astro-ph.EP - 地球与行星天体
cs.AI - 人工智能 cs.AR - 硬件体系结构 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.DS - 数据结构与算法 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 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.PF - 计算性能 cs.RO - 机器人学 cs.SD - 声音处理 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.CO - 组合数学 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.chem-ph -化学物理 physics.soc-ph - 物理学与社会 q-bio.PE - 人口与发展 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [astro-ph.EP]Machine Learning for Semi-Automated Meteorite Recovery
• [cs.AI]Analysis of the displacement of terrestrial mobile robots in corridors using paraconsistent annotated evidential logic eτ
• [cs.AI]Cross Learning in Deep Q-Networks
• [cs.AI]Explainable AI without Interpretable Model
• [cs.AI]Joint Spatio-Textual Reasoning for Answering Tourism Questions
• [cs.AI]Large-Scale Cargo Distribution
• [cs.AI]Multi-objective Reinforcement Learning based approach for User-Centric Power Optimization in Smart Home Environments
• [cs.AI]Neural Model-based Optimization with Right-Censored Observations
• [cs.AI]Research and Education Towards Smart and Sustainable World
• [cs.AI]The design and implementation of Language Learning Chatbot with XAI using Ontology and Transfer Learning
• [cs.AI]Towards a Measure of Individual Fairness for Deep Learning
• [cs.AI]Understanding Human Intelligence through Human Limitations
• [cs.AI]{Playing Carcassonne with Monte Carlo Tree Search
• [cs.AR]Breaking the Memory Wall for AI Chip with a New Dimension
• [cs.CL]A Simple and Efficient Ensemble Classifier Combining Multiple Neural Network Models on Social Media Datasets in Vietnamese
• [cs.CL]A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation
• [cs.CL]A Survey on Semantic Parsing from the perspective of Compositionality
• [cs.CL]Aligning Intraobserver Agreement by Transitivity
• [cs.CL]Building Legal Case Retrieval Systems with Lexical Matching and Summarization using A Pre-Trained Phrase Scoring Model
• [cs.CL]Contextual Knowledge Selection and Embedding towards Enhanced Pre-Trained Language Models
• [cs.CL]Contrastive Distillation on Intermediate Representations for Language Model Compression
• [cs.CL]Conversational Semantic Parsing
• [cs.CL]DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialogue
• [cs.CL]Double Graph Based Reasoning for Document-level Relation Extraction
• [cs.CL]Fake News Spreader Detection on Twitter using Character N-Grams. Notebook for PAN at CLEF 2020
• [cs.CL]GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
• [cs.CL]HINT3: Raising the bar for Intent Detection in the Wild
• [cs.CL]Improve Transformer Models with Better Relative Position Embeddings
• [cs.CL]Improving Low Compute Language Modeling with In-Domain Embedding Initialisation
• [cs.CL]Leader: Prefixing a Length for Faster Word Vector Serialization
• [cs.CL]Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems
• [cs.CL]Neural Retrieval for Question Answering with Cross-Attention Supervised Data Augmentation
• [cs.CL]Neural Topic Modeling by Incorporating Document Relationship Graph
• [cs.CL]Neural Topic Modeling with Cycle-Consistent Adversarial Training
• [cs.CL]Parsing with Multilingual BERT, a Small Corpus, and a Small Treebank
• [cs.CL]Sequence-to-Sequence Learning for Indonesian Automatic Question Generator
• [cs.CL]SynSetExpan: An Iterative Framework for Joint Entity Set Expansion and Synonym Discovery
• [cs.CL]TernaryBERT: Distillation-aware Ultra-low Bit BERT
• [cs.CL]Transformers Are Better Than Humans at Identifying Generated Text
• [cs.CL]Utility is in the Eye of the User: A Critique of NLP Leaderboards
• [cs.CL]Utterance-level Dialogue Understanding: An Empirical Study
• [cs.CL]Visual Pivoting for (Unsupervised) Entity Alignment
• [cs.CR]A Distributed Computing Perspective of Unconditionally Secure Information Transmission in Russian Cards Problems
• [cs.CR]Oblivious Sampling Algorithms for Private Data Analysis
• [cs.CV]A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification
• [cs.CV]A Comprehensive Review for MRF and CRF Approaches in Pathology Image Analysis
• [cs.CV]A Flow Base Bi-path Network for Cross-scene Video Crowd Understanding in Aerial View
• [cs.CV]A Prototype-Based Generalized Zero-Shot Learning Framework for Hand Gesture Recognition
• [cs.CV]A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection
• [cs.CV]A Survey on Deep Learning Techniques for Video Anomaly Detection
• [cs.CV]A comparison of classical and variational autoencoders for anomaly detection
• [cs.CV]Adaptive confidence thresholding for semi-supervised monocular depth estimation
• [cs.CV]An Image Processing Pipeline for Automated Packaging Structure Recognition
• [cs.CV]Asymmetric Loss For Multi-Label Classification
• [cs.CV]Attentional Feature Fusion
• [cs.CV]BAMSProd: A Step towards Generalizing the Adaptive Optimization Methods to Deep Binary Model
• [cs.CV]Beneficial Perturbation Network for designing general adaptive artificial intelligence systems
• [cs.CV]CoKe: Localized Contrastive Learning for Robust Keypoint Detection
• [cs.CV]Cross-Task Representation Learning for Anatomical Landmark Detection
• [cs.CV]Deep discriminant analysis for task-dependent compact network search
• [cs.CV]Detecting soccer balls with reduced neural networks: a comparison of multiple architectures under constrained hardware scenarios
• [cs.CV]Fast Gravitational Approach for Rigid Point Set Registration with Ordinary Differential Equations
• [cs.CV]Fully Automated Left Atrium Segmentation from Anatomical Cine Long-axis MRI Sequences using Deep Convolutional Neural Network with Unscented Kalman Filter
• [cs.CV]Geometric Loss for Deep Multiple Sclerosis lesion Segmentation
• [cs.CV]Graph-based methods for analyzing orchard tree structure using noisy point cloud data
• [cs.CV]Improving Interpretability for Computer-aided Diagnosis tools on Whole Slide Imaging with Multiple Instance Learning and Gradient-based Explanations
• [cs.CV]Kernel Based Progressive Distillation for Adder Neural Networks
• [cs.CV]Knowledge Fusion Transformers for Video Action Recognition
• [cs.CV]Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
• [cs.CV]Learning to Stop: A Simple yet Effective Approach to Urban Vision-Language Navigation
• [cs.CV]Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection
• [cs.CV]Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
• [cs.CV]MARA-Net: Single Image Deraining Network with Multi-level connection and Adaptive Regional Attention
• [cs.CV]MS-RANAS: Multi-Scale Resource-Aware Neural Architecture Search
• [cs.CV]MetaMix: Improved Meta-Learning with Interpolation-based Consistency Regularization
• [cs.CV]Micro-Facial Expression Recognition in Video Based on Optimal Convolutional Neural Network (MFEOCNN) Algorithm
• [cs.CV]Micro-Facial Expression Recognition in Video Based on Optimal Convolutional Neural Network (MFEOCNN) Algorithm
• [cs.CV]Multi-View Consistency Loss for Improved Single-Image 3D Reconstruction of Clothed People
