evidence Across Heterogeneous Tasks
    • [cs.LG]Learning an Interpretable Traffic Signal Control Policy
    • [cs.LG]Learning to Impute: A General Framework for Semi-supervised Learning
    • [cs.LG]Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning
    • [cs.LG]Monte-Carlo Tree Search for Policy Optimization
    • [cs.LG]On Simulation and Trajectory Prediction with Gaussian Process Dynamics
    • [cs.LG]On the Initialization of Long Short-Term Memory Networks
    • [cs.LG]Online Reinforcement Learning of Optimal Threshold Policies for Markov Decision Processes
    • [cs.LG]Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning
    • [cs.LG]Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning
    • [cs.LG]Privacy Attacks on Network Embeddings
    • [cs.LG]Quantile Propagation for Wasserstein-Approximate Gaussian Processes
    • [cs.LG]Recommendations and User Agency: The Reachability of Collaboratively-Filtered Information
    • [cs.LG]Regularized Operating Envelope with Interpretability and Implementability Constraints
    • [cs.LG]Spectral embedding of regularized block models
    • [cs.LG]TentacleNet: A Pseudo-Ensemble Template for Accurate Binary Convolutional Neural Networks
    • [cs.LG]TextNAS: A Neural Architecture Search Space tailored for Text Representation
    • [cs.LG]The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity
    • [cs.LG]The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
    • [cs.LG]Variational Recurrent Models for Solving Partially Observable Control Tasks
    • [cs.LO]Bringing Belief Base Change into Dynamic Epistemic Logic
    • [cs.MA]A Survey of Deep Reinforcement Learning in Video Games
    • [cs.MM]Hiding Data in Images Using Cryptography and Deep Neural Network
    • [cs.MM]Leveraging Topics and Audio Features with Multimodal Attention for Audio Visual Scene-Aware Dialog
    • [cs.NE]Intelligent Wireless Sensor Nodes for Human Footstep Sound Classification for Security Application
    • [cs.NE]Multifactorial Evolutionary Algorithm For Clustered Minimum Routing Cost Problem
    • [cs.OS]Virtual Gang based Scheduling of Real-Time Tasks on Multicore Platforms
    • [cs.RO]A Multimodal Target-Source Classifier with Attention Branches to Understand Ambiguous Instructions for Fetching Daily Objects
    • [cs.RO]Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability
    • [cs.RO]Joint Forward-Backward Visual Odometry for Stereo Cameras
    • [cs.RO]Manipulation Planning and Control for Shelf Replenishment
    • [cs.RO]Probabilistic Safety Constraints for Learned High Relative Degree System Dynamics
    • [cs.RO]Safe and Fast Tracking Control on a Robot Manipulator: Robust MPC and Neural Network Control
    • [cs.RO]Shared Autonomy in Web-based Human Robot Interaction
    • [cs.RO]Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning
    • [cs.SD]Deep Audio Prior
    • [cs.SD]Emotion Recognition from Speech
    • [cs.SD]Learning Singing From Speech
    • [cs.SE]An Overview on Smart Contracts: Challenges, Advances and Platforms
    • [cs.SI]Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of Ethereum Graph
    • [cs.SI]Mining the Automotive Industry: A Network Analysis of Corporate Positioning and Technological Trends
    • [eess.AS]Mixture of Inference Networks for VAE-based Audio-visual Speech Enhancement
    • [eess.IV]A Generalizable Method for Automated Quality Control of Functional Neuroimaging Datasets
    • [eess.IV]Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
    • [eess.IV]Fully Automated Multi-Organ Segmentation in Abdominal Magnetic Resonance Imaging with Deep Neural Networks
    • [eess.IV]Low radiation tomographic reconstruction with and without template information
    • [eess.IV]Patch-based Generative Adversarial Network Towards Retinal Vessel Segmentation
    • [eess.IV]Rapid Whole-Heart CMR with Single Volume Super-resolution
    • [eess.IV]Re-Identification and Growth Detection of Pulmonary Nodules without Image Registration Using 3D Siamese Neural Networks
    • [eess.IV]Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach
    • [eess.IV]Spatio-Temporal Segmentation in 3D Echocardiographic Sequences using Fractional Brownian Motion
    • [eess.IV]UWGAN: Underwater GAN for Real-world Underwater Color Restoration and Dehazing
    • [eess.SP]Deep Learning Strategies For Joint Channel Estimation and Hybrid Beamforming in Multi-Carrier mm-Wave Massive MIMO Systems
    • [eess.SP]Low-Complexity Detection for Faster-than-Nyquist Signaling based on Probabilistic Data Association
    • [eess.SP]Reconfigurable Intelligent Surface Aided NOMA Networks
    • [eess.SY]Graphon-based sensitivity analysis of SIS epidemics
    • [eess.SY]Teaching robots to perceive time — A reinforcement learning approach (Extended version)
    • [math.AT]Approximation of Reeb spaces with Mappers and Applications to Stochastic Filters
    • [math.CO]Johnson Graph Codes
    • [math.NA]Simulating sticky particles: A Monte Carlo method to sample a Stratification
    • [math.OC]Analysis of Optimal Thresholding Algorithms for Compressed Sensing
    • [math.OC]Hamilton-Jacobi-Bellman Equations for Q-Learning in Continuous Time
    • [math.PR]A vector-contraction inequality for Rademacher complexities using $p$-stable variables
    • [math.ST]A note on the Regularity of Center-Outward Distribution and Quantile Functions
    • [math.ST]An improper estimator with optimal excess risk in misspecified density estimation and logistic regression
    • [math.ST]Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices
    • [math.ST]Foundations of Structural Statistics: Topological Statistical Theory
    • [math.ST]Improved Central Limit Theorem and bootstrap approximations in high dimensions
    • [math.ST]Persistent Homology of Graph Embeddings
    • [math.ST]Properties of Chromy’s sampling procedure
    • [physics.comp-ph]Simulating collective neutrinos oscillations on the Intel Many Integrated Core (MIC) architecture
    • [physics.flu-dyn]A physics-aware machine to predict extreme events in turbulence
    • [q-bio.NC]Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks
    • [q-bio.QM]iPromoter-BnCNN: a Novel Branched CNN Based Predictor for Identifying and Classifying Sigma Promoters
    • [q-fin.ST]DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News
    • [stat.AP]A Bayesian Application in Judicial Decisions
    • [stat.AP]Link prediction in dynamic networks using random dot product graphs
    • [stat.AP]Modelling basketball players’ performance and interactions between teammates with a regime switching approach
    • [stat.AP]On Information Coefficient and Directional Statistics
    • [stat.AP]Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections
    • [stat.AP]Quantifying demand and weather uncertainty in power system models using the m out of n bootstrap
    • [stat.AP]Simultaneous Inference for Empirical Best Predictors with a Poverty Study in Small Areas
    • [stat.AP]Using Small Domain Estimation to obtain better retrospective Age Period Cohort insights
    • [stat.CO]Blang: Bayesian declarative modelling of arbitrary data structures
    • [stat.CO]Missing data analysis and imputation via latent Gaussian Markov random fields
    • [stat.ME]A Symmetric Prior for Multinomial Probit Models
    • [stat.ME]Bayesian shape invariant model for longitudinal growth curve data
    • [stat.ME]Discussion of “Unbiased Markov chain Monte Carlo with couplings” by Pierre E. Jacob, John O’Leary and Yves F. Atchadé
    • [stat.ME]Pooled scale estimators for scaling prior to cluster analysis
    • [stat.ME]Randomization Tests in Observational Studies with Staggered Adoption of Treatment
    • [stat.ME]Study on upper limit of sample sizes for a two-level test in NIST SP800-22
    • [stat.ME]Testing the equality of multivariate means when $p>n$ by combining the Hoteling and Simes tests
    • [stat.ML]A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks
    • [stat.ML]Multilevel Monte Carlo estimation of log marginal likelihood
    • [stat.ML]Recreation of the Periodic Table with an Unsupervised Machine Learning Algorithm
    • [stat.ML]Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines
    • [stat.ML]Tensor Basis Gaussian Process Models of Hyperelastic Materials

