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.DM - 离散数学 cs.GT - 计算机科学与博弈论 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 econ.EM - 计量经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.PR - 概率 math.ST - 统计理论 physics.bio-ph - 生物物理 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-bio.PE - 人口与发展 quant-ph - 量子物理 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 stat.OT - 其他统计学
• [cs.AI]A Conditional Perspective for Iterated Belief Contraction
• [cs.AI]Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty through Sociotechnical Commitments
• [cs.AI]Towards Inconsistency Measurement in Business Rule Bases
• [cs.CL]A Comparative Study on End-to-end Speech to Text Translation
• [cs.CL]Aging Memories Generate More Fluent Dialogue Responses with Memory Networks
• [cs.CL]CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain
• [cs.CL]Casting a Wide Net: Robust Extraction of Potentially Idiomatic Expressions
• [cs.CL]Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension
• [cs.CL]Controlling Neural Machine Translation Formality with Synthetic Supervision
• [cs.CL]Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement
• [cs.CL]EmpGAN: Multi-resolution Interactive Empathetic Dialogue Generation
• [cs.CL]Global Greedy Dependency Parsing
• [cs.CL]Global Thread-Level Inference for Comment Classification in Community Question Answering
• [cs.CL]Joint Embedding Learning of Educational Knowledge Graphs
• [cs.CL]Joint Emotion Label Space Modelling for Affect Lexica
• [cs.CL]Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation
• [cs.CL]Natural Language Generation Challenges for Explainable AI
• [cs.CL]On Using SpecAugment for End-to-End Speech Translation
• [cs.CL]On using 2D sequence-to-sequence models for speech recognition
• [cs.CL]Paraphrasing Verbs for Noun Compound Interpretation
• [cs.CL]Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network
• [cs.CL]Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation Generation
• [cs.CL]Rule-Guided Compositional Representation Learning on Knowledge Graphs
• [cs.CL]SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings
• [cs.CL]Table-Of-Contents generation on contemporary documents
• [cs.CL]Zero-Shot Semantic Parsing for Instructions
• [cs.CR]Sieving Fake News From Genuine: A Synopsis
• [cs.CR]Web-sites password management (in)security: Evidence and remedies
• [cs.CV]3D-Rotation-Equivariant Quaternion Neural Networks
• [cs.CV]Action Recognition Using Volumetric Motion Representations
• [cs.CV]Analysis of Deep Networks for Monocular Depth Estimation Through Adversarial Attacks with Proposal of a Defense Method
• [cs.CV]Attention Guided Anomaly Detection and Localization in Images
• [cs.CV]CUP: Cluster Pruning for Compressing Deep Neural Networks
• [cs.CV]CoopNet: Cooperative Convolutional Neural Network for Low-Power MCUs
• [cs.CV]Cross-Class Relevance Learning for Temporal Concept Localization
• [cs.CV]D3S — A Discriminative Single Shot Segmentation Tracker
• [cs.CV]DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners
• [cs.CV]Deep Learning based HEp-2 Image Classification: A Comprehensive Review
• [cs.CV]Deep Motion Blur Removal Using Noisy/Blurry Image Pairs
• [cs.CV]DermGAN: Synthetic Generation of Clinical Skin Images with Pathology
• [cs.CV]Discriminative Local Sparse Representation by Robust Adaptive Dictionary Pair Learning
• [cs.CV]Efficient Derivative Computation for Cumulative B-Splines on Lie Groups
• [cs.CV]EfficientDet: Scalable and Efficient Object Detection
• [cs.CV]Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery
• [cs.CV]Event-based Object Detection and Tracking for Space Situational Awareness
• [cs.CV]Experimental Exploration of Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection
• [cs.CV]Explanation vs Attention: A Two-Player Game to Obtain Attention for VQA
• [cs.CV]Exploring the Origins and Prevalence of Texture Bias in Convolutional Neural Networks
• [cs.CV]Fast and Flexible Image Blind Denoising via Competition of Experts
• [cs.CV]Fine-grained Synthesis of Unrestricted Adversarial Examples
• [cs.CV]Hierarchical Attention Networks for Medical Image Segmentation
• [cs.CV]Hybrid Composition with IdleBlock: More Efficient Networks for Image Recognition
• [cs.CV]Improving Semantic Segmentation of Aerial Images Using Patch-based Attention
• [cs.CV]Instance-Invariant Adaptive Object Detection via Progressive Disentanglement
• [cs.CV]Joint Super-Resolution and Alignment of Tiny Faces
• [cs.CV]Learning Cross-modal Context Graph for Visual Grounding
• [cs.CV]Learning Modulated Loss for Rotated Object Detection
• [cs.CV]Learning Stylized Character Expressions from Humans
• [cs.CV]Learning mappings onto regularized latent spaces for biometric authentication
• [cs.CV]MMTM: Multimodal Transfer Module for CNN Fusion
• [cs.CV]MetH: A family of high-resolution and variable-shape image challenges
• [cs.CV]Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain
• [cs.CV]Mini Lesions Detection on Diabetic Retinopathy Images via Large Scale CNN Features
• [cs.CV]Modal-aware Features for Multimodal Hashing
• [cs.CV]Open Cross-Domain Visual Search
• [cs.CV]Real-time Scene Text Detection with Differentiable Binarization
• [cs.CV]RefineDetLite: A Lightweight One-stage Object Detection Framework for CPU-only Devices
• [cs.CV]SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation
• [cs.CV]Search to Distill: Pearls are Everywhere but not the Eyes
• [cs.CV]Self-supervised Learning of 3D Objects from Natural Images
• [cs.CV]Shift Convolution Network for Stereo Matching
• [cs.CV]Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication
• [cs.CV]Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping
• [cs.CV]The dynamics of the stomatognathic system from 4D multimodal data
• [cs.CV]Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN
• [cs.CV]Unified Multifaceted Feature Learning for Person Re-Identification
• [cs.CV]Unsupervised Monocular Depth Prediction for Indoor Continuous Video Streams