• [cs.CV]Multi-term and Multi-task Affect Analysis in the Wild
• [cs.CV]Neural Alignment for Face De-pixelization
• [cs.CV]One-Shot learning based classification for segregation of plastic waste
• [cs.CV]Robust Detection of Objects under Periodic Motion with Gaussian Process Filtering
• [cs.CV]Rotated Binary Neural Network
• [cs.CV]SIR: Similar Image Retrieval for Product Search in E-Commerce
• [cs.CV]Score-level Multi Cue Fusion for Sign Language Recognition
• [cs.CV]SwiftFace: Real-Time Face Detection
• [cs.CV]TinyGAN: Distilling BigGAN for Conditional Image Generation
• [cs.CV]Uncertainty Sets for Image Classifiers using Conformal Prediction
• [cs.CV]VIVO: Surpassing Human Performance in Novel Object Captioning with Visual Vocabulary Pre-Training
• [cs.CV]Video Face Recognition System: RetinaFace-mnet-faster and Secondary Search
• [cs.CV]Weakly-supervised Salient Instance Detection
• [cs.CV]Where is the Model Looking At?—Concentrate and Explain the Network Attention
• [cs.CV]imdpGAN: Generating Private and Specific Data with Generative Adversarial Networks
• [cs.CY]Signs for Ethical AI: A Route Towards Transparency
• [cs.CY]The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integrity
• [cs.CY]Towards Intelligent Risk-based Customer Segmentation in Banking
• [cs.DC]Communication Lower-Bounds for Distributed-Memory Computations for Mass Spectrometry based Omics Data
• [cs.DC]DPCrowd: Privacy-preserving and Communication-efficient Decentralized Statistical Estimation for Real-time Crowd-sourced Data
• [cs.DC]Engineering In-place (Shared-memory) Sorting Algorithms
• [cs.DC]Montage: A General System for Buffered Durably Linearizable Data Structures
• [cs.DS]Simultaneous Greedys: A Swiss Army Knife for Constrained Submodular Maximization
• [cs.GT]Zero Knowledge Games
• [cs.HC]Designing everyday automation with well-being in mind
• [cs.HC]The EMPATHIC Framework for Task Learning from Implicit Human Feedback
• [cs.IR]One Person, One Model, One World: Learning Continual User Representation without Forgetting
• [cs.IT]A PHY Layer Security of a Jamming-Based Underlay Cognitive Hybrid Satellite-Terrestrial Network
• [cs.IT]On the Outage Performance of SWIPT-NOMA-CRS with imperfect SIC and CSI
• [cs.IT]Recursive CSI Quantization of Time-Correlated MIMO Channels by Deep Learning Classification
• [cs.IT]Task-Based Analog-to-Digital Converters
• [cs.IT]Weighted Sum-Rate Maximization for Intelligent Reflecting Surface Assisted Multi-Cell MU-MIMO Communications
• [cs.IT]Wireless Powered Cooperative Relaying Systems with Non-orthogonal Multiple Access
• [cs.LG]A Fast Graph Neural Network-Based Method for Winner Determination in Multi-Unit Combinatorial Auctions
• [cs.LG]A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning
• [cs.LG]Adversarial Attacks Against Deep Learning Systems for ICD-9 Code Assignment
• [cs.LG]Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
• [cs.LG]Anomaly Detection and Sampling Cost Control via Hierarchical GANs
• [cs.LG]Apollo: An Adaptive Parameter-wise Diagonal Quasi-Newton Method for Nonconvex Stochastic Optimization
• [cs.LG]ChemoVerse: Manifold traversal of latent spaces for novel molecule discovery
• [cs.LG]Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress
• [cs.LG]EEG to fMRI Synthesis: Is Deep Learning a candidate?
• [cs.LG]EEMC: Embedding Enhanced Multi-tag Classification
• [cs.LG]Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary
• [cs.LG]Estimation of Switched Markov Polynomial NARX models
• [cs.LG]Fast Design Space Adaptation with Deep Reinforcement Learning for Analog Circuit Sizing
• [cs.LG]Fast Fréchet Inception Distance
• [cs.LG]Framework for Designing Filters of Spectral Graph Convolutional Neural Networks in the Context of Regularization Theory
• [cs.LG]Geometric Disentanglement by Random Convex Polytopes
• [cs.LG]Graph Neural Networks with Heterophily
• [cs.LG]GraphITE: Estimating Individual Effects of Graph-structured Treatments
• [cs.LG]Identification of Probability weighted ARX models with arbitrary domains
• [cs.LG]Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples
• [cs.LG]Learned Fine-Tuner for Incongruous Few-Shot Learning
• [cs.LG]Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy
• [cs.LG]Machine-Learning Approach to Analyze the Status of Forklift Vehicles with Irregular Movement in a Shipyard
• [cs.LG]Message Passing Neural Processes
• [cs.LG]New GCNN-Based Architecture for Semi-Supervised Node Classification
• [cs.LG]Novelty Search in representational space for sample efficient exploration
• [cs.LG]PDLight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Pressure and Dynamic Light Duration
• [cs.LG]Realistic Image Normalization for Multi-Domain Segmentation
• [cs.LG]STRATA: Building Robustness with a Simple Method for Generating Black-box Adversarial Attacks for Models of Code
• [cs.LG]Selective Cascade of Residual ExtraTrees
• [cs.LG]Self-Supervised Few-Shot Learning on Point Clouds
• [cs.LG]Self-grouping Convolutional Neural Networks
• [cs.LG]Tackling unsupervised multi-source domain adaptation with optimism and consistency
• [cs.LG]Think before you act: A simple baseline for compositional generalization
• [cs.LG]Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning
• [cs.LG]Unbalanced Sobolev Descent
• [cs.LG]Weakly Supervised-Based Oversampling for High Imbalance and High Dimensionality Data Classification
• [cs.LG]What if Neural Networks had SVDs?
• [cs.NE]Deep Evolution for Facial Emotion Recognition
• [cs.NE]Semantic-based Distance Approaches in Multi-objective Genetic Programming
• [cs.NI]Mobility Management in Emerging Ultra-Dense Cellular Networks: A Survey, Outlook, and Future Research Directions
• [cs.PF]Performance Modeling of Streaming Kernels and Sparse Matrix-Vector Multiplication on A64FX
• [cs.RO]A Modeled Approach for Online Adversarial Test of Operational Vehicle Safety
• [cs.RO]Enforcing nonholonomic constraints in Aerobat, a roosting flapping wing model
• [cs.RO]Four-Arm Collaboration: Two Dual-Arm Robots Work Together to Maneuver Tethered Tools
• [cs.RO]Learning Skills to Patch Plans Based on Inaccurate Models
• [cs.RO]Loop-box: Multi-Agent Direct SLAM Triggered by Single Loop Closure for Large-Scale Mapping
• [cs.RO]Modeling and Testing Multi-Agent Traffic Rules within Interactive Behavior Planning
• [cs.RO]Reality-assisted evolution of soft robots through large-scale physical experimentation: a review
• [cs.SD]Bespoke Neural Networks for Score-Informed Source Separation
• [cs.SD]Residual acoustic echo suppression based on efficient multi-task convolutional neural network
• [cs.SI]A network approach to expertise retrieval based on path similarity and credit allocation
• [cs.SI]From Twitter to Traffic Predictor: Next-Day Morning Traffic Prediction Using Social Media Data
• [cs.SI]Network Analysis of the 2016 Presidential Campaign Tweets
• [cs.SI]Online platforms of public participation — a deliberative democracy or a delusion?