    ·····································

    • [cs.AI]EvoMan: Game-playing Competition
    Fabricio Olivetti de Franca, Karine Miras, A. E. Eiben, Patricia Vargas
    http://arxiv.org/abs/1912.10445v1

    • [cs.AI]Learning Variable Ordering Heuristics for Solving Constraint Satisfaction Problems
    Wen Song, Zhiguang Cao, Jie Zhang, Andrew Lim
    http://arxiv.org/abs/1912.10762v1

    • [cs.AI]Questions to Guide the Future of Artificial Intelligence Research
    Jordan Ott
    http://arxiv.org/abs/1912.10305v1

    • [cs.AI]SensAI+Expanse Adaptation on Human Behaviour Towards Emotional Valence Prediction
    Nuno A. C. Henriques, Helder Coelho, Leonel Garcia-Marques
    http://arxiv.org/abs/1912.10084v1

    • [cs.AI]Sum-Product Network Decompilation
    Cory J. Butz, Jhonatan S. Oliveira, Robert Peharz
    http://arxiv.org/abs/1912.10092v1

    • [cs.CL]“The Squawk Bot”: Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering
    Xuan-Hong Dang, Syed Yousaf Shah, Petros Zerfos
    http://arxiv.org/abs/1912.10858v1

    • [cs.CL]A Machine Learning Framework for Authorship Identification From Texts
    Rahul Radhakrishnan Iyer, Carolyn Penstein Rose
    http://arxiv.org/abs/1912.10204v1

    • [cs.CL]AdvCodec: Towards A Unified Framework for Adversarial Text Generation
    Boxin Wang, Hengzhi Pei, Han Liu, Bo Li
    http://arxiv.org/abs/1912.10375v1

    • [cs.CL]BioConceptVec: creating and evaluating literature-based biomedical concept embeddings on a large scale
    Qingyu Chen, Kyubum Lee, Shankai Yan, Sun Kim, Chih-Hsuan Wei, Zhiyong Lu
    http://arxiv.org/abs/1912.10846v1

    • [cs.CL]Combining Context and Knowledge Representations for Chemical-Disease Relation Extraction
    Huiwei Zhou, Yunlong Yang, Shixian Ning, Zhuang Liu, Chengkun Lang, Yingyu Lin, Degen Huang
    http://arxiv.org/abs/1912.10604v1

    • [cs.CL]Exploring Context, Attention and Audio Features for Audio Visual Scene-Aware Dialog
    Shachi H Kumar, Eda Okur, Saurav Sahay, Jonathan Huang, Lama Nachman
    http://arxiv.org/abs/1912.10132v1

    • [cs.CL]Harnessing Evolution of Multi-Turn Conversations for Effective Answer Retrieval
    Mohammad Aliannejadi, Manajit Chakraborty, Esteban Andrés Ríssola, Fabio Crestani
    http://arxiv.org/abs/1912.10554v1

    • [cs.CL]Hunt Protagonist of Sentiment: Sentiment Analysis via Capsule Network with Sentiment-Aspect Reconstruction
    Chi Xu, Hao Feng, Xiang Ao
    http://arxiv.org/abs/1912.10785v1

    • [cs.CL]Hybrid Machine Learning Models of Classifying Residential Requests for Smart Dispatching
    T. Chen, J. Sun, H. Lin, Y. Liu
    http://arxiv.org/abs/1912.10546v1

    • [cs.CL]Knowledge-guided Convolutional Networks for Chemical-Disease Relation Extraction
    Huiwei Zhou, Chengkun Lang, Zhuang Liu, Shixian Ning, Yingyu Lin, Lei Du
    http://arxiv.org/abs/1912.10590v1

    • [cs.CL]Modeling Intent, Dialog Policies and Response Adaptation for Goal-Oriented Interactions
    Saurav Sahay, Shachi H Kumar, Eda Okur, Haroon Syed, Lama Nachman
    http://arxiv.org/abs/1912.10130v1

    • [cs.CL]Predicting Heart Failure Readmission from Clinical Notes Using Deep Learning
    Xiong Liu, Yu Chen, Jay Bae, Hu Li, Joseph Johnston, Todd Sanger
    http://arxiv.org/abs/1912.10306v1

    • [cs.CL]Probing the phonetic and phonological knowledge of tones in Mandarin TTS models
    Jian Zhu
    http://arxiv.org/abs/1912.10915v1

    • [cs.CL]Recurrent Hierarchical Topic-Guided Neural Language Models
    Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou
    http://arxiv.org/abs/1912.10337v1

    • [cs.CL]SberQuAD - Russian Reading Comprehension Dataset: Description and Analysis
    Pavel Efimov, Leonid Boytsov, Pavel Braslavski
    http://arxiv.org/abs/1912.09723v2

    • [cs.CL]Siamese Networks for Large-Scale Author Identification
    Chakaveh Saedi, Mark Dras
    http://arxiv.org/abs/1912.10616v1

    • [cs.CL]Tag-less Back-Translation
    Idris Abdulmumin, Bashir Shehu Galadanci, Aliyu Garba
    http://arxiv.org/abs/1912.10514v1

    • [cs.CL]What do Asian Religions Have in Common? An Unsupervised Text Analytics Exploration
    Preeti Sah, Ernest Fokoué
    http://arxiv.org/abs/1912.10847v1

    • [cs.CR]Dispel: Byzantine SMR with Distributed Pipelining
    Gauthier Voron, Vincent Gramoli
    http://arxiv.org/abs/1912.10367v1

    • [cs.CV]2DR1-PCA and 2DL1-PCA: two variant 2DPCA algorithms based on none L2 norm
    Xing Liu, Xiao-Jun Wu, Zi-Qi Li
    http://arxiv.org/abs/1912.10768v1

    • [cs.CV]5D Light Field Synthesis from a Monocular Video
    Kyuho Bae, Andre Ivan, Hajime Nagahara, In Kyu Park
    http://arxiv.org/abs/1912.10687v1

    • [cs.CV]A Compared Study Between Some Subspace Based Algorithms
    Xing Liu, Xiao-Jun Wu, Zhen Liu, He-Feng Yin
    http://arxiv.org/abs/1912.10657v1

    • [cs.CV]A Robust Non-Linear and Feature-Selection Image Fusion Theory
    Aiqing Fang, Xinbo Zhao, Yanning Zhang
    http://arxiv.org/abs/1912.10738v1

    • [cs.CV]A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D images
    Irem Ulku, Erdem Akagunduz
    http://arxiv.org/abs/1912.10230v1

    • [cs.CV]A sparse resultant based method for efficient minimal solvers
    Snehal Bhayani, Zuzana Kukelova, Janne Heikkilä
    http://arxiv.org/abs/1912.10268v1

    • [cs.CV]Active Learning for Segmentation Based on Bayesian Sample Queries
    Firat Ozdemir, Zixuan Peng, Philipp Fuernstahl, Christine Tanner, Orcun Goksel
    http://arxiv.org/abs/1912.10493v1