• [cs.CV]Utility Analysis of Network Architectures for 3D Point Cloud Processing
• [cs.CV]Vision: A Deep Learning Approach to provide walking assistance to the visually impaired
• [cs.CV]Weak Supervision for Generating Pixel-Level Annotations in Scene Text Segmentation
• [cs.CV]You Are Here: Geolocation by Embedding Maps and Images
• [cs.CY]Neural Approximate Dynamic Programming for On-Demand Ride-Pooling
• [cs.CY]Putting the SC in SCORE: Solar Car Optimized Route Estimation and Smart Cities
• [cs.DC]A Code injection Method for Rapid Docker Image Building
• [cs.DC]Auto-Precision Scaling for Distributed Deep Learning
• [cs.DC]Characterizing Scalability of Sparse Matrix-Vector Multiplications on Phytium FT-2000+ Many-cores
• [cs.DC]FeCaffe: FPGA-enabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10
• [cs.DC]How to profit from payments channels
• [cs.DC]Parallel Implementations for Computing the Minimum Distance of a Random Linear Code on Multicomputers
• [cs.DC]Robustness and efficiency of leaderless probabilistic consensus protocols within Byzantine infrastructures
• [cs.DM]Steepest ascent can be exponential in bounded treewidth problems
• [cs.GT]Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning
• [cs.IT]Decoding Polar Codes via Weighted-Window Soft Cancellation for Slowly-Varying Channel
• [cs.IT]On the Hamming distances of repeated-root cyclic codes of length $5p^s$
• [cs.IT]Online Power Allocation at Energy Harvesting Transmitter for Multiple Receivers with and without Individual Rate Constraints for OMA and NOMA Transmissions
• [cs.IT]Partially Permuted Multi-Trellis Belief Propagation for Polar Codes
• [cs.LG]A CNN-RNN Framework for Crop Yield Prediction
• [cs.LG]A Fast Sampling Gradient Tree Boosting Framework
• [cs.LG]A Framework for End-to-End Deep Learning-Based Anomaly Detection in Transportation Networks
• [cs.LG]Adaptive Wind Driven Optimization Trained Artificial Neural Networks
• [cs.LG]Adversarial Robustness of Flow-Based Generative Models
• [cs.LG]Avoiding Jammers: A Reinforcement Learning Approach
• [cs.LG]Bayesian Curiosity for Efficient Exploration in Reinforcement Learning
• [cs.LG]Black-box Combinatorial Optimization using Models with Integer-valued Minima
• [cs.LG]CAT: CRF-based ASR Toolkit
• [cs.LG]CNAK : Cluster Number Assisted K-means
• [cs.LG]Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data
• [cs.LG]Corruption Robust Exploration in Episodic Reinforcement Learning
• [cs.LG]DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
• [cs.LG]Deep Anomaly Detection with Deviation Networks
• [cs.LG]Deep Minimax Probability Machine
• [cs.LG]Deep Reinforcement Learning with Explicitly Represented Knowledge and Variable State and Action Spaces
• [cs.LG]Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks
• [cs.LG]Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
• [cs.LG]Efficient decorrelation of features using Gramian in Reinforcement Learning
• [cs.LG]Evaluating task-agnostic exploration for fixed-batch learning of arbitrary future tasks
• [cs.LG]Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking
• [cs.LG]Exponential Family Graph Embeddings
• [cs.LG]Fast and Deep Graph Neural Networks
• [cs.LG]Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation
• [cs.LG]Forbidden knowledge in machine learning — Reflections on the limits of research and publication
• [cs.LG]Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning
• [cs.LG]Generate (non-software) Bugs to Fool Classifiers
• [cs.LG]Graph-Driven Generative Models for Heterogeneous Multi-Task Learning
• [cs.LG]Gromov-Wasserstein Factorization Models for Graph Clustering
• [cs.LG]Heterogeneous Deep Graph Infomax
• [cs.LG]Heterogeneous Graph-based Knowledge Transfer for Generalized Zero-shot Learning
• [cs.LG]Hierarchical Average Reward Policy Gradient Algorithms
• [cs.LG]Inspect Transfer Learning Architecture with Dilated Convolution
• [cs.LG]Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees
• [cs.LG]Learning Embeddings from Cancer Mutation Sets for Classification Tasks
• [cs.LG]Learning Generalized Quasi-Geostrophic Models Using Deep Neural Numerical Models
• [cs.LG]Learning to Control Latent Representations for Few-Shot Learning of Named Entities
• [cs.LG]LionForests: Local Interpretation of Random Forests through Path Selection
• [cs.LG]Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates
• [cs.LG]Log Message Anomaly Detection and Classification Using Auto-B/LSTM and Auto-GRU
• [cs.LG]Logic-inspired Deep Neural Networks
• [cs.LG]Object-based multi-temporal and multi-source land cover mapping leveraging hierarchical class relationships
• [cs.LG]On Node Features for Graph Neural Networks
• [cs.LG]Outside the Box: Abstraction-Based Monitoring of Neural Networks
• [cs.LG]Representation Learning with Multisets
• [cs.LG]Response Transformation and Profit Decomposition for Revenue Uplift Modeling
• [cs.LG]Robust Learning of Discrete Distributions from Batches
• [cs.LG]Robust Triple-Matrix-Recovery-Based Auto-Weighted Label Propagation for Classification
• [cs.LG]Shapelets for earthquake detection
• [cs.LG]TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction
• [cs.LG]Towards a Unified Evaluation of Explanation Methods without Ground Truth
• [cs.LG]Transfer Learning Toolkit: Primers and Benchmarks
• [cs.LG]Understanding Top-k Sparsification in Distributed Deep Learning
• [cs.LG]Where is the Bottleneck of Adversarial Learning with Unlabeled Data?
• [cs.NE]Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems
• [cs.NE]Supported-BinaryNet: Bitcell Array-based Weight Supports for Dynamic Accuracy-Latency Trade-offs in SRAM-based Binarized Neural Network
• [cs.NI]Delay-Aware Wireless Network Coding in Adversarial Traffic
• [cs.RO]A Configuration-Space Decomposition Scheme for Learning-based Collision Checking
• [cs.RO]A Human Action Descriptor Based on Motion Coordination
• [cs.RO]Intermittent Connectivity for Exploration in Communication-Constrained Multi-Agent Systems