• [cs.SI]The Emergence of Higher-Order Structure in Scientific and Technological Knowledge Networks
• [eess.AS]Static and Dynamic Measures of Active Music Listening as Indicators of Depression Risk
• [eess.IV]Automatic Segmentation, Localization, and Identification of Vertebrae in 3D CT Images Using Cascaded Convolutional Neural Networks
• [eess.IV]Cranial Implant Design via Virtual Craniectomy with Shape Priors
• [eess.IV]Deep Image Reconstruction using Unregistered Measurements without Groundtruth
• [eess.IV]Deep Learning-Based Automatic Detection of Poorly Positioned Mammograms to Minimize Patient Return Visits for Repeat Imaging: A Real-World Application
• [eess.IV]Fully Automatic Intervertebral Disc Segmentation Using Multimodal 3D U-Net
• [eess.IV]Learning to Compress Videos without Computing Motion
• [eess.IV]Learning to Improve Image Compression without Changing the Standard Decoder
• [eess.IV]MPG-Net: Multi-Prediction Guided Network for Segmentation of Retinal Layers in OCT Images
• [eess.IV]Multi-focus Image Fusion for Visual Sensor Networks
• [eess.SP]A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing
• [eess.SP]Deep Learning-based Phase Reconfiguration for Intelligent Reflecting Surfaces
• [eess.SP]Deep Learning-based Symbolic Indoor Positioning using the Serving eNodeB
• [eess.SP]Distributed ADMM with Synergetic Communication and Computation
• [eess.SP]Integrated Communication and Localization in mmWave Systems
• [eess.SP]Noise Variance Estimation Using Asymptotic Residual in Compressed Sensing
• [eess.SY]Compositionality of Linearly Solvable Optimal Control in Networked Multi-Agent Systems
• [eess.SY]Ergodic Control Strategy for Multi-Agent Environment Exploration
• [math.CO]The star-structure connectivity and star-substructure connectivity of hypercubes and folded hypercubes
• [math.NA]A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder
• [math.OC]Distributed Online Linear Quadratic Control for Linear Time-invariant Systems
• [math.OC]Mathematical derivation for Vora-Value based filter design method: Gradient and Hessian
• [math.OC]Parameter Identification for Multirobot Systems Using Optimization Based Controllers (Extended Version)
• [math.OC]Patterns of Nonlinear Opinion Formation on Networks
• [math.OC]Projection-Free Adaptive Gradients for Large-Scale Optimization
• [math.ST]High-dimensional CLT for Sums of Non-degenerate Random Vectors: $n^{-1/2}$-rate
• [math.ST]Nonparametric independence tests in metric spaces: What is known and what is not
• [math.ST]On Smooth Change-Point Location Estimation for Poisson Processes
• [math.ST]Quantile Regression Neural Networks: A Bayesian Approach
• [physics.chem-ph]Physics-Constrained Predictive Molecular Latent Space Discovery with Graph Scattering Variational Autoencoder
• [physics.soc-ph]An information theoretic network approach to socioeconomic correlations
• [physics.soc-ph]Vaccination strategies against COVID-19 and the diffusion of anti-vaccination views
• [q-bio.PE]Ensemble Forecasting of the Zika Space-TimeSpread with Topological Data Analysis
• [q-fin.ST]Forecasting Short-term load using Econometrics time series model with T-student Distribution
• [stat.AP]A hierarchical spatio-temporal model to analyze relative risk variations of COVID-19: a focus on Spain, Italy and Germany
• [stat.AP]Calibration methods for spatial Data
• [stat.AP]Ensemble Kalman Filter for non-conservative moving mesh solvers with a joint physics and mesh location update
• [stat.AP]Evaluating Ensemble Post-Processing for Wind Power Forecasts
• [stat.AP]Hierarchical correction of $p$-values via a tree running Ornstein-Uhlenbeck process
• [stat.ME]A General Bayesian Model for Heteroskedastic Data with Fully Conjugate Full-Conditional Distributions
• [stat.ME]Dynamic sparsity on dynamic regression models
• [stat.ME]Efficient Study Design with Multiple Measurement Instruments
• [stat.ME]Modeling partitions of individuals
• [stat.ME]On a new test of fit to the beta distribution
• [stat.ML]Lipschitz neural networks are dense in the set of all Lipschitz functions
• [stat.ML]Online Action Learning in High Dimensions: A New Exploration Rule for Contextual $ε_t$-Greedy Heuristics
• [stat.ML]Testing for Normality with Neural Networks
·····································
• [astro-ph.EP]Machine Learning for Semi-Automated Meteorite Recovery
Seamus Anderson, Martin Towner, Phil Bland, Christopher Haikings, William Volante, Eleanor Sansom, Hadrien Devillepoix, Patrick Shober, Benjamin Hartig, Martin Cupak, Trent Jansen-Sturgeon, Robert Howie, Gretchen Benedix, Geoff Deacon
http://arxiv.org/abs/2009.13852v1
• [cs.AI]Analysis of the displacement of terrestrial mobile robots in corridors using paraconsistent annotated evidential logic eτ
Flavio Amadeu Bernardini, Marcia Terra da Silva, Jair Minoro Abe, Luiz Antonio de Lima, Kanstantsin Miatluk
http://arxiv.org/abs/2009.14192v1
• [cs.AI]Cross Learning in Deep Q-Networks
Xing Wang, Alexander Vinel
http://arxiv.org/abs/2009.13780v1
• [cs.AI]Explainable AI without Interpretable Model
Kary Främling
http://arxiv.org/abs/2009.13996v1
• [cs.AI]Joint Spatio-Textual Reasoning for Answering Tourism Questions
Danish Contractor, Shashank Goel, Mausam, Parag Singla
http://arxiv.org/abs/2009.13613v1
• [cs.AI]Large-Scale Cargo Distribution
Luka Stopar, Luka Bradesko, Tobias Jacobs, Azur Kurbašić, Miha Cimperman
http://arxiv.org/abs/2009.14187v1
• [cs.AI]Multi-objective Reinforcement Learning based approach for User-Centric Power Optimization in Smart Home Environments
Saurabh Gupta, Siddhant Bhambri, Karan Dhingra, Arun Balaji Buduru, Ponnurangam Kumaraguru
http://arxiv.org/abs/2009.13854v1
• [cs.AI]Neural Model-based Optimization with Right-Censored Observations
Katharina Eggensperger, Kai Haase, Philipp Müller, Marius Lindauer, Frank Hutter
http://arxiv.org/abs/2009.13828v1
• [cs.AI]Research and Education Towards Smart and Sustainable World
Jukka Riekki, Aarne Mämmelä
http://arxiv.org/abs/2009.13849v1
• [cs.AI]The design and implementation of Language Learning Chatbot with XAI using Ontology and Transfer Learning
Nuobei Shi, Qin Zeng, Raymond Lee
http://arxiv.org/abs/2009.13984v1
• [cs.AI]Towards a Measure of Individual Fairness for Deep Learning
Krystal Maughan, Joseph P. Near
http://arxiv.org/abs/2009.13650v1
• [cs.AI]Understanding Human Intelligence through Human Limitations
Thomas L. Griffiths
http://arxiv.org/abs/2009.14050v1
• [cs.AI]{Playing Carcassonne with Monte Carlo Tree Search
Fred Valdez Ameneyro, Edgar Galvan, Anger Fernando Kuri Morales
http://arxiv.org/abs/2009.12974v1
• [cs.AR]Breaking the Memory Wall for AI Chip with a New Dimension
Eugene Tam, Shenfei Jiang, Paul Duan, Shawn Meng, Yue Pang, Cayden Huang, Yi Han, Jacke Xie, Yuanjun Cui, Jinsong Yu, Minggui Lu
http://arxiv.org/abs/2009.13664v1
• [cs.CL]A Simple and Efficient Ensemble Classifier Combining Multiple Neural Network Models on Social Media Datasets in Vietnamese
Huy Duc Huynh, Hang Thi-Thuy Do, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
http://arxiv.org/abs/2009.13060v2
• [cs.CL]A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation
Dinghan Shen, Mingzhi Zheng, Yelong Shen, Yanru Qu, Weizhu Chen
http://arxiv.org/abs/2009.13818v1
• [cs.CL]A Survey on Semantic Parsing from the perspective of Compositionality
Pawan Kumar, Srikanta Bedathur
http://arxiv.org/abs/2009.14116v1
• [cs.CL]Aligning Intraobserver Agreement by Transitivity
Jacopo Amidei
http://arxiv.org/abs/2009.13905v1