    • [cs.CV]Adversarial Cross-Domain Action Recognition with Co-Attention
    Boxiao Pan, Zhangjie Cao, Ehsan Adeli, Juan Carlos Niebles
    http://arxiv.org/abs/1912.10405v1

    • [cs.CV]Adversarial Feature Distribution Alignment for Semi-Supervised Learning
    Christoph Mayer, Matthieu Paul, Radu Timofte
    http://arxiv.org/abs/1912.10428v1

    • [cs.CV]Analysis of the hands in egocentric vision: A survey
    Andrea Bandini, José Zariffa
    http://arxiv.org/abs/1912.10867v1

    • [cs.CV]Assessing Data Quality of Annotations with Krippendorff Alpha For Applications in Computer Vision
    Joseph Nassar, Viveca Pavon-Harr, Marc Bosch, Ian McCulloh
    http://arxiv.org/abs/1912.10107v1

    • [cs.CV]CNN-generated images are surprisingly easy to spot… for now
    Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, Alexei A. Efros
    http://arxiv.org/abs/1912.11035v1

    • [cs.CV]Candidate Fusion: Integrating Language Modelling into a Sequence-to-Sequence Handwritten Word Recognition Architecture
    Lei Kang, Pau Riba, Mauricio Villegas, Alicia Fornés, Marçal Rusiñol
    http://arxiv.org/abs/1912.10308v1

    • [cs.CV]Continuity, Stability, and Integration: Novel Tracking-Based Perspectives for Temporal Object Detection
    Xingyu Chen, Zhengxing Wu, Junzhi Yu
    http://arxiv.org/abs/1912.10406v1

    • [cs.CV]Convolutional Neural Networks: A Binocular Vision Perspective
    Yigit Oktar, Diclehan Karakaya, Oguzhan Ulucan, Mehmet Turkan
    http://arxiv.org/abs/1912.10201v1

    • [cs.CV]Cross-Modal Image Fusion Theory Guided by Subjective Visual Attention
    Aiqing Fang, Xinbo Zhao, Yanning Zhang
    http://arxiv.org/abs/1912.10718v1

    • [cs.CV]DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration
    Wenxiao Wang, Shuai Zhao, Minghao Chen, Jinming Hu, Deng Cai, Haifeng Liu
    http://arxiv.org/abs/1912.10178v1

    • [cs.CV]DMCL: Distillation Multiple Choice Learning for Multimodal Action Recognition
    Nuno C. Garcia, Sarah Adel Bargal, Vitaly Ablavsky, Pietro Morerio, Vittorio Murino, Stan Sclaroff
    http://arxiv.org/abs/1912.10982v1

    • [cs.CV]Decoupled Attention Network for Text Recognition
    Tianwei Wang, Yuanzhi Zhu, Lianwen Jin, Canjie Luo, Xiaoxue Chen, Yaqiang Wu, Qianying Wang, Mingxiang Cai
    http://arxiv.org/abs/1912.10205v1

    • [cs.CV]Depth Completion via Deep Basis Fitting
    Chao Qu, Ty Nguyen, Camillo J. Taylor
    http://arxiv.org/abs/1912.10336v1

    • [cs.CV]Do Facial Expressions Predict Ad Sharing? A Large-Scale Observational Study
    Daniel McDuff, Jonah Berger
    http://arxiv.org/abs/1912.10311v1

    • [cs.CV]Eikonal Region-based Active Contours for Image Segmentation
    Da Chen, Jean-Marie Mirebeau, Huazhong Shu, Laurent D. Cohen
    http://arxiv.org/abs/1912.10122v1

    • [cs.CV]Eliminating cross-camera bias for vehicle re-identification
    Jinjia Peng, Guangqi Jiang, Dongyan Chen, Tongtong Zhao, Huibing Wang, Xianping Fu
    http://arxiv.org/abs/1912.10193v1

    • [cs.CV]Extracting urban water by combining deep learning and Google Earth Engine
    Y. D. Wang, Z. W. Li, C. Zeng, G. S. Xia, H. F. Shen
    http://arxiv.org/abs/1912.10726v1

    • [cs.CV]FasterSeg: Searching for Faster Real-time Semantic Segmentation
    Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang
    http://arxiv.org/abs/1912.10917v1

    • [cs.CV]From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality
    Zhenqiang Ying, Haoran Niu, Praful Gupta, Dhruv Mahajan, Deepti Ghadiyaram, Alan Bovik
    http://arxiv.org/abs/1912.10088v1

    • [cs.CV]Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction
    Yuan Yao, Nico Schertler, Enrique Rosales, Helge Rhodin, Leonid Sigal, Alla Sheffer
    http://arxiv.org/abs/1912.10589v1

    • [cs.CV]**Generalizing Deep Models for Overhead Image Segmentation Through Getis-Ord Gi Pooling
    Xueqing Deng, Yi Zhu, Yuxin Tian, Shawn Newsam
    http://arxiv.org/abs/1912.10667v1

    • [cs.CV]Geometry Sharing Network for 3D Point Cloud Classification and Segmentation
    Mingye Xu, Zhipeng Zhou, Yu Qiao
    http://arxiv.org/abs/1912.10644v1

    • [cs.CV]Graph-Based Parallel Large Scale Structure from Motion
    Yu Chen, Shuhan Shen, Yisong Chen, Guoping Wang
    http://arxiv.org/abs/1912.10659v1

    • [cs.CV]Image Outpainting and Harmonization using Generative Adversarial Networks
    Basile Van Hoorick
    http://arxiv.org/abs/1912.10960v1

    • [cs.CV]Jacobian Adversarially Regularized Networks for Robustness
    Alvin Chan, Yi Tay, Yew Soon Ong, Jie Fu
    http://arxiv.org/abs/1912.10185v1

    • [cs.CV]Joint Face Super-Resolution and Deblurring Using a Generative Adversarial Network
    Jung Un Yun, In Kyu Park
    http://arxiv.org/abs/1912.10427v1

    • [cs.CV]Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
    Zhenyi Wang, Ping Yu, Yang Zhao, Ruiyi Zhang, Yufan Zhou, Junsong Yuan, Changyou Chen
    http://arxiv.org/abs/1912.10150v1

    • [cs.CV]Learning to Generate Dense Point Clouds with Textures on Multiple Categories
    Tao Hu, Geng Lin, Zhizhong Han, Matthias Zwicker
    http://arxiv.org/abs/1912.10545v1

    • [cs.CV]Measuring Dataset Granularity
    Yin Cui, Zeqi Gu, Dhruv Mahajan, Laurens van der Maaten, Serge Belongie, Ser-Nam Lim
    http://arxiv.org/abs/1912.10154v1

    • [cs.CV]Minimal Solutions for Relative Pose with a Single Affine Correspondence
    Banglei Guan, Ji Zhao, Zhang Li, Fang Sun, Friedrich Fraundorfer
    http://arxiv.org/abs/1912.10776v1

    • [cs.CV]Multimodal Representation Model based on Graph-Based Rank Fusion
    Icaro Cavalcante Dourado, Salvatore Tabbone, Ricardo da Silva Torres
    http://arxiv.org/abs/1912.10314v1

    • [cs.CV]Neural Outlier Rejection for Self-Supervised Keypoint Learning
    Jiexiong Tang, Hanme Kim, Vitor Guizilini, Sudeep Pillai, Rares Ambrus
    http://arxiv.org/abs/1912.10615v1