• [cs.RO]On Policy Learning Robust to Irreversible Events: An Application to Robotic In-Hand Manipulation
• [cs.RO]Path tracking control of self-reconfigurable robot hTetro with four differential drive units
• [cs.RO]Robust Lane Marking Detection Algorithm Using Drivable Area Segmentation and Extended SLT
• [cs.SD]Demystifying TasNet: A Dissecting Approach
• [cs.SD]Joint DNN-Based Multichannel Reduction of Acoustic Echo, Reverberation and Noise
• [cs.SE]Commit2Vec: Learning Distributed Representations of Code Changes
• [econ.EM]Statistical Inference on Partially Linear Panel Model under Unobserved Linearity
• [eess.IV]An Inception Inspired Deep Network to Analyse Fundus Images
• [eess.IV]Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction
• [eess.IV]Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models
• [eess.IV]Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution
• [eess.IV]Pan-Cancer Diagnostic Consensus Through Searching Archival Histopathology Images Using Artificial Intelligence
• [eess.IV]Segmentation of Defective Skulls from CT Data for Tissue Modelling
• [eess.IV]W-Net: Two-stage U-Net with misaligned data for raw-to-RGB mapping
• [eess.IV]Yottixel — An Image Search Engine for Large Archives of Histopathology Whole Slide Images
• [eess.SP]Multi-group Multicast Beamforming: Optimal Structure and Efficient Algorithms
• [eess.SP]Performance Monitoring for Live Systems with Soft FEC and Multilevel Modulation
• [math.PR]Sparse random tensors: concentration, regularization and applications
• [math.ST]Predictive properties of forecast combination, ensemble methods, and Bayesian predictive synthesis
• [physics.bio-ph]Machine Learning Classification Informed by a Functional Biophysical System
• [physics.comp-ph]Towards Physics-informed Deep Learning for Turbulent Flow Prediction
• [physics.soc-ph]Empirical model of campus air temperature and urban morphology parameters based on field measurement and machine learning in Singapore
• [physics.soc-ph]Multi-criteria community detection in International Trade Network
• [physics.soc-ph]Universal and non-universal text statistics: Clustering coefficient for language identification
• [q-bio.PE]Modeling the Temporal Population Distribution of Ae. aegypti Mosquito using Big Earth Observation Data
• [quant-ph]Stability of logarithmic Sobolev inequalities under a noncommutative change of measure
• [stat.AP]A Framework for Challenge Design: Insight and Deployment Challenges to Address Medical Image Analysis Problems
• [stat.AP]Bayesian Hierarchical Models for the Prediction of Volleyball Results
• [stat.AP]Ensuring Reliable Monte Carlo Estimates of Network Properties
• [stat.AP]Examining the impact of data quality and completeness of electronic health records on predictions of patients risks of cardiovascular disease
• [stat.AP]Weather event severity prediction using buoy data and machine learning
• [stat.CO]Replication-based emulation of the response distribution of stochastic simulators using generalized lambda distributions
• [stat.ME]Measuring spatiotemporal disease clustering with the tau statistic
• [stat.ME]Mixtures of multivariate generalized linear models with overlapping clusters
• [stat.ME]Parsimonious Mixtures of Matrix Variate Bilinear Factor Analyzers
• [stat.ME]Symbolic Formulae for Linear Mixed Models
• [stat.ML]Additive Bayesian Network Modelling with the R Package abn
• [stat.ML]Bayesian interpretation of SGD as Ito process
• [stat.ML]Bayesian sparse convex clustering via global-local shrinkage priors
• [stat.OT]Sharp hypotheses and bispatial inference
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• [cs.AI]A Conditional Perspective for Iterated Belief Contraction
Kai Sauerwald, Gabriele Kern-Isberner, Christoph Beierle
http://arxiv.org/abs/1911.08833v1
• [cs.AI]Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty through Sociotechnical Commitments
Roel Dobbe, Thomas Krendl Gilbert, Yonatan Mintz
http://arxiv.org/abs/1911.09005v1
• [cs.AI]Towards Inconsistency Measurement in Business Rule Bases
Carl Corea, Matthias Thimm
http://arxiv.org/abs/1911.08872v1
• [cs.CL]A Comparative Study on End-to-end Speech to Text Translation
Parnia Bahar, Tobias Bieschke, Hermann Ney
http://arxiv.org/abs/1911.08870v1
• [cs.CL]Aging Memories Generate More Fluent Dialogue Responses with Memory Networks
Omar U. Florez, Erik Mueller
http://arxiv.org/abs/1911.08522v1
• [cs.CL]CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain
Chaojun Xiao, Haoxi Zhong, Zhipeng Guo, Cunchao Tu, Zhiyuan Liu, Maosong Sun, Tianyang Zhang, Xianpei Han, Zhen hu, Heng Wang, Jianfeng Xu
http://arxiv.org/abs/1911.08962v1
• [cs.CL]Casting a Wide Net: Robust Extraction of Potentially Idiomatic Expressions
Hessel Haagsma, Malvina Nissim, Johan Bos
http://arxiv.org/abs/1911.08829v1
• [cs.CL]Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension
Xiaorui Zhou, Senlin Luo, Yunfang Wu
http://arxiv.org/abs/1911.08648v1
• [cs.CL]Controlling Neural Machine Translation Formality with Synthetic Supervision
Xing Niu, Marine Carpuat
http://arxiv.org/abs/1911.08706v1
• [cs.CL]Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement
Ting-En Lin, Hua Xu, Hanlei Zhang
http://arxiv.org/abs/1911.08891v1
• [cs.CL]EmpGAN: Multi-resolution Interactive Empathetic Dialogue Generation
Qintong Li, Hongshen Chen, Zhaochun Ren, Zhumin Chen, Zhaopeng Tu, Jun Ma
http://arxiv.org/abs/1911.08698v1
• [cs.CL]Global Greedy Dependency Parsing
Zuchao Li, Hai Zhao, Kevin Parnow
http://arxiv.org/abs/1911.08673v1
• [cs.CL]Global Thread-Level Inference for Comment Classification in Community Question Answering
Shafiq Joty, Alberto Barrón-Cedeño, Giovanni Da San Martino, Simone Filice, Lluís Màrquez, Alessandro Moschitti, Preslav Nakov
http://arxiv.org/abs/1911.08755v1
• [cs.CL]Joint Embedding Learning of Educational Knowledge Graphs
Siyu Yao, Ruijie Wang, Shen Sun, Derui Bu, Jun Liu
http://arxiv.org/abs/1911.08776v1
• [cs.CL]Joint Emotion Label Space Modelling for Affect Lexica
Luna De Bruyne, Pepa Atanasova, Isabelle Augenstein