• [cs.CL]Building Legal Case Retrieval Systems with Lexical Matching and Summarization using A Pre-Trained Phrase Scoring Model
Vu Tran, Minh Le Nguyen, Ken Satoh
http://arxiv.org/abs/2009.14083v1
• [cs.CL]Contextual Knowledge Selection and Embedding towards Enhanced Pre-Trained Language Models
YuSheng Su, Xu Han, Zhengyan Zhang, Peng Li, Zhiyuan Liu, Yankai Lin, Jie Zhou, Maosong Sun
http://arxiv.org/abs/2009.13964v1
• [cs.CL]Contrastive Distillation on Intermediate Representations for Language Model Compression
Siqi Sun, Zhe Gan, Yu Cheng, Yuwei Fang, Shuohang Wang, Jingjing Liu
http://arxiv.org/abs/2009.14167v1
• [cs.CL]Conversational Semantic Parsing
Armen Aghajanyan, Jean Maillard, Akshat Shrivastava, Keith Diedrick, Mike Haeger, Haoran Li, Yashar Mehdad, Ves Stoyanov, Anuj Kumar, Mike Lewis, Sonal Gupta
http://arxiv.org/abs/2009.13655v1
• [cs.CL]DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialogue
Shikib Mehri, Mihail Eric, Dilek Hakkani-Tur
http://arxiv.org/abs/2009.13570v1
• [cs.CL]Double Graph Based Reasoning for Document-level Relation Extraction
Shuang Zeng, Runxin Xu, Baobao Chang, Lei Li
http://arxiv.org/abs/2009.13752v1
• [cs.CL]Fake News Spreader Detection on Twitter using Character N-Grams. Notebook for PAN at CLEF 2020
Inna Vogel, Meghana Meghana
http://arxiv.org/abs/2009.13859v1
• [cs.CL]GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
Tao Yu, Chien-Sheng Wu, Xi Victoria Lin, Bailin Wang, Yi Chern Tan, Xinyi Yang, Dragomir Radev, Richard Socher, Caiming Xiong
http://arxiv.org/abs/2009.13845v1
• [cs.CL]HINT3: Raising the bar for Intent Detection in the Wild
Gaurav Arora, Chirag Jain, Manas Chaturvedi, Krupal Modi
http://arxiv.org/abs/2009.13833v1
• [cs.CL]Improve Transformer Models with Better Relative Position Embeddings
Zhiheng Huang, Davis Liang, Peng Xu, Bing Xiang
http://arxiv.org/abs/2009.13658v1
• [cs.CL]Improving Low Compute Language Modeling with In-Domain Embedding Initialisation
Charles Welch, Rada
1000
Mihalcea, Jonathan K. Kummerfeld
http://arxiv.org/abs/2009.14109v1
• [cs.CL]Leader: Prefixing a Length for Faster Word Vector Serialization
Brian Lester
http://arxiv.org/abs/2009.13699v1
• [cs.CL]Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems
Andrea Madotto, Samuel Cahyawijaya, Genta Indra Winata, Yan Xu, Zihan Liu, Zhaojiang Lin, Pascale Fung
http://arxiv.org/abs/2009.13656v1
• [cs.CL]Neural Retrieval for Question Answering with Cross-Attention Supervised Data Augmentation
Yinfei Yang, Ning Jin, Kuo Lin, Mandy Guo, Daniel Cer
http://arxiv.org/abs/2009.13815v1
• [cs.CL]Neural Topic Modeling by Incorporating Document Relationship Graph
Deyu Zhou, Xuemeng Hu, Rui Wang
http://arxiv.org/abs/2009.13972v1
• [cs.CL]Neural Topic Modeling with Cycle-Consistent Adversarial Training
Xuemeng Hu, Rui Wang, Deyu Zhou, Yuxuan Xiong
http://arxiv.org/abs/2009.13971v1
• [cs.CL]Parsing with Multilingual BERT, a Small Corpus, and a Small Treebank
Ethan C. Chau, Lucy H. Lin, Noah A. Smith
http://arxiv.org/abs/2009.14124v1
• [cs.CL]Sequence-to-Sequence Learning for Indonesian Automatic Question Generator
Ferdiant Joshua Muis, Ayu Purwarianti
http://arxiv.org/abs/2009.13889v1
• [cs.CL]SynSetExpan: An Iterative Framework for Joint Entity Set Expansion and Synonym Discovery
Jiaming Shen, Wenda Qiu, Jingbo Shang, Michelle Vanni, Xiang Ren, Jiawei Han
http://arxiv.org/abs/2009.13827v1
• [cs.CL]TernaryBERT: Distillation-aware Ultra-low Bit BERT
Wei Zhang, Lu Hou, Yichun Yin, Lifeng Shang, Xiao Chen, Xin Jiang, Qun Liu
http://arxiv.org/abs/2009.12812v2
• [cs.CL]Transformers Are Better Than Humans at Identifying Generated Text
Antonis Maronikolakis, Mark Stevenson, Hinrich Schutze
http://arxiv.org/abs/2009.13375v2
• [cs.CL]Utility is in the Eye of the User: A Critique of NLP Leaderboards
Kawin Ethayarajh, Dan Jurafsky
http://arxiv.org/abs/2009.13888v1
• [cs.CL]Utterance-level Dialogue Understanding: An Empirical Study
Deepanway Ghosal, Navonil Majumder, Rada Mihalcea, Soujanya Poria
http://arxiv.org/abs/2009.13902v1
• [cs.CL]Visual Pivoting for (Unsupervised) Entity Alignment
Fangyu Liu, Muhao Chen, Dan Roth, Nigel Collier
http://arxiv.org/abs/2009.13603v1
• [cs.CR]A Distributed Computing Perspective of Unconditionally Secure Information Transmission in Russian Cards Problems
Sergio Rajsbaum
http://arxiv.org/abs/2009.13644v1
• [cs.CR]Oblivious Sampling Algorithms for Private Data Analysis
Sajin Sasy, Olga Ohrimenko
http://arxiv.org/abs/2009.13689v1
• [cs.CV]A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification
Hichame Yessou, Gencer Sumbul, Begüm Demir
http://arxiv.org/abs/2009.13935v1
• [cs.CV]A Comprehensive Review for MRF and CRF Approaches in Pathology Image Analysis
Chen Li, Yixin Li, Changhao Sun, Hao Chen, Hong Zhang
http://arxiv.org/abs/2009.13721v1
• [cs.CV]A Flow Base Bi-path Network for Cross-scene Video Crowd Understanding in Aerial View
Zhiyuan Zhao, Tao Han, Junyu Gao, Qi Wang, Xuelong Li
http://arxiv.org/abs/2009.13723v1
• [cs.CV]A Prototype-Based Generalized Zero-Shot Learning Framework for Hand Gesture Recognition
Jinting Wu, Yujia Zhang, Xiaoguang Zhao
http://arxiv.org/abs/2009.13957v1
• [cs.CV]A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection
Kemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan
http://arxiv.org/abs/2009.13592v1
• [cs.CV]A Survey on Deep Learning Techniques for Video Anomaly Detection
Jessie James P. Suarez, Prospero C. Naval Jr
http://arxiv.org/abs/2009.14146v1
• [cs.CV]A comparison of classical and variational autoencoders for anomaly detection
Fabrizio Patuzzo
http://arxiv.org/abs/2009.13793v1
• [cs.CV]Adaptive confidence thresholding for semi-supervised monocular depth estimation
Hyesong Choi, Hunsang Lee, Sunkyung Kim, Sunok Kim, Seungryong Kim, Dongbo Min
http://arxiv.org/abs/2009.12840v1
• [cs.CV]An Image Processing Pipeline for Automated Packaging Structure Recognition
Laura Dörr, Felix Brandt, Martin Pouls, Alexander Naumann
http://arxiv.org/abs/2009.13824v1
• [cs.CV]Asymmetric Loss For Multi-Label Classification
Emanuel Ben-Baruch, Tal Ridnik, Nadav Zamir, Asaf Noy, Itamar Friedman, Matan Protter, Lihi Zelnik-Manor
http://arxiv.org/abs/2009.14119v1
• [cs.CV]Attentional Feature Fusion
Yimian Dai, Fabian Gieseke, Stefan Oehmcke, Yiquan Wu, Kobus Barnard
http://arxiv.org/abs/2009.14082v1
• [cs.CV]BAMSProd: A Step towards Generalizing the Adaptive Optimization Methods to Deep Binary Model
Junjie Liu, Dongchao Wen, Deyu Wang, Wei Tao, Tse-Wei Chen, Kinya Osa, Masami Kato
http://arxiv.org/abs/2009.13799v1
• [cs.CV]Beneficial Perturbation Network for designing general adaptive artificial intelligence systems
Shixian Wen, Amanda Rios, Yunhao Ge, Laurent Itti
http://arxiv.org/abs/2009.13954v1
• [cs.CV]CoKe: Localized Contrastive Learning for Robust Keypoint Detection
Yutong Bai, Angtian Wang, Adam Kortylewski, Alan Yuille
http://arxiv.org/abs/2009.14115v1
• [cs.CV]Cross-Task Representation Learning for Anatomical Landmark Detection
Zeyu Fu, Jianbo Jiao, Michael Suttie, J. Alison Noble
http://arxiv.org/abs/2009.13635v1
• [cs.CV]Deep discriminant analysis for task-dependent compact network search
Qing Tian, Tal Arbel, James J. Clark
http://arxiv.org/abs/2009.13716v1
• [cs.CV]Detecting soccer balls with reduced neural networks: a comparison of multiple architectures under constrained hardware scenarios
Douglas De Rizzo Meneghetti, Thiago Pedro Donadon Homem, Jonas Henrique Renolfi de Oliveira, Isaac Jesus da Silva, Danilo Hernani Perico, Reinaldo Augusto da Costa Bianchi