    • [cs.CV]One-Shot Imitation Filming of Human Motion Videos
    Chong Huang, Yuanjie Dang, Peng Chen, Xin Yang, Kwang-Ting, Cheng
    http://arxiv.org/abs/1912.10609v1

    • [cs.CV]Oriented Objects as pairs of Middle Lines
    Haoran Wei, Lin Zhou, Yue Zhang, Hao Li, Rongxin Guo, Hongqi Wang, Xian Sun
    http://arxiv.org/abs/1912.10694v1

    • [cs.CV]Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling
    Wenkai Han, Chenglu Wen, Cheng Wang, Xin Li, Qing Li
    http://arxiv.org/abs/1912.10775v1

    • [cs.CV]Progressive DARTS: Bridging the Optimization Gap for NAS in the Wild
    Xin Chen, Lingxi Xie, Jun Wu, Qi Tian
    http://arxiv.org/abs/1912.10952v1

    • [cs.CV]RPGAN: GANs Interpretability via Random Routing
    Andrey Voynov, Artem Babenko
    http://arxiv.org/abs/1912.10920v1

    • [cs.CV]Research on Clustering Performance of Sparse Subspace Clustering
    Wen-Jin Fu, Xiao-Jun Wu, He-Feng Yin, Wen-Bo Hu
    http://arxiv.org/abs/1912.10256v1

    • [cs.CV]Robust Pose Invariant Shape and Texture based Hand Recognition
    F. Sohel, A. El-Sallam, M. Bennamoun
    http://arxiv.org/abs/1912.10373v1

    • [cs.CV]Saliency Based Fire Detection Using Texture and Color Features
    Maedeh Jamali, Nader Karimi, Shadrokh Samavi
    http://arxiv.org/abs/1912.10059v1

    • [cs.CV]Scale Match for Tiny Person Detection
    Xuehui Yu, Yuqi Gong, Nan Jiang, Qixiang Ye, Zhenjun Han
    http://arxiv.org/abs/1912.10664v1

    • [cs.CV]Seek and You Will Find: A New Optimized Framework for Efficient Detection of Pedestrian
    Sudip Das, Partha Sarathi Mukherjee, Ujjwal Bhattacharya
    http://arxiv.org/abs/1912.10241v1

    • [cs.CV]Style-based Variational Autoencoder for Real-World Super-Resolution
    Xin Ma, Yi Li, Huaibo Huang, Mandi Luo, Tanhao Hu, Ran He
    http://arxiv.org/abs/1912.10227v1

    • [cs.CV]The Five Elements of Flow
    Markus Hofinger, Samuel Rota Bulò, Lorenzo Porzi, Arno Knapitsch, Thomas Pock, Peter Kontschieder
    http://arxiv.org/abs/1912.10739v1

    • [cs.CV]Tifinagh-IRCAM Handwritten character recognition using Deep learning
    El Wardani Dadi
    http://arxiv.org/abs/1912.10338v1

    • [cs.CV]Towards Efficient Training for Neural Network Quantization
    Qing Jin, Linjie Yang, Zhenyu Liao
    http://arxiv.org/abs/1912.10207v1

    • [cs.CV]\emph{cm}SalGAN: RGB-D Salient Object Detection with Cross-View Generative Adversarial Networks
    Bo Jiang, Zitai Zhou, Xiao Wang, Jin Tang
    http://arxiv.org/abs/1912.10280v1

    • [cs.CY](Mis)Information Operations: An Integrated Perspective
    Matteo Cinelli, Mauro Conti, Livio Finos, Francesco Grisolia, Petra Kralj Novak, Antonio Peruzzi, Maurizio Tesconi, Fabiana Zollo, Walter Quattrociocchi
    http://arxiv.org/abs/1912.10795v1

    • [cs.CY]Teaching Responsible Data Science: Charting New Pedagogical Territory
    Julia Stoyanovich, Armanda Lewis
    http://arxiv.org/abs/1912.10564v1

    • [cs.DC]Jupiter: A Networked Computing Architecture
    Pradipta Ghosh, Quynh Nguyen, Pranav K Sakulkar, Aleksandra Knezevic, Jason A. Tran, Jiatong Wang, Zhifeng Lin, Bhaskar Krishnamachari, Murali Annavaram, Salman Avestimehr
    http://arxiv.org/abs/1912.10643v1

    • [cs.DC]Microchain: a Light Hierarchical Consensus Protocol for IoT System
    Ronghua Xu, Yu Chen
    http://arxiv.org/abs/1912.10357v1

    • [cs.GT]How Quantum Information can improve Social Welfare
    Berry Groisman, Michael Mc Gettrick, Mehdi Mhalla, Marcin Pawlowski
    http://arxiv.org/abs/1912.10967v1

    • [cs.HC]Emotion Recognition Using Wearables: A Systematic Literature Review Work in progress
    Stanisław Saganowski, Anna Dutkowiak, Adam Dziadek, Maciej Dzieżyc, Joanna Komoszyńska, Weronika Michalska, Adam Polak, Michał Ujma, Przemysław Kazienko
    http://arxiv.org/abs/1912.10528v1

    • [cs.HC]Experience Report: Towards Moving Things with Types — Helping Logistics Domain Experts to Control Cyber-Physical Systems with Type-Based Synthesis
    Jan Bessai, Moritz Roidl, Anna Vasileva
    http://arxiv.org/abs/1912.10628v1

    • [cs.IT]A Survey of NOMA: Current Status and Open Research Challenges
    Behrooz Makki, Krishna Chitti, Ali Behravan, Mohamed-Slim Alouini
    http://arxiv.org/abs/1912.10561v1

    • [cs.IT]An Efficient Deep Learning Framework for Low Rate Massive MIMO CSI Reporting
    Zhenyu Liu, Lin Zhang, Zhi Ding
    http://arxiv.org/abs/1912.10608v1

    • [cs.IT]Channel Estimation Method and Phase Shift Design for Reconfigurable Intelligent Surface Assisted MIMO Networks
    Jawad Mirza, Bakhtiar Ali
    http://arxiv.org/abs/1912.10671v1

    • [cs.IT]Compressive Sensing Based Channel Estimation for Millimeter-Wave Full-Dimensional MIMO with Lens-Array
    Ziwei Wan, Zhen Gao, Byonghyo Shim, Kai Yang, Guoqiang Mao, Mohamed-Slim Alouini
    http://arxiv.org/abs/1912.10668v1

    • [cs.IT]Direct and Indirect Effects — An Information Theoretic Perspective
    Gabriel Schamberg, William Chapman, Shang-Ping Xie, Todd P. Coleman
    http://arxiv.org/abs/1912.10508v1

    • [cs.IT]Energy-Aware Multi-Server Mobile Edge Computing: A Deep Reinforcement Learning Approach
    Navid Naderializadeh, Morteza Hashemi
    http://arxiv.org/abs/1912.10485v1

    • [cs.IT]Low-Complexity Random Rotation-based Schemes for Intelligent Reflecting Surfaces
    Constantinos Psomas, Ilias Chrysovergis, Ioannis Krikidis
    http://arxiv.org/abs/1912.10347v1

    • [cs.IT]Non-Orthogonal eMBB-URLLC Radio Access for Cloud Radio Access Networks with Analog Fronthauling
    Andrea Matera, Rahif Kassab, Osvaldo Simeone, Umberto Spagnolini
    http://arxiv.org/abs/1912.10519v1