http://arxiv.org/abs/1911.08782v1
• [cs.CL]Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation
Zequn Sun, Chengming Wang, Wei Hu, Muhao Chen, Jian Dai, Wei Zhang, Yuzhong Qu
http://arxiv.org/abs/1911.08936v1
• [cs.CL]Natural Language Generation Challenges for Explainable AI
Ehud Reiter
http://arxiv.org/abs/1911.08794v1
• [cs.CL]On Using SpecAugment for End-to-End Speech Translation
Parnia Bahar, Albert Zeyer, Ralf Schlüter, Hermann Ney
http://arxiv.org/abs/1911.08876v1
• [cs.CL]On using 2D sequence-to-sequence models for speech recognition
Parnia Bahar, Albert Zeyer, Ralf Schlüter, Hermann Ney
http://arxiv.org/abs/1911.08888v1
• [cs.CL]Paraphrasing Verbs for Noun Compound Interpretation
Preslav Nakov
http://arxiv.org/abs/1911.08762v1
• [cs.CL]Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network
Wenxiang Jiao, Michael R. Lyu, Irwin King
http://arxiv.org/abs/1911.09075v1
• [cs.CL]Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation Generation
Yew Ken Chia, Sam Witteveen, Martin Andrews
http://arxiv.org/abs/1911.08976v1
• [cs.CL]Rule-Guided Compositional Representation Learning on Knowledge Graphs
Guanglin Niu, Yongfei Zhang, Bo Li, Peng Cui, Si Liu, Jingyang Li, Xiaowei Zhang
http://arxiv.org/abs/1911.08935v1
• [cs.CL]SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings
Todor Mihaylov, Preslav Nakov
http://arxiv.org/abs/1911.08743v1
• [cs.CL]Table-Of-Contents generation on contemporary documents
Najah-Imane Bentabet, Rémi Juge, Sira Ferradans
http://arxiv.org/abs/1911.08836v1
• [cs.CL]Zero-Shot Semantic Parsing for Instructions
Ofer Givoli, Roi Reichart
http://arxiv.org/abs/1911.08827v1
• [cs.CR]Sieving Fake News From Genuine: A Synopsis
Shahid Alam, Abdulaziz Ravshanbekov
http://arxiv.org/abs/1911.08516v1
• [cs.CR]Web-sites password management (in)security: Evidence and remedies
Simone Raponi, Roberto Di Pietro
http://arxiv.org/abs/1911.08565v1
• [cs.CV]3D-Rotation-Equivariant Quaternion Neural Networks
Binbin Zhang, Wen Shen, Shikun Huang, Zhihua Wei, Quanshi Zhang
http://arxiv.org/abs/1911.09040v1
• [cs.CV]Action Recognition Using Volumetric Motion Representations
Michael Peven, Gregory D. Hager, Austin Reiter
http://arxiv.org/abs/1911.08511v1
• [cs.CV]Analysis of Deep Networks for Monocular Depth Estimation Through Adversarial Attacks with Proposal of a Defense Method
Junjie Hu, Takayuki Okatani
http://arxiv.org/abs/1911.08790v1
• [cs.CV]Attention Guided Anomaly Detection and Localization in Images
Shashanka Venkataramanan, Kuan-Chuan Peng, Rajat Vikram Singh, Abhijit Mahalanobis
http://arxiv.org/abs/1911.08616v1
• [cs.CV]CUP: Cluster Pruning for Compressing Deep Neural Networks
Rahul Duggal, Cao Xiao, Richard Vuduc, Jimeng Sun
http://arxiv.org/abs/1911.08630v1
• [cs.CV]CoopNet: Cooperative Convolutional Neural Network for Low-Power MCUs
Luca Mocerino, Andrea Calimera
http://arxiv.org/abs/1911.08606v1
• [cs.CV]Cross-Class Relevance Learning for Temporal Concept Localization
Junwei Ma, Satya Krishna Gorti, Maksims Volkovs, Ilya Stanevich, Guangwei Yu
http://arxiv.org/abs/1911.08548v1
• [cs.CV]D3S — A Discriminative Single Shot Segmentation Tracker
Alan Lukežič, Jiří Matas, Matej Kristan
http://arxiv.org/abs/1911.08862v1
• [cs.CV]DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners
Xiaolong Hu, Zhulin An, Chuanguang Yang, Hui Zhu, Kaiqaing Xu, Yongjun Xu
http://arxiv.org/abs/1911.08691v1
• [cs.CV]Deep Learning based HEp-2 Image Classification: A Comprehensive Review
Saimunur Rahman, Lei Wang, Changming Sun, Luping Zhou
http://arxiv.org/abs/1911.08916v1
• [cs.CV]Deep Motion Blur Removal Using Noisy/Blurry Image Pairs
Shuang Zhang, Ada Zhen, Robert L. Stevenson
http://arxiv.org/abs/1911.08541v1
• [cs.CV]DermGAN: Synthetic Generation of Clinical Skin Images with Pathology
Amirata Ghorbani, Vivek Natarajan, David Coz, Yuan Liu
http://arxiv.org/abs/1911.08716v1
• [cs.CV]Discriminative Local Sparse Representation by Robust Adaptive Dictionary Pair Learning
Yulin Sun, Zhao Zhang, Weiming Jiang, Zheng Zhang, Li Zhang, Shuicheng Yan, Meng Wang
http://arxiv.org/abs/1911.08680v1
• [cs.CV]Efficient Derivative Computation for Cumulative B-Splines on Lie Groups
Christiane Sommer, Vladyslav Usenko, David Schubert, Nikolaus Demmel, Daniel Cremers
http://arxiv.org/abs/1911.08860v1
• [cs.CV]EfficientDet: Scalable and Efficient Object Detection
Mingxing Tan, Ruoming Pang, Quoc V. Le
http://arxiv.org/abs/1911.09070v1
• [cs.CV]Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery
Yona Falinie A. Gaus, Neelanjan Bhowmik, Samet Akcay, Toby P. Breckon
http://arxiv.org/abs/1911.08966v1
• [cs.CV]Event-based Object Detection and Tracking for Space Situational Awareness
Saeed Afshar, Andrew P Nicholson, Andre van Schaik, Gregory Cohen
http://arxiv.org/abs/1911.08730v1
• [cs.CV]Experimental Exploration of Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection
Ganesh Samarth C. A., Neelanjan Bhowmik, Toby P. Breckon
http://arxiv.org/abs/1911.09010v1
• [cs.CV]Explanation vs Attention: A Two-Player Game to Obtain Attention for VQA
Badri N. Patro, Anupriy, Vinay P. Namboodiri
http://arxiv.org/abs/1911.08618v1
• [cs.CV]Exploring the Origins and Prevalence of Texture Bias in Convolutional Neural Networks
Katherine L. Hermann, Simon Kornblith
http://arxiv.org/abs/1911.09071v1
• [cs.CV]Fast and Flexible Image Blind Denoising via Competition of Experts
Shunta Maeda
http://arxiv.org/abs/1911.08724v1
• [cs.CV]Fine-grained Synthesis of Unrestricted Adversarial Examples
Omid Poursaeed, Tianxing Jiang, Harry Yang, Serge Belongie, Ser-Nam Lim
http://arxiv.org/abs/1911.09058v1
• [cs.CV]Hierarchical Attention Networks for Medical Image Segmentation
Fei Ding, Gang Yang, Jinlu Liu, Jun Wu, Dayong Ding, Jie Xv, Gangwei Cheng, Xirong Li
http://arxiv.org/abs/1911.08777v1
• [cs.CV]Hybrid Composition with IdleBlock: More Efficient Networks for Image Recognition
Bing Xu, Andrew Tulloch, Yunpeng Chen, Xiaomeng Yang, Lin Qiao
http://arxiv.org/abs/1911.08609v1
• [cs.CV]Improving Semantic Segmentation of Aerial Images Using Patch-based Attention