http://arxiv.org/abs/2009.13684v1
• [cs.CV]Fast Gravitational Approach for Rigid Point Set Registration with Ordinary Differential Equations
Sk Aziz Ali, Kerem Kahraman, Christian Theobalt, Didier Stricker, Vladislav Golyanik
http://arxiv.org/abs/2009.14005v1
• [cs.CV]Fully Automated Left Atrium Segmentation from Anatomical Cine Long-axis MRI Sequences using Deep Convolutional Neural Network with Unscented Kalman Filter
Xiaoran Zhang, Michelle Noga, David Glynn Martin, Kumaradevan Punithakumar
http://arxiv.org/abs/2009.13627v1
• [cs.CV]Geometric Loss for Deep Multiple Sclerosis lesion Segmentation
Hang Zhang, Jinwei Zhang, Rongguang Wang, Qihao Zhang, Susan A. Gauthier, Pascal Spincemaille, Thanh D. Nguyen, Yi Wang
http://arxiv.org/abs/2009.13755v1
• [cs.CV]Graph-based methods for analyzing orchard tree structure using noisy point cloud data
Fredrik Westling, Dr James Underwood, Dr Mitch Bryson
http://arxiv.org/abs/2009.13727v1
• [cs.CV]Improving Interpretability for Computer-aided Diagnosis tools on Whole Slide Imaging with Multiple Instance Learning and Gradient-based Explanations
Antoine Pirovano, Hippolyte Heuberger, Sylvain Berlemont, Saïd Ladjal, Isabelle Bloch
http://arxiv.org/abs/2009.14001v1
• [cs.CV]Kernel Based Progressive Distillation for Adder Neural Networks
Yixing Xu, Chang Xu, Xinghao Chen, Wei Zhang, Chunjing Xu, Yunhe Wang
http://arxiv.org/abs/2009.13044v2
• [cs.CV]Knowledge Fusion Transformers for Video Action Recognition
Ganesh Samarth, Sheetal Ojha, Nikhil Pareek
http://arxiv.org/abs/2009.13782v1
• [cs.CV]Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Jerry Wei, Arief Suriawinata, Bing Ren, Xiaoying Liu, Mikhail Lisovsky, Louis Vaickus, Charles Brown, Michael Baker, Mustafa Nasir-Moin, Naofumi Tomita, Lorenzo Torresani, Jason Wei, Saeed Hassanpour
http://arxiv.org/abs/2009.13698v1
• [cs.CV]Learning to Stop: A Simple yet Effective Approach to Urban Vision-Language Navigation
Jiannan Xiang, Xin Eric Wang, William Yang Wang
http://arxiv.org/abs/2009.13112v2
• [cs.CV]Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection
Heng Zhang, Elisa Fromont, Sébastien Lefevre, Bruno Avignon
http://arxiv.org/abs/2009.14085v1
• [cs.CV]Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
Kaihua Tang, Jianqiang Huang, Hanwang Zhang
http://arxiv.org/abs/2009.12991v2
• [cs.CV]MARA-Net: Single Image Deraining Network with Multi-level connection and Adaptive Regional Attention
Yeachan Park, Myeongho Jeon, Junho Lee, Myungjoo Kan
http://arxiv.org/abs/2009.13990v1
• [cs.CV]MS-RANAS: Multi-Scale Resource-Aware Neural Architecture Search
Cristian Cioflan, Radu Timofte
http://arxiv.org/abs/2009.13940v1
• [cs.CV]MetaMix: Improved Meta-Learning with Interpolation-based Consistency Regularization
Yangbin Chen, Yun Ma, Tom Ko, Jianping Wang, Qing Li
http://arxiv.org/abs/2009.13735v1
• [cs.CV]Micro-Facial Expression Recognition in Video Based on Optimal Convolutional Neural Network (MFEOCNN) Algorithm
S. D. Lalitha, K. K. Thyagharajan
http://arxiv.org/abs/2009.13792v1
• [cs.CV]Micro-Facial Expression Recognition in Video Based on Optimal Convolutional Neural Network (MFEOCNN) Algorithm
S. D. Lalitha, K. K. Thyagharajan
http://arxiv.org/abs/2009.1379
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2v1)
• [cs.CV]Multi-View Consistency Loss for Improved Single-Image 3D Reconstruction of Clothed People
Akin Caliskan, Armin Mustafa, Evren Imre, Adrian Hilton
http://arxiv.org/abs/2009.14162v1
• [cs.CV]Multi-term and Multi-task Affect Analysis in the Wild
Sachihiro Youoku, Junya Saito, Yuushi Toyoda, Takahisa Yamamoto, Junya Saito, Ryosuke Kawamura, Xiaoyu Mi, Kentaro Murase
http://arxiv.org/abs/2009.13885v1
• [cs.CV]Neural Alignment for Face De-pixelization
Maayan Shuvi, Noa Fish, Kfir Aberman, Ariel Shamir, Daniel Cohen-Or
http://arxiv.org/abs/2009.13856v1
• [cs.CV]One-Shot learning based classification for segregation of plastic waste
Shivaank Agarwal, Ravindra Gudi, Paresh Saxena
http://arxiv.org/abs/2009.13953v1
• [cs.CV]Robust Detection of Objects under Periodic Motion with Gaussian Process Filtering
Joris Guerin, Anne Magaly de Paula Canuto, Luiz Marcos Garcia Goncalves
http://arxiv.org/abs/2009.14178v1
• [cs.CV]Rotated Binary Neural Network
Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Yan Wang, Yongjian Wu, Feiyue Huang, Chia-Wen Lin
http://arxiv.org/abs/2009.13055v2
• [cs.CV]SIR: Similar Image Retrieval for Product Search in E-Commerce
Theban Stanley, Nihar Vanjara, Yanxin Pan, Ekaterina Pirogova, Swagata Chakraborty, Abon Chaudhuri
http://arxiv.org/abs/2009.13836v1
• [cs.CV]Score-level Multi Cue Fusion for Sign Language Recognition
Çağrı Gökçe, Oğulcan Özdemir, Ahmet Alp Kındıroğlu, Lale Akarun
http://arxiv.org/abs/2009.14139v1
• [cs.CV]SwiftFace: Real-Time Face Detection
Leonardo Ramos, Bernardo Morales
http://arxiv.org/abs/2009.13743v1
• [cs.CV]TinyGAN: Distilling BigGAN for Conditional Image Generation
Ting-Yun Chang, Chi-Jen Lu
http://arxiv.org/abs/2009.13829v1
• [cs.CV]Uncertainty Sets for Image Classifiers using Conformal Prediction
Anastasios Angelopoulos, Stephen Bates, Jitendra Malik, Michael I. Jordan
http://arxiv.org/abs/2009.14193v1
• [cs.CV]VIVO: Surpassing Human Performance in Novel Object Captioning with Visual Vocabulary Pre-Training
Xiaowei Hu, Xi Yin, Kevin Lin, Lijuan Wang, Lei Zhang, Jianfeng Gao, Zicheng Liu
http://arxiv.org/abs/2009.13682v1
• [cs.CV]Video Face Recognition System: RetinaFace-mnet-faster and Secondary Search
Qian Li, Nan Guo, Xiaochun Ye, Dongrui Fan, Zhimin Tang
http://arxiv.org/abs/2009.13167v2
• [cs.CV]Weakly-supervised Salient Instance Detection
Xin Tian, Ke Xu, Xin Yang, Baocai Yin, Rynson W. H. Lau
http://arxiv.org/abs/2009.13898v1
• [cs.CV]Where is the Model Looking At?—Concentrate and Explain the Network Attention
Wenjia Xu, Jiuniu Wang, Yang Wang, Guangluan Xu, Wei Dai, Yirong Wu
http://arxiv.org/abs/2009.13862v1
• [cs.CV]imdpGAN: Generating Private and Specific Data with Generative Adversarial Networks
Saurabh Gupta, Arun Balaji Buduru, Ponnurangam Kumaraguru
http://arxiv.org/abs/2009.13839v1
• [cs.CY]Signs for Ethical AI: A Route Towards Transparency
Dario Garcia-Gasulla, Atia Cortés, Sergio Alvarez-Napagao, Ulises Cortés
http://arxiv.org/abs/2009.13871v1
• [cs.CY]The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integrity
Mohamed Abdalla, Moustafa Abdalla
http://arxiv.org/abs/2009.13676v1
• [cs.CY]Towards Intelligent Risk-based Customer Segmentation in Banking
Shahabodin Khadivi Zand
http://arxiv.org/abs/2009.13929v1
• [cs.DC]Communication Lower-Bounds for Distributed-Memory Computations for Mass Spectrometry based Omics Data
Fahad Saeed
http://arxiv.org/abs/2009.14123v1
• [cs.DC]DPCrowd: Privacy-preserving and Communication-efficient Decentralized Statistical Estimation for Real-time Crowd-sourced Data
Xuebin Ren, Chia-Mu Yu, Wei Yu, Xinyu Yang, Jun Zhao, Shusen Yang
http://arxiv.org/abs/2009.14125v1
• [cs.DC]Engineering In-place (Shared-memory) Sorting Algorithms
Michael Axtmann, Sascha Witt, Daniel Ferizovic, Peter Sanders
http://arxiv.org/abs/2009.13569v1
• [cs.DC]Montage: A General System for Buffered Durably Linearizable Data Structures
Haosen Wen, Wentao Cai, Mingzhe Du, Louis Jenkins, Benjamin Valpey, Michael L. Scott
http://arxiv.org/abs/2009.13701v1
• [cs.DS]Simultaneous Greedys: A Swiss Army Knife for Constrained Submodular Maximization
Moran Feldman, Christopher Harshaw, Amin Karbasi
http://arxiv.org/abs/2009.13998v1