    • [cs.IT]Overcoming the Channel Estimation Barrier in Massive MIMO Communication Systems
    Zhenyu Liu, Lin Zhang, Zhi Ding
    http://arxiv.org/abs/1912.10573v1

    • [cs.IT]Passive Beamforming and Information Transfer Design for Large Intelligent Surface Aided Multiuser MIMO Systems
    Wenjing Yan, Xiaojun~Yuan, Zhen-Qing He, Xiaoyan Kuai
    http://arxiv.org/abs/rg/abs/1912.10209v1

    • [cs.IT]Power Control for Massive MIMO Systems with Nonorthogonal Pilots
    Xihan Chen, Kaiming Shen, Hei Victor Cheng, An Liu, Wei Yu, Min-Jian Zhao
    http://arxiv.org/abs/1912.10187v1

    • [cs.IT]Progressive Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface with Discrete Phase Shifts
    Changsheng You, Beixiong Zheng, Rui Zhang
    http://arxiv.org/abs/1912.10646v1

    • [cs.IT]Trellis-Coded Non-Orthogonal Multiple Access
    Xun Zou, Mehdi Ganji, Hamid Jafarkhani
    http://arxiv.org/abs/1912.10074v1

    • [cs.LG]A Regression Framework for Predicting User’s Next Location using Call Detail Records
    Mohammad Saleh Mahdizadeh, Behnam Bahrak
    http://arxiv.org/abs/1912.10438v1

    • [cs.LG]A Survey of Deep Learning Applications to Autonomous Vehicle Control
    Sampo Kuutti, Richard Bowden, Yaochu Jin, Phil Barber, Saber Fallah
    http://arxiv.org/abs/1912.10773v1

    • [cs.LG]An optical diffractive deep neural network with multiple frequency-channels
    Yingshi Chen, Jinfeng Zhu
    http://arxiv.org/abs/1912.10730v1

    • [cs.LG]AutoML: Exploration v.s. Exploitation
    Hassan Eldeeb, Abdelrhman Eldallal
    http://arxiv.org/abs/1912.10746v1

    • [cs.LG]BackPACK: Packing more into backprop
    Felix Dangel, Frederik Kunstner, Philipp Hennig
    http://arxiv.org/abs/1912.10985v1

    • [cs.LG]Bandit Multiclass Linear Classification for the Group Linear Separable Case
    Jittat Fakcharoenphol, Chayutpong Prompak
    http://arxiv.org/abs/1912.10340v1

    • [cs.LG]Black Box Recursive Translations for Molecular Optimization
    Farhan Damani, Vishnu Sresht, Stephen Ra
    http://arxiv.org/abs/1912.10156v1

    • [cs.LG]Business Process Variant Analysis based on Mutual Fingerprints of Event Logs
    Farbod Taymouri, Marcello La Rosa, Josep Carmona
    http://arxiv.org/abs/1912.10598v1

    • [cs.LG]Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning
    Yanchao Sun, Furong Huang
    http://arxiv.org/abs/1912.10329v1

    • [cs.LG]Chart Auto-Encoders for Manifold Structured Data
    Stefan Schonsheck, Jie Chen, Rongjie Lai
    http://arxiv.org/abs/1912.10094v1

    • [cs.LG]Closed Form Variances for Variational Auto-Encoders
    Graham Fyffe
    http://arxiv.org/abs/1912.10309v1

    • [cs.LG]Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability
    Max Revay, Ian R. Manchester
    http://arxiv.org/abs/1912.10402v1

    • [cs.LG]Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data
    Ruocheng Guo, Jundong Li, Huan Liu
    http://arxiv.org/abs/1912.10536v1

    • [cs.LG]Data-Free Adversarial Distillation
    Gongfan Fang, Jie Song, Chengchao Shen, Xinchao Wang, Da Chen, Mingli Song
    http://arxiv.org/abs/1912.11006v1

    • [cs.LG]Deep Automodulators
    Ari Heljakka, Yuxin Hou, Juho Kannala, Arno Solin
    http://arxiv.org/abs/1912.10321v1

    • [cs.LG]Deep Learning via Dynamical Systems: An Approximation Perspective
    Qianxiao Li, Ting Lin, Zuowei Shen
    http://arxiv.org/abs/1912.10382v1

    • [cs.LG]Direct and indirect reinforcement learning
    Yang Guan, Shengbo Eben Li, Jingliang Duan, Jie Li, Yangang Ren, Bo Cheng
    http://arxiv.org/abs/1912.10600v1

    • [cs.LG]EAST: Encoding-Aware Sparse Training for Deep Memory Compression of ConvNets
    Matteo Grimaldi, Valentino Peluso, Andrea Calimera
    http://arxiv.org/abs/1912.10087v1

    • [cs.LG]Efficient Parameter Sampling for Neural Network Construction
    Drimik Roy Chowdhury, Muhammad Firmansyah Kasim
    http://arxiv.org/abs/1912.10559v1

    • [cs.LG]Estimation of Spectral Risk Measures
    Ajay Kumar Pandey, Prashanth L. A., Sanjay P. Bhat
    http://arxiv.org/abs/1912.10398v1

    • [cs.LG]Evaluating the Effectiveness of Margin Parameter when Learning Knowledge Embedding Representation for Domain-specific Multi-relational Categorized Data
    Matthew Wai Heng Chung, Hegler Tissot
    http://arxiv.org/abs/1912.10264v1

    • [cs.LG]Exploring TD error as a heuristic for $σ$ selection in Q($σ$, $λ$)
    Abhishek Nan
    http://arxiv.org/abs/1912.10316v1

    • [cs.LG]Finite-Time Analysis and Restarting Scheme for Linear Two-Time-Scale Stochastic Approximation
    Thinh T. Doan
    http://arxiv.org/abs/1912.10583v1

    • [cs.LG]Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction
    Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning
    http://arxiv.org/abs/1912.10202v1

    • [cs.LG]Hierarchical Target-Attentive Diagnosis Prediction in Heterogeneous Information Networks
    Anahita Hosseini, Tyler Davis, Majid Sarrafzadeh
    http://arxiv.org/abs/1912.10552v1

    • [cs.LG]How Robust Are Graph Neural Networks to Structural Noise?
    James Fox, Sivasankaran Rajamanickam
    http://arxiv.org/abs/1912.10206v1

    • [cs.LG]Interpreting Predictive Process Monitoring Benchmarks
    Renuka Sindhgatta, Chun Ouyang, Catarina Moreira, Yi Liao
    http://arxiv.org/abs/1912.10558v1

    • [cs.LG]Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
    Alexander Shevchenko, Marco Mondelli
    http://arxiv.org/abs/1912.10095v1

    • [cs.LG]Large Random Forests: Optimisation for Rapid Evaluation
    Frederik Gossen, Bernhard Steffen
    http://arxiv.org/abs/1912.10934v1

    • [cs.LG]Latent Variables on Spheres for Sampling and Spherical Inference
    Deli Zhao, Jiapeng Zhu, Bo Zhang
    http://arxiv.org/abs/1912.10233v1

    • [cs.LG]Layerwise Noise Maximisation to Train Low-Energy Deep Neural Networks
    Sébastien Henwood, François Leduc-Primeau, Yvon Savaria
    http://arxiv.org/abs/1912.10764v1

    • [cs.LG]Learn-able parameter guided Activation Functions
    S. Balaji, T. Kavya, Natasha Sebastian
    http://arxiv.org/abs/1912.10752v1

    • [cs.LG]Learning Improved Representations by Transferring Incomplete Evidence Across Heterogeneous Tasks
    Athanasios Davvetas, Iraklis A. Klampanos
    http://arxiv.org/abs/1912.10490v1