Lei Ding, Hao Tang, Lorenzo Bruzzone
http://arxiv.org/abs/1911.08877v1
• [cs.CV]Instance-Invariant Adaptive Object Detection via Progressive Disentanglement
Aming Wu, Yahong Han, Linchao Zhu, Yi Yang
http://arxiv.org/abs/1911.08712v1
• [cs.CV]Joint Super-Resolution and Alignment of Tiny Faces
Yu Yin, Joseph P. Robinson, Yulun Zhang, Yun Fu
http://arxiv.org/abs/1911.08566v1
• [cs.CV]Learning Cross-modal Context Graph for Visual Grounding
Yongfei Liu, Bo Wan, Xiaodan Zhu, Xuming He
http://arxiv.org/abs/1911.09042v1
• [cs.CV]Learning Modulated Loss for Rotated Object Detection
Wen Qian, Xue Yang, Silong Peng, Yue Guo, Chijun Yan
http://arxiv.org/abs/1911.08299v2
• [cs.CV]Learning Stylized Character Expressions from Humans
Deepali Aneja, Alex Colburn, Gary Faigin, Linda Shapiro, Barbara Mones
http://arxiv.org/abs/1911.08591v1
• [cs.CV]Learning mappings onto regularized latent spaces for biometric authentication
Matteo Testa, Arslan Ali, Tiziano Bianchi, Enrico Magli
http://arxiv.org/abs/1911.08764v1
• [cs.CV]MMTM: Multimodal Transfer Module for CNN Fusion
Hamid Reza Vaezi Joze, Amirreza Shaban, Michael L. Iuzzolino, Kazuhito Koishida
http://arxiv.org/abs/1911.08670v1
• [cs.CV]MetH: A family of high-resolution and variable-shape image challenges
Ferran Parés Pont, Dario Garcia-Gasulla, Harald Servat, Jesús Labarta, Eduard Ayguadé
http://arxiv.org/abs/1911.08953v1
• [cs.CV]Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain
Barak Battash, Haim Barad, Hanlin Tang, Amit Bleiweiss
http://arxiv.org/abs/1911.08206v2
• [cs.CV]Mini Lesions Detection on Diabetic Retinopathy Images via Large Scale CNN Features
Qilei Chen, Xinzi Sun, Ning Zhang, Yu Cao, Benyuan Liu
http://arxiv.org/abs/1911.08588v1
• [cs.CV]Modal-aware Features for Multimodal Hashing
Haien Zeng, Hanjiang Lai, Hanlu Chu, Yong Tang, Jian Yin
http://arxiv.org/abs/1911.08479v1
• [cs.CV]Open Cross-Domain Visual Search
William Thong, Pascal Mettes, Cees G. M. Snoek
http://arxiv.org/abs/1911.08621v1
• [cs.CV]Real-time Scene Text Detection with Differentiable Binarization
Minghui Liao, Zhaoyi Wan, Cong Yao, Kai Chen, Xiang Bai
http://arxiv.org/abs/1911.08947v1
• [cs.CV]RefineDetLite: A Lightweight One-stage Object Detection Framework for CPU-only Devices
Chen Chen, Mengyuan Liu, Xiandong Meng, Wanpeng Xiao, Qi Ju
http://arxiv.org/abs/1911.08855v1
• [cs.CV]SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation
Sheng Jin, Shangchen Zhou, Yao Liu, Chao Chen, Xiaoshuai Sun, Hongxun Yao, Xiansheng Hua
http://arxiv.org/abs/1911.08688v1
• [cs.CV]Search to Distill: Pearls are Everywhere but not the Eyes
Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang
http://arxiv.org/abs/1911.09074v1
• [cs.CV]Self-supervised Learning of 3D Objects from Natural Images
Hiroharu Kato, Tatsuya Harada
http://arxiv.org/abs/1911.08850v1
• [cs.CV]Shift Convolution Network for Stereo Matching
Jian Xie
http://arxiv.org/abs/1911.08896v1
• [cs.CV]Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication
Ankur Mali, Alexander G. Ororbia, Clyde Lee Giles
http://arxiv.org/abs/1911.08478v1
• [cs.CV]Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping
Uttaran Bhattacharya, Christian Roncal, Trisha Mittal, Rohan Chandra, Aniket Bera, Dinesh Manocha
http://arxiv.org/abs/1911.08708v1
• [cs.CV]The dynamics of the stomatognathic system from 4D multimodal data
Agnieszka A. Tomaka, Leszek Luchowski, Dariusz Pojda, Michał Tarnawski, Krzysztof Domino
http://arxiv.org/abs/1911.08854v1
• [cs.CV]Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN
Cun Xiaodong, Pun Chi-Man, Shi Cheng
http://arxiv.org/abs/1911.08718v1
• [cs.CV]Unified Multifaceted Feature Learning for Person Re-Identification
Cheng Yan, Guansong Pang, Xiao Bai, Chunhua Shen
http://arxiv.org/abs/1911.08651v1
• [cs.CV]Unsupervised Monocular Depth Prediction for Indoor Continuous Video Streams
Yinglong Feng, Shuncheng Wu, Okan Köpüklü, Xueyang Kang, Federico Tombari
http://arxiv.org/abs/1911.08995v1
• [cs.CV]Utility Analysis of Network Architectures for 3D Point Cloud Processing
Shikun Huang, Binbin Zhang, Wen Shen, Zhihua Wei, Quanshi Zhang
http://arxiv.org/abs/1911.09053v1
• [cs.CV]Vision: A Deep Learning Approach to provide walking assistance to the visually impaired
Nikhil Thakurdesai, Anupam Tripathi, Dheeraj Butani, Smita Sankhe
http://arxiv.org/abs/1911.08739v1
• [cs.CV]Weak Supervision for Generating Pixel-Level Annotations in Scene Text Segmentation
Simone Bonechi, Paolo Andreini, Monica Bianchini, Franco Scarselli
http://arxiv.org/abs/1911.09026v1
• [cs.CV]You Are Here: Geolocation by Embedding Maps and Images
Obed Samano Abonce, Mengjie Zhou, Andrew Calway
http://arxiv.org/abs/1911.08797v1
• [cs.CY]Neural Approximate Dynamic Programming for On-Demand Ride-Pooling
Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
http://arxiv.org/abs/1911.08842v1
• [cs.CY]Putting the SC in SCORE: Solar Car Optimized Route Estimation and Smart Cities
Mehrija Hasicic, Harun Siljak
http://arxiv.org/abs/1911.08940v1
• [cs.DC]A Code injection Method for Rapid Docker Image Building
Yujing Wang, Qinyang Bao
http://arxiv.org/abs/1911.07444v2
• [cs.DC]Auto-Precision Scaling for Distributed Deep Learning
Ruobing Han, Yang You, James Demmel
http://arxiv.org/abs/1911.08907v1
• [cs.DC]Characterizing Scalability of Sparse Matrix-Vector Multiplications on Phytium FT-2000+ Many-cores
Donglin Chen, Jianbin Fang, Chuanfu Xu, Shizhao Chen, Zheng Wang
http://arxiv.org/abs/1911.08779v1
• [cs.DC]FeCaffe: FPGA-enabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10
Ke He, Bo Liu, Yu Zhang, Andrew Ling, Dian Gu
http://arxiv.org/abs/1911.08905v1
• [cs.DC]How to profit from payments channels
Oguzhan Ersoy, Stefanie Ross, Zekeriya Erkin
http://arxiv.org/abs/1911.08803v1
• [cs.DC]Parallel Implementations for Computing the Minimum Distance of a Random Linear Code on Multicomputers
Gregorio Quintana-Ortí, Fernando Hernando, Francisco D. Igual
http://arxiv.org/abs/1911.08963v1