• [cs.GT]Zero Knowledge Games
Ian Malloy
http://arxiv.org/abs/2009.13521v1
• [cs.HC]Designing everyday automation with well-being in mind
Holger Klapperich, Alarith Uhde, Marc Hassenzahl
http://arxiv.org/abs/2009.13919v1
• [cs.HC]The EMPATHIC Framework for Task Learning from Implicit Human Feedback
Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox
http://arxiv.org/abs/2009.13649v1
• [cs.IR]One Person, One Model, One World: Learning Continual User Representation without Forgetting
Fajie Yuan, Guoxiao Zhang, Alexandros Karatzoglou, Xiangnan He, Joemon Jose, Beibei Kong, Yudong Li
http://arxiv.org/abs/2009.13724v1
• [cs.IT]A PHY Layer Security of a Jamming-Based Underlay Cognitive Hybrid Satellite-Terrestrial Network
Mounia Bouabdellah, Faissal El Bouanani
http://arxiv.org/abs/2009.13993v1
• [cs.IT]On the Outage Performance of SWIPT-NOMA-CRS with imperfect SIC and CSI
Ferdi Kara
http://arxiv.org/abs/2009.13979v1
• [cs.IT]Recursive CSI Quantization of Time-Correlated MIMO Channels by Deep Learning Classification
Stefan Schwarz
http://arxiv.org/abs/2009.13560v1
• [cs.IT]Task-Based Analog-to-Digital Converters
Peter Neuhaus, Nir Shlezinger, Meik Dörpinghaus, Yonina C. Eldar, Gerhard Fettweis
http://arxiv.org/abs/2009.14088v1
• [cs.IT]Weighted Sum-Rate Maximization for Intelligent Reflecting Surface Assisted Multi-Cell MU-MIMO Communications
Chen He, Xie Xie, Xiaoya Li, Kun Yang, Z. Jane Wang
http://arxiv.org/abs/2009.13899v1
• [cs.IT]Wireless Powered Cooperative Relaying Systems with Non-orthogonal Multiple Access
Ferdi Kara
http://arxiv.org/abs/2009.13973v1
• [cs.LG]A Fast Graph Neural Network-Based Method for Winner Determination in Multi-Unit Combinatorial Auctions
Mengyuan Lee, Seyyedali Hosseinalipour, Christopher G. Brinton, Guanding Yu, Huaiyu Dai
http://arxiv.org/abs/2009.13697v1
• [cs.LG]A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
http://arxiv.org/abs/2009.13982v1
• [cs.LG]Adversarial Attacks Against Deep Learning Systems for ICD-9 Code Assignment
Sharan Raja, Rudraksh Tuwani
http://arxiv.org/abs/2009.13720v1
• [cs.LG]Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
Vihang P. Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter
http://arxiv.org/abs/2009.14108v1
• [cs.LG]Anomaly Detection and Sampling Cost Control via Hierarchical GANs
Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
http://arxiv.org/abs/2009.13598v1
• [cs.LG]Apollo: An Adaptive Parameter-wise Diagonal Quasi-Newton Method for Nonconvex Stochastic Optimization
Xuezhe Ma
http://arxiv.org/abs/2009.13586v1
• [cs.LG]ChemoVerse: Manifold traversal of latent spaces for novel molecule discovery
Harshdeep Singh, Nicholas McCarthy, Qurrat Ul Ain, Jeremiah Hayes
http://arxiv.org/abs/2009.13946v1
• [cs.LG]Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress
Renjie Wu, Eamonn J. Keogh
http://arxiv.org/abs/2009.13807v1
• [cs.LG]EEG to fMRI Synthesis: Is Deep Learning a candidate?
David Calhas, Rui Henriques
http://arxiv.org/abs/2009.14133v1
• [cs.LG]EEMC: Embedding Enhanced Multi-tag Classification
Yanlin Li, Shi An, Ruisheng Zhang
http://arxiv.org/abs/2009.13826v1
• [cs.LG]Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary
Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm
http://arxiv.org/abs/2009.13853v1
• [cs.LG]Estimation of Switched Markov Polynomial NARX models
Alessandro Brusaferri, Matteo Matteucci, Stefano Spinelli
http://arxiv.org/abs/2009.14073v1
• [cs.LG]Fast Design Space Adaptation with Deep Reinforcement Learning for Analog Circuit Sizing
Kevin-CY Tsai, Kai-En Yang, Hung-Hao Shen, Mike Jiang, Fammy Tsai, CA Wang, Yiju Ting, Jason Yeh, Citi Lai
http://arxiv.org/abs/2009.13772v1
• [cs.LG]Fast Fréchet Inception Distance
Alexander Mathiasen, Frederik Hvilshøj
http://arxiv.org/abs/2009.14075v1
• [cs.LG]Framework for Designing Filters of Spectral Graph Convolutional Neural Networks in the Context of Regularization Theory
Asif Salim, Sumitra S
http://arxiv.org/abs/2009.13801v1
• [cs.LG]Geometric Disentanglement by Random Convex Polytopes
Michael Joswig, Marek Kaluba, Lukas Ruff
http://arxiv.org/abs/2009.13987v1
• [cs.LG]Graph Neural Networks with Heterophily
Jiong Zhu, Ryan A. Rossi, Anup Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra
http://arxiv.org/abs/2009.13566v1
• [cs.LG]GraphITE: Estimating Individual Effects of Graph-structured Treatments
Shonosuke Harada, Hisashi Kashima
http://arxiv.org/abs/2009.14061v1
• [cs.LG]Identification of Probability weighted ARX models with arbitrary domains
Alessandro Brusaferri, Matteo Matteucci, Stefano Spinelli
http://arxiv.org/abs/2009.13975v1
• [cs.LG]Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples
Jaehoon Koo, Diego Klabjan, Jean Utke
http://arxiv.org/abs/2009.14111v1
• [cs.LG]Learned Fine-Tuner for Incongruous Few-Shot Learning
Pu Zhao, Sijia Liu, Parikshit Ram, Songtao Lu, Djallel Bouneffouf, Xue Lin
http://arxiv.org/abs/2009.13714v1
• [cs.LG]Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy
Yunshu Du, Garrett Warnell, Assefaw Gebremedhin, Peter Stone, Matthew E. Taylor
http://arxiv.org/abs/2009.13736v1
• [cs.LG]Machine-Learning Approach to Analyze the Status of Forklift Vehicles with Irregular Movement in a Shipyard
Hyeonju Lee, Jongho Lee, Minji An, Gunil Park, Sungchul Choi
http://arxiv.org/abs/2009.14025v1
• [cs.LG]Message Passing Neural Processes
Ben Day, Cătălina Cangea, Arian R. Jamasb, Pietro Liò
http://arxiv.org/abs/2009.13895v1
• [cs.LG]New GCNN-Based Architecture for Semi-Supervised Node Classification
Mohammad Esmaeili, Aria Nosratinia
http://arxiv.org/abs/2009.13734v1
• [cs.LG]Novelty Search in representational space for sample efficient exploration
Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau
http://arxiv.org/abs/2009.13579v1
• [cs.LG]PDLight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Pressure and Dynamic Light Duration
Chenguang Zhao, Xiaorong Hu, Gang Wang
http://arxiv.org/abs/2009.13711v1
• [cs.LG]Realistic Image Normalization for Multi-Domain Segmentation
Pierre-Luc Delisle, Benoit Anctil-Robitaille, Christian Desrosiers, Herve Lombaert
http://arxiv.org/abs/2009.14024v1
• [cs.LG]STRATA: Building Robustness with a Simple Method for Generating Black-box Adversarial Attacks for Models of Code
Jacob M. Springer, Bryn Marie Reinstadler, Una-May O’Reilly
http://arxiv.org/abs/2009.13562v1
• [cs.LG]Selective Cascade of Residual ExtraTrees
Qimin Liu, Fang Liu
http://arxiv.org/abs/2009.14138v1
• [cs.LG]Self-Supervised Few-Shot Learning on Point Clouds
Charu Sharma, Manohar Kaul
http://arxiv.org/abs/2009.14168v1
• [cs.LG]Self-grouping Convolutional Neural Networks
Qingbei Guo, Xiao-Jun Wu, Josef Kittler, Zhiquan Feng
http://arxiv.org/abs/2009.13803v1
• [cs.LG]Tackling unsupervised multi-source domain adaptation with optimism and consistency
Diogo Pernes, Jaime S. Cardoso
http://arxiv.org/abs/2009.13939v1
• [cs.LG]Think before you act: A simple baseline for compositional generalization
Christina Heinze-Deml, Diane Bouchacourt
http://arxiv.org/abs/2009.13962v1
• [cs.LG]Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning
Haotian Fu, Hongyao Tang, Jianye Hao, Chen Chen, Xidong Feng, Dong Li, Wulong Liu
http://arxiv.org/abs/2009.13891v1
• [cs.LG]Unbalanced Sobolev Descent
Youssef Mroueh, Mattia Rigotti
http://arxiv.org/abs/2009.14148v1
• [cs.LG]Weakly Supervised-Based Oversampling for High Imbalance and High Dimensionality Data Classification
Min Qian, Yan-Fu Li
http://arxiv.org/abs/2009.14096v1
• [cs.LG]What if Neural Networks had SVDs?