    • [cs.LG]Learning an Interpretable Traffic Signal Control Policy
    James Ault, Josiah Hanna, Guni Sharon
    http://arxiv.org/abs/1912.11023v1

    • [cs.LG]Learning to Impute: A General Framework for Semi-supervised Learning
    Wei-Hong Li, Chuan-Sheng Foo, Hakan Bilen
    http://arxiv.org/abs/1912.10364v1

    • [cs.LG]Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning
    Eun Seo Jo, Timnit Gebru
    http://arxiv.org/abs/1912.10389v1

    • [cs.LG]Monte-Carlo Tree Search for Policy Optimization
    Xiaobai Ma, Katherine Driggs-Campbell, Zongzhang Zhang, Mykel J. Kochenderfer
    http://arxiv.org/abs/1912.10648v1

    • [cs.LG]On Simulation and Trajectory Prediction with Gaussian Process Dynamics
    Lukas Hewing, Elena Arcari, Lukas P. Fröhlich, Melanie N. Zeilinger
    http://arxiv.org/abs/1912.10900v1

    • [cs.LG]On the Initialization of Long Short-Term Memory Networks
    Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, Marc Modat, M. Jorge Cardoso, Sebastien Ourselin, Lauge Sorensen
    http://arxiv.org/abs/1912.10454v1

    • [cs.LG]Online Reinforcement Learning of Optimal Threshold Policies for Markov Decision Processes
    Arghyadip Roy, Vivek Borkar, Abhay Karandikar, Prasanna Chaporkar
    http://arxiv.org/abs/1912.10325v1

    • [cs.LG]Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning
    Sheng Li, Maxim Egorov, Mykel Kochenderfer
    http://arxiv.org/abs/1912.10146v1

    • [cs.LG]Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning
    Tian Tan, Zhihan Xiong, Vikranth R. Dwaracherla
    http://arxiv.org/abs/1912.10577v1

    • [cs.LG]Privacy Attacks on Network Embeddings
    Michael Ellers, Michael Cochez, Tobias Schumacher, Markus Strohmaier, Florian Lemmerich
    http://arxiv.org/abs/1912.10979v1

    • [cs.LG]Quantile Propagation for Wasserstein-Approximate Gaussian Processes
    Rui Zhang, Christian J. Walder, Edwin V. Bonilla, Marian-Andrei Rizoiu, Lexing Xie
    http://arxiv.org/abs/1912.10200v1

    • [cs.LG]Recommendations and User Agency: The Reachability of Collaboratively-Filtered Information
    Sarah Dean, Sarah Rich, Benjamin Recht
    http://arxiv.org/abs/1912.10068v1

    • [cs.LG]Regularized Operating Envelope with Interpretability and Implementability Constraints
    Qiyao Wang, Haiyan Wang, Chetan Gupta, Susumu Serita
    http://arxiv.org/abs/1912.10158v1

    • [cs.LG]Spectral embedding of regularized block models
    Nathan de Lara, Thomas Bonald
    http://arxiv.org/abs/1912.10903v1

    • [cs.LG]TentacleNet: A Pseudo-Ensemble Template for Accurate Binary Convolutional Neural Networks
    Luca Mocerino, Andrea Calimera
    http://arxiv.org/abs/1912.10103v1

    • [cs.LG]TextNAS: A Neural Architecture Search Space tailored for Text Representation
    Yujing Wang, Yaming Yang, Yiren Chen, Jing Bai, Ce Zhang, Guinan Su, Xiaoyu Kou, Yunhai Tong, Mao Yang, Lidong Zhou
    http://arxiv.org/abs/1912.10729v1

    • [cs.LG]The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity
    Pedro Sandoval Segura, Julius Lauw, Daniel Bashir, Kinjal Shah, Sonia Sehra, Dominique Macias, George Montanez
    http://arxiv.org/abs/1912.10597v1

    • [cs.LG]The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
    Bin Dai, Ziyu Wang, David Wipf
    http://arxiv.org/abs/1912.10702v1

    • [cs.LG]Variational Recurrent Models for Solving Partially Observable Control Tasks
    Dongqi Han, Kenji Doya, Jun Tani
    http://arxiv.org/abs/1912.10703v1

    • [cs.LO]Bringing Belief Base Change into Dynamic Epistemic Logic
    Marlo Souza, Álvaro Moreira
    http://arxiv.org/abs/1912.10515v1

    • [cs.MA]A Survey of Deep Reinforcement Learning in Video Games
    Kun Shao, Zhentao Tang, Yuanheng Zhu, Nannan Li, Dongbin Zhao
    http://arxiv.org/abs/1912.10944v1

    • [cs.MM]Hiding Data in Images Using Cryptography and Deep Neural Network
    Kartik Sharma, Ashutosh Aggarwal, Tanay Singhania, Deepak Gupta, Ashish Khanna
    http://arxiv.org/abs/1912.10413v1

    • [cs.MM]Leveraging Topics and Audio Features with Multimodal Attention for Audio Visual Scene-Aware Dialog
    Shachi H Kumar, Eda Okur, Saurav Sahay, Jonathan Huang, Lama Nachman
    http://arxiv.org/abs/1912.10131v1

    • [cs.NE]Intelligent Wireless Sensor Nodes for Human Footstep Sound Classification for Security Application
    Anand Kumar Mukhopadhyay, Naligala Moses Prabhakar, Divya Lakshmi Duggisetty, Indrajit Chakrabarti, Mrigank Sharad
    http://arxiv.org/abs/1912.10905v1

    • [cs.NE]Multifactorial Evolutionary Algorithm For Clustered Minimum Routing Cost Problem
    Tran Ba Trung, Huynh Thi Thanh Binh, Le Tien Thanh, Ly Trung Hieu, Pham Dinh Thanh
    http://arxiv.org/abs/1912.10986v1

    • [cs.OS]Virtual Gang based Scheduling of Real-Time Tasks on Multicore Platforms
    Waqar Ali, Heechul Yun
    http://arxiv.org/abs/1912.10959v1

    • [cs.RO]A Multimodal Target-Source Classifier with Attention Branches to Understand Ambiguous Instructions for Fetching Daily Objects
    Aly Magassouba, Komei Sugiura, Hisashi Kawai
    http://arxiv.org/abs/1912.10675v1

    • [cs.RO]Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability
    Anjian Li, Somil Bansal, Georgios Giovanis, Varun Tolani, Claire Tomlin, Mo Chen
    http://arxiv.org/abs/1912.10120v1

    • [cs.RO]Joint Forward-Backward Visual Odometry for Stereo Cameras
    Raghav Sardana, Rahul Kottath, Vinod Karar, Shashi Poddar
    http://arxiv.org/abs/1912.10293v1

    • [cs.RO]Manipulation Planning and Control for Shelf Replenishment
    Marco Costanzo, Simon Stelter, Ciro Natale, Salvatore Pirozzi, Georg Bartels, Alexis Maldonado, Michael Beetz
    http://arxiv.org/abs/1912.11018v1

    • [cs.RO]Probabilistic Safety Constraints for Learned High Relative Degree System Dynamics
    Mohammad Javad Khojasteh, Vikas Dhiman, Massimo Franceschetti, Nikolay Atanasov
    http://arxiv.org/abs/1912.10116v1

    • [cs.RO]Safe and Fast Tracking Control on a Robot Manipulator: Robust MPC and Neural Network Control
    Julian Nubert, Johannes Köhler, Vincent Berenz, Frank Allgöwer, Sebastian Trimpe
    http://arxiv.org/abs/1912.10360v1