• [cs.DC]Robustness and efficiency of leaderless probabilistic consensus protocols within Byzantine infrastructures
Angelo Capossele, Sebastian Mueller, Andreas Penzkofer
http://arxiv.org/abs/1911.08787v1
• [cs.DM]Steepest ascent can be exponential in bounded treewidth problems
David A. Cohen, Martin C. Cooper, Artem Kaznatcheev, Mark Wallace
http://arxiv.org/abs/1911.08600v1
• [cs.GT]Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning
Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe
http://arxiv.org/abs/1911.08799v1
• [cs.IT]Decoding Polar Codes via Weighted-Window Soft Cancellation for Slowly-Varying Channel
Yong Fang
http://arxiv.org/abs/1911.08763v1
• [cs.IT]On the Hamming distances of repeated-root cyclic codes of length $5p^s$
Xia Li, Qin Yue
http://arxiv.org/abs/1911.07542v2
• [cs.IT]Online Power Allocation at Energy Harvesting Transmitter for Multiple Receivers with and without Individual Rate Constraints for OMA and NOMA Transmissions
Mateen Ashraf, Zijian Wang, Luc Vandendorpe
http://arxiv.org/abs/1911.08839v1
• [cs.IT]Partially Permuted Multi-Trellis Belief Propagation for Polar Codes
Vismika Ranasinghe, Nandana Rajatheva, Matti Latva-aho
http://arxiv.org/abs/1911.08868v1
• [cs.LG]A CNN-RNN Framework for Crop Yield Prediction
Saeed Khaki, Lizhi Wang, Sotirios V. Archontoulis
http://arxiv.org/abs/1911.09045v1
• [cs.LG]A Fast Sampling Gradient Tree Boosting Framework
Daniel Chao Zhou, Zhongming Jin, Tong Zhang
http://arxiv.org/abs/1911.08820v1
• [cs.LG]A Framework for End-to-End Deep Learning-Based Anomaly Detection in Transportation Networks
Neema Davis, Gaurav Raina, Krishna Jagannathan
http://arxiv.org/abs/1911.08793v1
• [cs.LG]Adaptive Wind Driven Optimization Trained Artificial Neural Networks
Zikri Bayraktar
http://arxiv.org/abs/1911.08942v1
• [cs.LG]Adversarial Robustness of Flow-Based Generative Models
Phillip Pope, Yogesh Balaji, Soheil Feizi
http://arxiv.org/abs/1911.08654v1
• [cs.LG]Avoiding Jammers: A Reinforcement Learning Approach
Serkan Ak, Stefan Bruggenwirth
http://arxiv.org/abs/1911.08874v1
• [cs.LG]Bayesian Curiosity for Efficient Exploration in Reinforcement Learning
Tom Blau, Lionel Ott, Fabio Ramos
http://arxiv.org/abs/1911.08701v1
• [cs.LG]Black-box Combinatorial Optimization using Models with Integer-valued Minima
Laurens Bliek, Sicco Verwer, Mathijs de Weerdt
http://arxiv.org/abs/1911.08817v1
• [cs.LG]CAT: CRF-based ASR Toolkit
Keyu An, Hongyu Xiang, Zhijian Ou
http://arxiv.org/abs/1911.08747v1
• [cs.LG]CNAK : Cluster Number Assisted K-means
Jayasree Saha, Jayanta Mukherjee
http://arxiv.org/abs/1911.08871v1
• [cs.LG]Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data
Azim Ahmadzadeh, Maxwell Hostetter, Berkay Aydin, Manolis K. Georgoulis, Dustin J. Kempton, Sushant S. Mahajan, Rafal A. Angryk
http://arxiv.org/abs/1911.09061v1
• [cs.LG]Corruption Robust Exploration in Episodic Reinforcement Learning
Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
http://arxiv.org/abs/1911.08689v1
• [cs.LG]DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
Ao Ren, Tao Zhang, Yuhao Wang, Sheng Lin, Peiyan Dong, Yen-kuang Chen, Yuan Xie, Yanzhi Wang
http://arxiv.org/abs/1911.08020v2
• [cs.LG]Deep Anomaly Detection with Deviation Networks
Guansong Pang, Chunhua Shen, Anton van den Hengel
http://arxiv.org/abs/1911.08623v1
• [cs.LG]Deep Minimax Probability Machine
Lirong He, Ziyi Guo, Kaizhu Huang, Zenglin Xu
http://arxiv.org/abs/1911.08723v1
• [cs.LG]Deep Reinforcement Learning with Explicitly Represented Knowledge and Variable State and Action Spaces
Jaromír Janisch, Tomáš Pevný, Viliam Lisý
http://arxiv.org/abs/1911.08756v1
• [cs.LG]Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks
Qun Liu, Lihua Fu, Meng Zhang
http://arxiv.org/abs/1911.08784v1
• [cs.LG]Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang
http://arxiv.org/abs/1911.08731v1
• [cs.LG]Efficient decorrelation of features using Gramian in Reinforcement Learning
Borislav Mavrin, Daniel Graves, Alan Chan
http://arxiv.org/abs/1911.08610v1
• [cs.LG]Evaluating task-agnostic exploration for fixed-batch learning of arbitrary future tasks
Vibhavari Dasagi, Robert Lee, Jake Bruce, Jürgen Leitner
http://arxiv.org/abs/1911.08666v1
• [cs.LG]Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking
Eric Crawford, Joelle Pineau
http://arxiv.org/abs/1911.09033v1
• [cs.LG]Exponential Family Graph Embeddings
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
http://arxiv.org/abs/1911.09007v1
• [cs.LG]Fast and Deep Graph Neural Networks
Claudio Gallicchio, Alessio Micheli
http://arxiv.org/abs/1911.08941v1
• [cs.LG]Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation
Junliang Guo, Xu Tan, Linli Xu, Tao Qin, Enhong Chen, Tie-Yan Liu
http://arxiv.org/abs/1911.08717v1
• [cs.LG]Forbidden knowledge in machine learning — Reflections on the limits of research and publication
Thilo Hagendorff
http://arxiv.org/abs/1911.08603v1
• [cs.LG]Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning
Xiang Ni, Jing Li, Mo Yu, Wang Zhou, Kun-Lung Wu
http://arxiv.org/abs/1911.08517v1
• [cs.LG]Generate (non-software) Bugs to Fool Classifiers
Hiromu Yakura, Youhei Akimoto, Jun Sakuma
http://arxiv.org/abs/1911.08644v1
• [cs.LG]Graph-Driven Generative Models for Heterogeneous Multi-Task Learning
Wenlin Wang, Hongteng Xu, Zhe Gan, Bai Li, Guoyin Wang, Liqun Chen, Qian Yang, Wenqi Wang, Lawrence Carin
http://arxiv.org/abs/1911.08709v1
• [cs.LG]Gromov-Wasserstein Factorization Models for Graph Clustering
Hongteng Xu
http://arxiv.org/abs/1911.08530v1
• [cs.LG]Heterogeneous Deep Graph Infomax
Yuxiang Ren, Bo Liu, Chao Huang, Peng Dai, Liefeng Bo, Jiawei Zhang
http://arxiv.org/abs/1911.08538v1
• [cs.LG]Heterogeneous Graph-based Knowledge Transfer for Generalized Zero-shot Learning
Junjie Wang, Xiangfeng Wang, Bo Jin, Junchi Yan, Wenjie Zhang, Hongyuan Zha
http://arxiv.org/abs/1911.09046v1
• [cs.LG]Hierarchical Average Reward Policy Gradient Algorithms
Akshay Dharmavaram, Matthew Riemer, Shalabh Bhatnagar
http://arxiv.org/abs/1911.08826v1