Alexander Mathiasen, Frederik Hvilshøj, Jakob Rødsgaard Jørgensen, Anshul Nasery, Davide Mottin
http://arxiv.org/abs/2009.13977v1
• [cs.NE]Deep Evolution for Facial Emotion Recognition
Emmanuel Dufourq, Bruce A. Bassett
http://arxiv.org/abs/2009.14194v1
• [cs.NE]Semantic-based Distance Approaches in Multi-objective Genetic Programming
Edgar Galván, Fergal Stapleton
http://arxiv.org/abs/2009.12401v2
• [cs.NI]Mobility Management in Emerging Ultra-Dense Cellular Networks: A Survey, Outlook, and Future Research Directions
Syed Muhammad Asad Zaidi, Marvin Manalastas, Hasan Farooq, Ali Imran
http://arxiv.org/abs/2009.13922v1
• [cs.PF]Performance Modeling of Streaming Kernels and Sparse Matrix-Vector Multiplication on A64FX
Christie L. Alappat, Jan Laukemann, Thomas Gruber, Georg Hager, Gerhard Wellein, Nils Meyer, Tilo Wettig
http://arxiv.org/abs/2009.13903v1
• [cs.RO]A Modeled Approach for Online Adversarial Test of Operational Vehicle Safety
Linda Capito, Bowen Weng, Umit Ozguner, Keith Redmill
http://arxiv.org/abs/2009.12222v2
• [cs.RO]Enforcing nonholonomic constraints in Aerobat, a roosting flapping wing model
Eric Sihite, Alireza Ramezani
http://arxiv.org/abs/2009.14156v1
• [cs.RO]Four-Arm Collaboration: Two Dual-Arm Robots Work Together to Maneuver Tethered Tools
Daniel Sanchez, Weiwei Wan, Keisuke Koyama, Kensuke Harada
http://arxiv.org/abs/2009.14089v1
• [cs.RO]Learning Skills to Patch Plans Based on Inaccurate Models
Alex LaGrassa, Steven Lee, Oliver Kroemer
http://arxiv.org/abs/2009.13732v1
• [cs.RO]Loop-box: Multi-Agent Direct SLAM Triggered by Single Loop Closure for Large-Scale Mapping
M Usman Maqbool Bhutta, Manohar Kuse, Rui Fan, Yanan Liu, Ming Liu
http://arxiv.org/abs/2009.13851v1
• [cs.RO]Modeling and Testing Multi-Agent Traffic Rules within Interactive Behavior Planning
Klemens Esterle, Luis Gressenbuch, Alois Knoll
http://arxiv.org/abs/2009.14186v1
• [cs.RO]Reality-assisted evolution of soft robots through large-scale physical experimentation: a review
Toby Howison, Simon Hauser, Josie Hughes, Fumuiya Iida
http://arxiv.org/abs/2009.13960v1
• [cs.SD]Bespoke Neural Networks for Score-Informed Source Separation
Ethan Manilow, Bryan Pardo
http://arxiv.org/abs/2009.13729v1
• [cs.SD]Residual acoustic echo suppression based on efficient multi-task convolutional neural network
Xinquan Zhou, Yanhong Leng
http://arxiv.org/abs/2009.13931v1
• [cs.SI]A network approach to expertise retrieval based on path similarity and credit allocation
Xiancheng Li, Luca Verginer, Massimo Riccaboni, Pietro Panzarasa
http://arxiv.org/abs/2009.13958v1
• [cs.SI]From Twitter to Traffic Predictor: Next-Day Morning Traffic Prediction Using Social Media Data
Weiran Yao, Sean Qian
http://arxiv.org/abs/2009.13794v1
• [cs.SI]Network Analysis of the 2016 Presidential Campaign Tweets
Dmitry Zinoviev
http://arxiv.org/abs/2009.13659v1
• [cs.SI]Online platforms of public participation — a deliberative democracy or a delusion?