    • [cs.RO]Shared Autonomy in Web-based Human Robot Interaction
    Yug Ajmera, Arshad Javed
    http://arxiv.org/abs/1912.10274v1

    • [cs.RO]Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning
    Richard Li, Allan Jabri, Trevor Darrell, Pulkit Agrawal
    http://arxiv.org/abs/1912.11032v1

    • [cs.SD]Deep Audio Prior
    Yapeng Tian, Chenliang Xu, Dingzeyu Li
    http://arxiv.org/abs/1912.10292v1

    • [cs.SD]Emotion Recognition from Speech
    Kannan Venkataramanan, Haresh Rengaraj Rajamohan
    http://arxiv.org/abs/1912.10458v1

    • [cs.SD]Learning Singing From Speech
    Liqiang Zhang, Chengzhu Yu, Heng Lu, Chao Weng, Yusong Wu, Xiang Xie, Zijin Li, Dong Yu
    http://arxiv.org/abs/1912.10128v1

    • [cs.SE]An Overview on Smart Contracts: Challenges, Advances and Platforms
    Zibin Zheng, Shaoan Xie, Hong-Ning Dai, Weili Chen, Xiangping Chen, Jian Weng, Muhammad Imran
    http://arxiv.org/abs/1912.10370v1

    • [cs.SI]Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of Ethereum Graph
    Yitao Li, Umar Islambekov, Cuneyt Akcora, Ekaterina Smirnova, Yulia R. Gel, Murat Kantarcioglu
    http://arxiv.org/abs/1912.10105v1

    • [cs.SI]Mining the Automotive Industry: A Network Analysis of Corporate Positioning and Technological Trends
    Niklas Stoehr, Fabian Braesemann, Michael Frommelt, Shi Zhou
    http://arxiv.org/abs/1912.10097v1

    • [eess.AS]Mixture of Inference Networks for VAE-based Audio-visual Speech Enhancement
    Mostafa Sadeghi, Xavier Alameda-Pineda
    http://arxiv.org/abs/1912.10647v1

    • [eess.IV]A Generalizable Method for Automated Quality Control of Functional Neuroimaging Datasets
    Matthew Kollada, Qingzhu Gao, Monika S Mellem, Tathagata Banerjee, William J Martin
    http://arxiv.org/abs/1912.10127v1

    • [eess.IV]Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
    Vishal Monga, Yuelong Li, Yonina C. Eldar
    http://arxiv.org/abs/1912.10557v1

    • [eess.IV]Fully Automated Multi-Organ Segmentation in Abdominal Magnetic Resonance Imaging with Deep Neural Networks
    Yuhua Chen, Dan Ruan, Jiayu Xiao, Lixia Wang, Bin Sun, Rola Saouaf, Wensha Yang, Debiao Li, Zhaoyang Fan
    http://arxiv.org/abs/1912.11000v1

    • [eess.IV]Low radiation tomographic reconstruction with and without template information
    Preeti Gopal, Sharat Chandran, Imants Svalbe, Ajit Rajwade
    http://arxiv.org/abs/1912.11022v1

    • [eess.IV]Patch-based Generative Adversarial Network Towards Retinal Vessel Segmentation
    Waseem Abbas, Muhammad Haroon Shakeel, Numan Khurshid, Murtaza Taj
    http://arxiv.org/abs/1912.10377v1

    • [eess.IV]Rapid Whole-Heart CMR with Single Volume Super-resolution
    Jennifer A. Steeden, Michael Quail, Alexander Gotschy, Andreas Hauptmann, Simon Arridge, Rodney Jones, Vivek Muthurangu
    http://arxiv.org/abs/1912.10503v1

    • [eess.IV]Re-Identification and Growth Detection of Pulmonary Nodules without Image Registration Using 3D Siamese Neural Networks
    Xavier Rafael-Palou, Anton Aubanell, Ilaria Bonavita, Mario Ceresa, Gemma Piella, Vicent Ribas, Miguel Ángel González Ballester
    http://arxiv.org/abs/1912.10525v1

    • [eess.IV]Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach
    William Lotter, Abdul Rahman Diab, Bryan Haslam, Jiye G. Kim, Giorgia Grisot, Eric Wu, Kevin Wu, Jorge Onieva Onieva, Jerrold L. Boxerman, Meiyun Wang, Mack Bandler, Gopal Vijayaraghavan, A. Gregory Sorensen
    http://arxiv.org/abs/1912.11027v1

    • [eess.IV]Spatio-Temporal Segmentation in 3D Echocardiographic Sequences using Fractional Brownian Motion
    Omar S. Al-Kadi
    http://arxiv.org/abs/1912.10220v1

    • [eess.IV]UWGAN: Underwater GAN for Real-world Underwater Color Restoration and Dehazing
    Nan Wang, Yabin Zhou, Fenglei Han, Haitao Zhu, Yaojing Zheng
    http://arxiv.org/abs/1912.10269v1

    • [eess.SP]Deep Learning Strategies For Joint Channel Estimation and Hybrid Beamforming in Multi-Carrier mm-Wave Massive MIMO Systems
    Ahmet M. Elbir, Kumar Vijay Mishra
    http://arxiv.org/abs/1912.10036v1

    • [eess.SP]Low-Complexity Detection for Faster-than-Nyquist Signaling based on Probabilistic Data Association
    Michel Kulhandjian, Ebrahim Bedeer, Hovannes Kulhandjian, Claude D’Amours, Halim Yanikomeroglu
    http://arxiv.org/abs/1912.10315v1

    • [eess.SP]Reconfigurable Intelligent Surface Aided NOMA Networks
    Tianwei Hou, Student Member, IEEE, Yuanwei Liu, Senior Member, IEEE, Zhengyu Song, Xin Sun, Yue Chen, Senior Member, IEEE, Lajos Hanzo, Fellow, IEEE
    http://arxiv.org/abs/1912.10044v1

    • [eess.SY]Graphon-based sensitivity analysis of SIS epidemics
    Renato Vizuete, Paolo Frasca, Federica Garin
    http://arxiv.org/abs/1912.10330v1

    • [eess.SY]Teaching robots to perceive time — A reinforcement learning approach (Extended version)
    Inês Lourenço, Bo Wahlberg, Rodrigo Ventura
    http://arxiv.org/abs/1912.10113v1

    • [math.AT]Approximation of Reeb spaces with Mappers and Applications to Stochastic Filters
    Mathieu Carrière, Bertrand Michel
    http://arxiv.org/abs/1912.10742v1

    • [math.CO]Johnson Graph Codes
    Iwan Duursma, Xiao Li
    http://arxiv.org/abs/1912.10388v1

    • [math.NA]Simulating sticky particles: A Monte Carlo method to sample a Stratification
    Miranda Holmes-Cerfon
    http://arxiv.org/abs/1912.10176v1

    • [math.OC]Analysis of Optimal Thresholding Algorithms for Compressed Sensing
    Yun-Bin Zhao, Zhi-Quan Luo
    http://arxiv.org/abs/1912.10258v1

    • [math.OC]Hamilton-Jacobi-Bellman Equations for Q-Learning in Continuous Time
    Jeongho Kim, Insoon Yang
    http://arxiv.org/abs/1912.10697v1

    • [math.PR]A vector-contraction inequality for Rademacher complexities using $p$-stable variables
    Oscar Zatarain-Vera
    http://arxiv.org/abs/1912.10136v1