• [cs.LG]Inspect Transfer Learning Architecture with Dilated Convolution
Syeda Noor Jaha Azim, Md. Aminur Rab Ratul
http://arxiv.org/abs/1911.08769v1
• [cs.LG]Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees
Shaohuai Shi, Zhenheng Tang, Qiang Wang, Kaiyong Zhao, Xiaowen Chu
http://arxiv.org/abs/1911.08727v1
• [cs.LG]Learning Embeddings from Cancer Mutation Sets for Classification Tasks
Geoffroy Dubourg-Felonneau, Yasmeen Kussad, Dominic Kirkham, John W Cassidy, Nirmesh Patel, Harry W Clifford
http://arxiv.org/abs/1911.09008v1
• [cs.LG]Learning Generalized Quasi-Geostrophic Models Using Deep Neural Numerical Models
Redouane Lguensat, Julien Le Sommer, Sammy Metref, Emmanuel Cosme, Ronan Fablet
http://arxiv.org/abs/1911.08856v1
• [cs.LG]Learning to Control Latent Representations for Few-Shot Learning of Named Entities
Omar U. Florez, Erik Mueller
http://arxiv.org/abs/1911.08542v1
• [cs.LG]LionForests: Local Interpretation of Random Forests through Path Selection
Ioannis Mollas, Grigorios Tsoumakas, Nick Bassiliades
http://arxiv.org/abs/1911.08780v1
• [cs.LG]Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates
Cong Xie, Oluwasanmi Koyejo, Indranil Gupta, Haibin Lin
http://arxiv.org/abs/1911.09030v1
• [cs.LG]Log Message Anomaly Detection and Classification Using Auto-B/LSTM and Auto-GRU
Amir Farzad, T. Aaron Gulliver
http://arxiv.org/abs/1911.08744v1
• [cs.LG]Logic-inspired Deep Neural Networks
Minh Le
http://arxiv.org/abs/1911.08635v1
• [cs.LG]Object-based multi-temporal and multi-source land cover mapping leveraging hierarchical class relationships
Yawogan Jean Eudes Gbodjo, Dino Ienco, Louise Leroux, Roberto Interdonato, Raffaele Gaetano, Babacar Ndao, Stephane Dupuy
http://arxiv.org/abs/1911.08815v1
• [cs.LG]On Node Features for Graph Neural Networks
Chi Thang Duong, Thanh Dat Hoang, Ha The Hien Dang, Quoc Viet Hung Nguyen, Karl Aberer
http://arxiv.org/abs/1911.08795v1
• [cs.LG]Outside the Box: Abstraction-Based Monitoring of Neural Networks
Thomas A. Henzinger, Anna Lukina, Christian Schilling
http://arxiv.org/abs/1911.09032v1
• [cs.LG]Representation Learning with Multisets
Vasco Portilheiro
http://arxiv.org/abs/1911.08577v1
• [cs.LG]Response Transformation and Profit Decomposition for Revenue Uplift Modeling
Robin M. Gubela, Stefan Lessmann, Szymon Jaroszewicz
http://arxiv.org/abs/1911.08729v1
• [cs.LG]Robust Learning of Discrete Distributions from Batches
Ayush Jain, Alon Orlitsky
http://arxiv.org/abs/1911.08532v1
• [cs.LG]Robust Triple-Matrix-Recovery-Based Auto-Weighted Label Propagation for Classification
Huan Zhang, Zhao Zhang, Mingbo Zhao, Qiaolin Ye, Min Zhang, Meng Wang
http://arxiv.org/abs/1911.08678v1
• [cs.LG]Shapelets for earthquake detection
Monica Arul, Ahsan Kareem
http://arxiv.org/abs/1911.09086v1
• [cs.LG]TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction
Kaiqun Fu, Taoran Ji, Liang Zhao, Chang-Tien Lu
http://arxiv.org/abs/1911.08684v1
• [cs.LG]Towards a Unified Evaluation of Explanation Methods without Ground Truth
Hao Zhang, Jiayi Chen, Haotian Xue, Quanshi Zhang
http://arxiv.org/abs/1911.09017v1
• [cs.LG]Transfer Learning Toolkit: Primers and Benchmarks
Fuzhen Zhuang, Keyu Duan, Tongjia Guo, Yongchun Zhu, Dongbo Xi, Zhiyuan Qi, Qing He
http://arxiv.org/abs/1911.08967v1
• [cs.LG]Understanding Top-k Sparsification in Distributed Deep Learning
Shaohuai Shi, Xiaowen Chu, Ka Chun Cheung, Simon See
http://arxiv.org/abs/1911.08772v1
• [cs.LG]Where is the Bottleneck of Adversarial Learning with Unlabeled Data?
Jingfeng Zhang, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama
http://arxiv.org/abs/1911.08696v1
• [cs.NE]Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems
Jordan MacLachlan, Yi Mei, Juergen Branke, Mengjie Zhang
http://arxiv.org/abs/1911.08650v1
• [cs.NE]Supported-BinaryNet: Bitcell Array-based Weight Supports for Dynamic Accuracy-Latency Trade-offs in SRAM-based Binarized Neural Network
Shamma Nasrin, Srikanth Ramakrishna, Theja Tulabandhula, Amit Ranjan Trivedi
http://arxiv.org/abs/1911.08518v1
• [cs.NI]Delay-Aware Wireless Network Coding in Adversarial Traffic
Yu-Pin Hsu
http://arxiv.org/abs/1911.08078v2
• [cs.RO]A Configuration-Space Decomposition Scheme for Learning-based Collision Checking
Yiheng Han, Wang Zhao, Jia Pan, Zipeng Ye, Ran Yi, Yong-Jin Liu
http://arxiv.org/abs/1911.08581v1
• [cs.RO]A Human Action Descriptor Based on Motion Coordination
Pietro Falco, Matteo Saveriano, Eka Gibran Hasany, Nicholas H. Kirk, Dongheui Lee
http://arxiv.org/abs/1911.08928v1
• [cs.RO]Intermittent Connectivity for Exploration in Communication-Constrained Multi-Agent Systems
Filip Klaesson, Petter Nilsson, Aaron D. Ames, Richard M. Murray
http://arxiv.org/abs/1911.08626v1
• [cs.RO]On Policy Learning Robust to Irreversible Events: An Application to Robotic In-Hand Manipulation
Pietro Falco, Abdallah Attawia, Matteo Saveriano, Dongheui Lee
http://arxiv.org/abs/1911.08927v1
• [cs.RO]Path tracking control of self-reconfigurable robot hTetro with four differential drive units
Yuyao Shi, Mohan Rajesh Elara, Anh Vu Le, Veerajagadheswar Prabakaran, Kristin L. Wood
http://arxiv.org/abs/1911.08746v1
• [cs.RO]Robust Lane Marking Detection Algorithm Using Drivable Area Segmentation and Extended SLT
Umar Ozgunalp, Rui Fan, Shanshan Cheng, Yuxiang Sun, Weixun Zuo, Yilong Zhu, Bohuan Xue, Linwei Zheng, Qing Liang, Ming Liu
http://arxiv.org/abs/1911.09054v1
• [cs.SD]Demystifying TasNet: A Dissecting Approach
Jens Heitkaemper, Darius Jakobeit, Christoph Boeddeker, Lukas Drude, Reinhold Haeb-Umbach
http://arxiv.org/abs/1911.08895v1
• [cs.SD]Joint DNN-Based Multichannel Reduction of Acoustic Echo, Reverberation and Noise
Guillaume Carbajal, Romain Serizel, Emmanuel Vincent, Eric Humbert
http://arxiv.org/abs/1911.08934v1
• [cs.SE]Commit2Vec: Learning Distributed Representations of Code Changes
Rocìo Cabrera Lozoya, Arnaud Baumann, Antonino Sabetta, Michele Bezzi
http://arxiv.org/abs/1911.07605v3
• [econ.EM]Statistical Inference on Partially Linear Panel Model under Unobserved Linearity