Jonathan Davies, Rob Procter
http://arxiv.org/abs/2009.14074v1
• [cs.SI]The Emergence of Higher-Order Structure in Scientific and Technological Knowledge Networks
Thomas Gebhart, Russell J. Funk
http://arxiv.org/abs/2009.13620v1
• [eess.AS]Static and Dynamic Measures of Active Music Listening as Indicators of Depression Risk
Aayush Surana, Yash Goyal, Vinoo Alluri
http://arxiv.org/abs/2009.13685v1
• [eess.IV]Automatic Segmentation, Localization, and Identification of Vertebrae in 3D CT Images Using Cascaded Convolutional Neural Networks
Naoto Masuzawa, Yoshiro Kitamura, Keigo Nakamura, Satoshi Iizuka, Edgar Simo-Serra
http://arxiv.org/abs/2009.13798v1
• [eess.IV]Cranial Implant Design via Virtual Craniectomy with Shape Priors
Franco Matzkin, Virginia Newcombe, Ben Glocker, Enzo Ferrante
http://arxiv.org/abs/2009.13704v1
• [eess.IV]Deep Image Reconstruction using Unregistered Measurements without Groundtruth
Weijie Gan, Yu Sun, Cihat Eldeniz, Jiaming Liu, Hongyu An, Ulugbek S. Kamilov
http://arxiv.org/abs/2009.13986v1
• [eess.IV]Deep Learning-Based Automatic Detection of Poorly Positioned Mammograms to Minimize Patient Return Visits for Repeat Imaging: A Real-World Application
Vikash Gupta, Clayton Taylor, Sarah Bonnet, Luciano M. Prevedello, Jeffrey Hawley, Richard D White, Mona G Flores, Barbaros Selnur Erdal
http://arxiv.org/abs/2009.13580v1
• [eess.IV]Fully Automatic Intervertebral Disc Segmentation Using Multimodal 3D U-Net
Chuanbo Wang, Ye Guo, Wei Chen, Zeyun Yu
http://arxiv.org/abs/2009.13583v1
• [eess.IV]Learning to Compress Videos without Computing Motion
Meixu Chen, Todd Goodall, Anjul Patney, Alan C. Bovik
http://arxiv.org/abs/2009.14110v1
• [eess.IV]Learning to Improve Image Compression without Changing the Standard Decoder
Yannick Strümpler, Ren Yang, Radu Timofte
http://arxiv.org/abs/2009.12927v2
• [eess.IV]MPG-Net: Multi-Prediction Guided Network for Segmentation of Retinal Layers in OCT Images
Zeyu Fu, Yang Sun, Xiangyu Zhang, Scott Stainton, Shaun Barney, Jeffry Hogg, William Innes, Satnam Dlay
http://arxiv.org/abs/2009.13634v1
• [eess.IV]Multi-focus Image Fusion for Visual Sensor Networks
Milad Abdollahzadeh, Touba Malekzadeh, Hadi Seyedarabi
http://arxiv.org/abs/2009.13615v1
• [eess.SP]A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing
Ping Lang, Xiongjun Fu, Marco Martorella, Jian Dong, Rui Qin, Xianpeng Meng, Min Xie
http://arxiv.org/abs/2009.13702v1
• [eess.SP]Deep Learning-based Phase Reconfiguration for Intelligent Reflecting Surfaces
Özgecan Özdogan, Emil Björnson
http://arxiv.org/abs/2009.13988v1
• [eess.SP]Deep Learning-based Symbolic Indoor Positioning using the Serving eNodeB
Fahad Alhomayani, Mohammad Mahoor
http://arxiv.org/abs/2009.13675v1
• [eess.SP]Distributed ADMM with Synergetic Communication and Computation
Zhuojun Tian, Zhaoyang Zhang, Jue Wang, Xiaoming Chen, Wei Wang, Huaiyu Dai
http://arxiv.org/abs/2009.13863v1
• [eess.SP]Integrated Communication and Localization in mmWave Systems
Jie Yang, Jing Xu, Xiao Li, Shi Jin, Bo Gao
http://arxiv.org/abs/2009.13135v2
• [eess.SP]Noise Variance Estimation Using Asymptotic Residual in Compressed Sensing
Ryo Hayakawa
http://arxiv.org/abs/2009.13678v1
• [eess.SY]Compositionality of Linearly Solvable Optimal Control in Networked Multi-Agent Systems
Lin Song, Neng Wan, Aditya Gahlawat, Naira Hovakimyan, Evangelos A. Theodorou
http://arxiv.org/abs/2009.13609v1
• [eess.SY]Ergodic Control Strategy for Multi-Agent Environment Exploration
Rabiul Hasan Kabir, Kooktae Lee, Geronimo Macias
http://arxiv.org/abs/2009.13744v1
• [math.CO]The star-structure connectivity and star-substructure connectivity of hypercubes and folded hypercubes
Lina Ba, Heping Zhang
http://arxiv.org/abs/2009.13751v1
• [math.NA]A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder
Youngkyu Kim, Youngsoo Choi, David Widemann, Tarek Zohdi
http://arxiv.org/abs/2009.11990v2
• [math.OC]Distributed Online Linear Quadratic Control for Linear Time-invariant Systems
Ting-Jui Chang, Shahin Shahrampour
http://arxiv.org/abs/2009.13749v1
• [math.OC]Mathematical derivation for Vora-Value based filter design method: Gradient and Hessian
Yuteng Zhu, Graham D. Finlayson
http://arxiv.org/abs/2009.13696v1
• [math.OC]Parameter Identification for Multirobot Systems Using Optimization Based Controllers (Extended Version)
Jaskaran Singh Grover, Changliu Liu, Katia Sycara
http://arxiv.org/abs/2009.13817v1
• [math.OC]Patterns of Nonlinear Opinion Formation on Networks
Anastasia Bizyaeva, Ayanna Matthews, Alessio Franci, Naomi Ehrich Leonard
http://arxiv.org/abs/2009.13600v1
• [math.OC]Projection-Free Adaptive Gradients for Large-Scale Optimization
Cyrille W. Combettes, Christoph Spiegel, Sebastian Pokutta
http://arxiv.org/abs/2009.14114v1
• [math.ST]High-dimensional CLT for Sums of Non-degenerate Random Vectors: $n^{-1/2}$-rate
Arun Kumar Kuchibhotla, Alessandro Rinaldo
http://arxiv.org/abs/2009.13673v1
• [math.ST]Nonparametric independence tests in metric spaces: What is known and what is not
Fernando Castro-Prado, Wenceslao González-Manteiga
http://arxiv.org/abs/2009.14150v1
• [math.ST]On Smooth Change-Point Location Estimation for Poisson Processes
A. Amiri, S Dachian
http://arxiv.org/abs/2009.13968v1
• [math.ST]Quantile Regression Neural Networks: A Bayesian Approach
Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti
http://arxiv.org/abs/2009.13591v1
• [physics.chem-ph]Physics-Constrained Predictive Molecular Latent Space Discovery with Graph Scattering Variational Autoencoder
Navid Shervani-Tabar, Nicholas Zabaras
http://arxiv.org/abs/2009.13878v1
• [physics.soc-ph]An information theoretic network approach to socioeconomic correlations
Alec Kirkley
http://arxiv.org/abs/2009.13825v1
• [physics.soc-ph]Vaccination strategies against COVID-19 and the diffusion of anti-vaccination views
Rafael Prieto Curiel, Humberto González Ramírez
http://arxiv.org/abs/2009.13674v1
• [q-bio.PE]Ensemble Forecasting of the Zika Space-TimeSpread with Topological Data Analysis
Marwah Soliman, Vyacheslav Lyubchich, Yulia R. Gel
http://arxiv.org/abs/2009.13423v1
• [q-fin.ST]Forecasting Short-term load using Econometrics time series model with T-student Distribution
Kasun Chandrarathna, Arman Edalati, AhmadReza Fourozan tabar
http://arxiv.org/abs/2009.13595v1
• [stat.AP]A hierarchical spatio-temporal model to analyze relative risk variations of COVID-19: a focus on Spain, Italy and Germany
Abdollah Jalilian, Jorge Mateu
http://arxiv.org/abs/2009.13577v1
• [stat.AP]Calibration methods for spatial Data
M A Amaral Turkman, K F Turkman, P de Zea Bermudez, S Pereira, P Pereira, M Carvalho
http://arxiv.org/abs/2009.13629v1
• [stat.AP]Ensemble Kalman Filter for non-conservative moving mesh solvers with a joint physics and mesh location update
Christian Sampson, Alberto Carrassi, Ali Aydoğdu, Chris K. R. T Jones
http://arxiv.org/abs/2009.13670v1
• [stat.AP]Evaluating Ensemble Post-Processing for Wind Power Forecasts
Kaleb Phipps, Sebastian Lerch, Maria Andersson, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig
http://arxiv.org/abs/2009.14127v1
• [stat.AP]Hierarchical correction of $p$-values via a tree running Ornstein-Uhlenbeck process
Bichat Antoine, Ambroise Christophe, Mariadassou Mahendra
http://arxiv.org/abs/2009.13335v2
• [stat.ME]A General Bayesian Model for Heteroskedastic Data with Fully Conjugate Full-Conditional Distributions
Paul A. Parker, Scott H. Holan, Skye A. Wills
http://arxiv.org/abs/2009.13636v1
• [stat.ME]Dynamic sparsity on dynamic regression models
Paloma W. Uribe, Hedibert F. Lopes
http://arxiv.org/abs/2009.14131v1
• [stat.ME]Efficient Study Design with Multiple Measurement Instruments
Michal Bitan, Malka Gorfine, Laura Rosen, David M. Steinberg
http://arxiv.org/abs/2009.13921v1
• [stat.ME]Modeling partitions of individuals
Marion Hoffman, Per Block, Tom A. B. Snijders
http://arxiv.org/abs/2009.13974v1
• [stat.ME]On a new test of fit to the beta distribution
Bruno Ebner, Shawn C. Liebenberg
http://arxiv.org/abs/2009.13995v1
• [stat.ML]Lipschitz neural networks are dense in the set of all Lipschitz functions
Stephan Eckstein
http://arxiv.org/abs/2009.13881v1
• [stat.ML]Online Action Learning in High Dimensions: A New Exploration Rule for Contextual $ε_t$-Greedy Heuristics
Claudio C. Flores, Marcelo C. Medeiros
http://arxiv.org/abs/2009.13961v1
• [stat.ML]Testing for Normality with Neural Networks
Milos Simic
http://arxiv.org/abs/2009.13831v1
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