    • [math.ST]A note on the Regularity of Center-Outward Distribution and Quantile Functions
    Eustasio del Barrio, Alberto González-Sanz, Marc Hallin
    http://arxiv.org/abs/1912.10719v1

    • [math.ST]An improper estimator with optimal excess risk in misspecified density estimation and logistic regression
    Jaouad Mourtada, Stéphane Gaïffas
    http://arxiv.org/abs/1912.10784v1

    • [math.ST]Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices
    Jaouad Mourtada
    http://arxiv.org/abs/1912.10754v1

    • [math.ST]Foundations of Structural Statistics: Topological Statistical Theory
    Patrick Michl
    http://arxiv.org/abs/1912.10266v1

    • [math.ST]Improved Central Limit Theorem and bootstrap approximations in high dimensions
    Victor Chernozhukov, Denis Chetverikov, Kengo Kato, Yuta Koike
    http://arxiv.org/abs/1912.10529v1

    • [math.ST]Persistent Homology of Graph Embeddings
    Vinesh Solanki, Patrick Rubin-Delanchy, Ian Gallagher
    http://arxiv.org/abs/1912.10238v1

    • [math.ST]Properties of Chromy’s sampling procedure
    Guillaume Chauvet
    http://arxiv.org/abs/1912.10896v1

    • [physics.comp-ph]Simulating collective neutrinos oscillations on the Intel Many Integrated Core (MIC) architecture
    Vahid Noormofidi, Susan R. Atlas, Huaiyu Duan
    http://arxiv.org/abs/1912.10596v1

    • [physics.flu-dyn]A physics-aware machine to predict extreme events in turbulence
    Nguyen Anh Khoa Doan, Wolfgang Polifke, Luca Magri
    http://arxiv.org/abs/1912.10994v1

    • [q-bio.NC]Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks
    Christopher J. Cueva, Peter Y. Wang, Matthew Chin, Xue-Xin Wei
    http://arxiv.org/abs/1912.10189v1

    • [q-bio.QM]iPromoter-BnCNN: a Novel Branched CNN Based Predictor for Identifying and Classifying Sigma Promoters
    Ruhul Amin, Chowdhury Rafeed Rahman, Md. Habibur Rahman Sifat, Md Nazmul Khan Liton, Md. Moshiur Rahman, Swakkhar Shatabda, Sajid Ahmed
    http://arxiv.org/abs/1912.10251v1

    • [q-fin.ST]DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News
    Xinyi Li, Yinchuan Li, Hongyang Yang, Liuqing Yang, Xiao-Yang Liu
    http://arxiv.org/abs/1912.10806v1

    • [stat.AP]A Bayesian Application in Judicial Decisions
    Filipe J. Zabala
    http://arxiv.org/abs/1912.10566v1

    • [stat.AP]Link prediction in dynamic networks using random dot product graphs
    Francesco Sanna Passino, Anna S. Bertiger, Joshua C. Neil, Nicholas A. Heard
    http://arxiv.org/abs/1912.10419v1

    • [stat.AP]Modelling basketball players’ performance and interactions between teammates with a regime switching approach
    Paola Zuccolotto, Marco Sandri, Marica Manisera, Rodolfo Metulini
    http://arxiv.org/abs/1912.10417v1

    • [stat.AP]On Information Coefficient and Directional Statistics
    Yijian Chuan, Lan Wu
    http://arxiv.org/abs/1912.10709v1

    • [stat.AP]Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections
    Francis X. Diebold, Glenn D. Rudebusch
    http://arxiv.org/abs/1912.10774v1

    • [stat.AP]Quantifying demand and weather uncertainty in power system models using the m out of n bootstrap
    Adriaan P Hilbers, David J Brayshaw, Axel Gandy
    http://arxiv.org/abs/1912.10326v1

    • [stat.AP]Simultaneous Inference for Empirical Best Predictors with a Poverty Study in Small Areas
    Katarzyna Reluga, María-José Lombardía, Stefan Sperlich
    http://arxiv.org/abs/1912.11028v1

    • [stat.AP]Using Small Domain Estimation to obtain better retrospective Age Period Cohort insights
    Koen Simons, Rebecca Bentley, Lyle Gurrin
    http://arxiv.org/abs/1912.10372v1

    • [stat.CO]Blang: Bayesian declarative modelling of arbitrary data structures
    Alexandre Bouchard-Côté, Kevin Chern, Davor Cubranic, Sahand Hosseini, Justin Hume, Matteo Lepur, Zihui Ouyang, Giorgio Sgarbi
    http://arxiv.org/abs/1912.10396v1

    • [stat.CO]Missing data analysis and imputation via latent Gaussian Markov random fields
    Virgilio Gómez-Rubio, Michela Cameletti, Marta Blangiardo
    http://arxiv.org/abs/1912.10981v1

    • [stat.ME]A Symmetric Prior for Multinomial Probit Models
    Lane F. Burgette, David Puelz, P. Richard Hahn
    http://arxiv.org/abs/1912.10334v1

    • [stat.ME]Bayesian shape invariant model for longitudinal growth curve data
    Mohammad Alfrad Nobel Bhuiyan, Heidi Sucharew, Rhonda Szczesniak, Marepalli Rao, Jessica Woo, Jane Khoury, Md Monir Hossain
    http://arxiv.org/abs/1912.10842v1

    • [stat.ME]Discussion of “Unbiased Markov chain Monte Carlo with couplings” by Pierre E. Jacob, John O’Leary and Yves F. Atchadé
    Leah F. South, Chris Nemeth, Chris J. Oates
    http://arxiv.org/abs/1912.10496v1

    • [stat.ME]Pooled scale estimators for scaling prior to cluster analysis
    Jakob Raymaekers, Ruben H. Zamar
    http://arxiv.org/abs/1912.10492v1

    • [stat.ME]Randomization Tests in Observational Studies with Staggered Adoption of Treatment
    Azeem Shaikh, Panos Toulis
    http://arxiv.org/abs/1912.10610v1

    • [stat.ME]Study on upper limit of sample sizes for a two-level test in NIST SP800-22
    Hiroshi Haramoto
    http://arxiv.org/abs/1912.10602v1

    • [stat.ME]Testing the equality of multivariate means when $p>n$ by combining the Hoteling and Simes tests
    Tzviel Frostig, Yoav Benjamini
    http://arxiv.org/abs/1912.10472v1

    • [stat.ML]A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks
    Angelos Filos, Sebastian Farquhar, Aidan N. Gomez, Tim G. J. Rudner, Zachary Kenton, Lewis Smith, Milad Alizadeh, Arnoud de Kroon, Yarin Gal
    http://arxiv.org/abs/1912.10481v1

    • [stat.ML]Multilevel Monte Carlo estimation of log marginal likelihood
    Takashi Goda, Kei Ishikawa
    http://arxiv.org/abs/1912.10636v1

    • [stat.ML]Recreation of the Periodic Table with an Unsupervised Machine Learning Algorithm
    Minoru Kusaba, Chang Liu, Yukinori Koyama, Kiyoyuki Terakura, Ryo Yoshida
    http://arxiv.org/abs/1912.10708v1

    • [stat.ML]Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines
    Panagiotis Tsilifis, Iason Papaioannou, Daniel Straub, Fabio Nobile
    http://arxiv.org/abs/1912.11029v1

    • [stat.ML]Tensor Basis Gaussian Process Models of Hyperelastic Materials
    Ari Frankel, Reese Jones, Laura Swiler
    http://arxiv.org/abs/1912.10872v1