Ruiqi Liu, Ben Boukai, Zuofeng Shang
http://arxiv.org/abs/1911.08830v1
• [eess.IV]An Inception Inspired Deep Network to Analyse Fundus Images
Fatmatulzehra Uslu
http://arxiv.org/abs/1911.08715v1
• [eess.IV]Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction
Shuo Wang, Chengliang Dai, Yuanhan Mo, Elsa Angelini, Yike Guo, Wenjia Bai
http://arxiv.org/abs/1911.08483v1
• [eess.IV]Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models
Xin He, Shihao Wang, Shaohuai Shi, Zhenheng Tang, Yuxin Wang, Zhihao Zhao, Jing Dai, Ronghao Ni, Xiaofeng Zhang, Xiaoming Liu, Zhili Wu, Wu Yu, Xiaowen Chu
http://arxiv.org/abs/1911.08705v1
• [eess.IV]Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution
Chih-Chung Hsu, Chia-Hsiang Lin
http://arxiv.org/abs/1911.08711v1
• [eess.IV]Pan-Cancer Diagnostic Consensus Through Searching Archival Histopathology Images Using Artificial Intelligence
Shivam Kalra, H. R. Tizhoosh, Sultaan Shah, Charles Choi, Savvas Damaskinos, Amir Safarpoor, Sobhan Shafiei, Morteza Babaie, Phedias Diamandis, Clinton JV Campbell, Liron Pantanowitz
http://arxiv.org/abs/1911.08736v1
• [eess.IV]Segmentation of Defective Skulls from CT Data for Tissue Modelling
Oldřich Kodym, Michal Španěl, Adam Herout
http://arxiv.org/abs/1911.08805v1
• [eess.IV]W-Net: Two-stage U-Net with misaligned data for raw-to-RGB mapping
Kwang Hyun Uhm, Seung-Wook Kim, Seo-Won Ji, Sungjin Cho, Jun Pyo Hong, Sung-Jea Ko
http://arxiv.org/abs/1911.08656v1
• [eess.IV]Yottixel — An Image Search Engine for Large Archives of Histopathology Whole Slide Images
S. Kalra, C. Choi, S. Shah, L. Pantanowitz, H. R. Tizhoosh
http://arxiv.org/abs/1911.08748v1
• [eess.SP]Multi-group Multicast Beamforming: Optimal Structure and Efficient Algorithms
Min Dong, Qiqi Wang
http://arxiv.org/abs/1911.08925v1
• [eess.SP]Performance Monitoring for Live Systems with Soft FEC and Multilevel Modulation
Tsuyoshi Yoshida, Mikael Mazur, Jochen Schröder, Magnus Karlsson, Erik Agrell
http://arxiv.org/abs/1911.08641v1
• [math.PR]Sparse random tensors: concentration, regularization and applications
Zhixin Zhou, Yizhe Zhu
http://arxiv.org/abs/1911.09063v1
• [math.ST]Predictive properties of forecast combination, ensemble methods, and Bayesian predictive synthesis
Kosaku Takanashi, Kenichiro McAlinn
http://arxiv.org/abs/1911.08662v1
• [physics.bio-ph]Machine Learning Classification Informed by a Functional Biophysical System
Jason A. Platt, Anna Miller, Henry D. I. Abarbanel
http://arxiv.org/abs/1911.08589v1
• [physics.comp-ph]Towards Physics-informed Deep Learning for Turbulent Flow Prediction
Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu
http://arxiv.org/abs/1911.08655v1
• [physics.soc-ph]Empirical model of campus air temperature and urban morphology parameters based on field measurement and machine learning in Singapore
Zhongqi Yu, Shisheng Chen, Nyuk Hien Wong, Marcel Ignatius, Jiyu Deng, Yueer He, Daniel Jun Chung Hii
http://arxiv.org/abs/1911.08822v1
• [physics.soc-ph]Multi-criteria community detection in International Trade Network
Paolo Bartesaghi, Stefano Benati, Gian Paolo Clemente, Rosanna Grassi
http://arxiv.org/abs/1911.08593v1
• [physics.soc-ph]Universal and non-universal text statistics: Clustering coefficient for language identification
Diego Espitia, Hernán Larralde
http://arxiv.org/abs/1911.08915v1
• [q-bio.PE]Modeling the Temporal Population Distribution of Ae. aegypti Mosquito using Big Earth Observation Data
Oladimeji Mudele, Fabio M. Bayer, Lucas Zanandrez, Alvaro E. Eiras, Paolo Gamba
http://arxiv.org/abs/1911.08979v1
• [quant-ph]Stability of logarithmic Sobolev inequalities under a noncommutative change of measure
Marius Junge, Nicholas LaRacuente, Cambyse Rouzé
http://arxiv.org/abs/1911.08533v1
• [stat.AP]A Framework for Challenge Design: Insight and Deployment Challenges to Address Medical Image Analysis Problems
Adriënne M. Mendrik, Stephen R. Aylward
http://arxiv.org/abs/1911.08531v1
• [stat.AP]Bayesian Hierarchical Models for the Prediction of Volleyball Results
Andrea Gabrio
http://arxiv.org/abs/1911.08791v1
• [stat.AP]Ensuring Reliable Monte Carlo Estimates of Network Properties
Haema Nilakanta, Zack W. Almquist, Galin L. Jones
http://arxiv.org/abs/1911.08682v1
• [stat.AP]Examining the impact of data quality and completeness of electronic health records on predictions of patients risks of cardiovascular disease
Yan Li, Matthew Sperrin, Glen P. Martin, Darren M Ashcroft, Tjeerd Pieter van Staa
http://arxiv.org/abs/1911.08504v1
• [stat.AP]Weather event severity prediction using buoy data and machine learning
Vikas Ramachandra
http://arxiv.org/abs/1911.09001v1
• [stat.CO]Replication-based emulation of the response distribution of stochastic simulators using generalized lambda distributions
X. Zhu, B. Sudret
http://arxiv.org/abs/1911.09067v1
• [stat.ME]Measuring spatiotemporal disease clustering with the tau statistic
Timothy M. Pollington, Michael J. Tildesley, T. Déirdre Hollingsworth, Lloyd A. C. Chapman
http://arxiv.org/abs/1911.08022v2
• [stat.ME]Mixtures of multivariate generalized linear models with overlapping clusters
Saverio Ranciati, Veronica Vinciotti, Ernst C. Wit, Giuliano Galimberti
http://arxiv.org/abs/1911.08955v1
• [stat.ME]Parsimonious Mixtures of Matrix Variate Bilinear Factor Analyzers
Michael P. B. Gallaugher, Paul D. McNicholas
http://arxiv.org/abs/1911.09012v1
• [stat.ME]Symbolic Formulae for Linear Mixed Models
Emi Tanaka, Francis K. C. Hui
http://arxiv.org/abs/1911.08628v1
• [stat.ML]Additive Bayesian Network Modelling with the R Package abn
Gilles Kratzer, Fraser Iain Lewis, Arianna Comin, Marta Pittavino, Reinhard Furrer
http://arxiv.org/abs/1911.09006v1
• [stat.ML]Bayesian interpretation of SGD as Ito process
Soma Yokoi, Issei Sato
http://arxiv.org/abs/1911.09011v1
• [stat.ML]Bayesian sparse convex clustering via global-local shrinkage priors
Kaito Shimamura, Shuichi Kawano
http://arxiv.org/abs/1911.08703v1
• [stat.OT]Sharp hypotheses and bispatial inference
Russell J. Bowater
http://arxiv.org/abs/1911.09049v1