astro-ph.CO - 宇宙学和天体物理学
    astro-ph.EP - 地球与行星天体
    astro-ph.HE - 高能天体物理现象
    cond-mat.mtrl-sci - 材料科学
    cs.AI - 人工智能
    cs.AR - 硬件体系结构
    cs.CE - 计算工程、 金融和科学
    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.DL - 数字图书馆
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.MA - 多代理系统
    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
    cs.SI - 社交网络与信息网络
    econ.TH - 理论经济学
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    eess.SY - 系统和控制
    math.AT - 代数拓扑
    math.NA - 数值分析
    math.OA - 算子代数
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.flu-dyn - 流体动力学
    physics.soc-ph - 物理学与社会
    q-fin.CP -计算金融学
    q-fin.ST - 统计金融学
    q-fin.TR - 贸易与市场微观结构
    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

    • [astro-ph.CO]Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning
    • [astro-ph.EP]DPNNet-2.0 Part I: Finding hidden planets from simulated images of protoplanetary disk gaps
    • [astro-ph.HE]Dim but not entirely dark: Extracting the Galactic Center Excess’ source-count distribution with neural nets
    • [cond-mat.mtrl-sci]Establishing process-structure linkages using Generative Adversarial Networks
    • [cs.AI]Learning Altruistic Behaviours in Reinforcement Learning without External Rewards
    • [cs.AI]MIMO: Mutual Integration of Patient Journey and Medical Ontology for Healthcare Representation Learning
    • [cs.AI]Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
    • [cs.AI]Semantic Reasoning with Differentiable Graph Transformations
    • [cs.AI]ThingFO v1.2’s Terms, Properties, Relationships and Axioms — Foundational Ontology for Things
    • [cs.AR]CREW: Computation Reuse and Efficient Weight Storage for Hardware-accelerated MLPs and RNNs
    • [cs.AR]Positive/Negative Approximate Multipliers for DNN Accelerators
    • [cs.AR]StreamBlocks: A compiler for heterogeneous dataflow computing (technical report)
    • [cs.CE]Similarity metrics for Different Market Scenarios in Abides
    • [cs.CL]BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledge
    • [cs.CL]Cross-Lingual BERT Contextual Embedding Space Mapping with Isotropic and Isometric Conditions
    • [cs.CL]Different kinds of cognitive plausibility: why are transformers better than RNNs at predicting N400 amplitude?
    • [cs.CL]Improving Sentence-Level Relation Extraction through Curriculum Learning
    • [cs.CL]Learning ULMFiT and Self-Distillation with Calibration for Medical Dialogue System
    • [cs.CL]More Parameters? No Thanks!
    • [cs.CL]Neural Abstructions: Abstractions that Support Construction for Grounded Language Learning
    • [cs.CL]Paraphrasing via Ranking Many Candidates
    • [cs.CL]Seed Words Based Data Selection for Language Model Adaptation
    • [cs.CL]Sequence Model with Self-Adaptive Sliding Window for Efficient Spoken Document Segmentation
    • [cs.CL]Simultaneous Speech Translation for Live Subtitling: from Delay to Display
    • [cs.CL]Token-Level Supervised Contrastive Learning for Punctuation Restoration
    • [cs.CL]WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset
    • [cs.CR]GNN4IP: Graph Neural Network for Hardware Intellectual Property Piracy Detection
    • [cs.CR]Image-Hashing-Based Anomaly Detection for Privacy-Preserving Online Proctoring
    • [cs.CV]A Comparison of Supervised and Unsupervised Deep Learning Methods for Anomaly Detection in Images
    • [cs.CV]Accelerating deep neural networks for efficient scene understanding in automotive cyber-physical systems
    • [cs.CV]Active 3D Shape Reconstruction from Vision and Touch
    • [cs.CV]Attention-Guided NIR Image Colorization via Adaptive Fusion of Semantic and Texture Clues
    • [cs.CV]Audio2Head: Audio-driven One-shot Talking-head Generation with Natural Head Motion
    • [cs.CV]Boosting few-shot classification with view-learnable contrastive learning
    • [cs.CV]Built-in Elastic Transformations for Improved Robustness
    • [cs.CV]Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
    • [cs.CV]Compound Figure Separation of Biomedical Images with Side Loss
    • [cs.CV]Critic Guided Segmentation of Rewarding Objects in First-Person Views
    • [cs.CV]DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation
    • [cs.CV]Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography
    • [cs.CV]DeepSocNav: Social Navigation by Imitating Human Behaviors
    • [cs.CV]Discriminator-Free Generative Adversarial Attack
    • [cs.CV]Examining the Human Perceptibility of Black-Box Adversarial Attacks on Face Recognition
    • [cs.CV]Face.evoLVe: A High-Performance Face Recognition Library
    • [cs.CV]Image Fusion Transformer
    • [cs.CV]InsPose: Instance-Aware Networks for Single-Stage Multi-Person Pose Estimation
    • [cs.CV]Learning a Sensor-invariant Embedding of Satellite Data: A Case Study for Lake Ice Monitoring
    • [cs.CV]Locality-aware Channel-wise Dropout for Occluded Face Recognition
    • [cs.CV]Monocular Visual Analysis for Electronic Line Calling of Tennis Games
    • [cs.CV]Multi-Modal Temporal Convolutional Network for Anticipating Actions in Egocentric Videos
    • [cs.CV]QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries
    • [cs.CV]RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank
    • [cs.CV]ReSSL: Relational Self-Supervised Learning with Weak Augmentation
    • [cs.CV]S2Looking: A Satellite Side-Looking Dataset for Building Change Detection
    • [cs.CV]Saliency for free: Saliency prediction as a side-effect of object recognition
    • [cs.CV]Self-Supervised Domain Adaptation for Diabetic Retinopathy Grading using Vessel Image Reconstruction
    • [cs.CV]Separating Skills and Concepts for Novel Visual Question Answering
    • [cs.CV]SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models
    • [cs.CV]Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision
    • [cs.CV]Towards Privacy-preserving Explanations in Medical Image Analysis
    • [cs.CV]Understanding Gender and Racial Disparities in Image Recognition Models
    • [cs.CV]Video Crowd Localization with Multi-focus Gaussian Neighbor Attention and a Large-Scale Benchmark
    • [cs.CY]Diversity in Sociotechnical Machine Learning Systems
    • [cs.CY]From Teaching to Coaching: A Case Study of a Technical Communication Course
    • [cs.CY]IT ambidexterity driven patient agility and hospital patient service performance: a variance approach
    • [cs.CY]Multi-Layered Diagnostics for Smart Cities
    • [cs.CY]The role of IT ambidexterity, digital dynamic capability and knowledge processes as enablers of patient agility: an empirical study
    • [cs.CY]Toward Trustworthy Urban IT Systems: The Bright and Dark Sides of Smart City Development
    • [cs.DC]A New Design Framework for Heterogeneous Uncoded Storage Elastic Computing
    • [cs.DC]Online Deployment Algorithms for Microservice Systems with Complex Dependencies
    • [cs.DL]Temporal search in the scientific space predicts breakthrough inventions
    • [cs.HC]Readability Research: An Interdisciplinary Approach
    • [cs.IR]Learned Sorted Table Search and Static Indexes in Small Space: Methodological and Practical Insights via an Experimental Study
    • [cs.IT]A DNN-based OTFS Transceiver with Delay-Doppler Channel Training and IQI Compensation
    • [cs.IT]Exploring the Non-Overlapping Visibility Regions in XL-MIMO Random Access Protocol
    • [cs.IT]How Does Cell-Free Massive MIMO Support Multiple Federated Learning Groups?
    • [cs.IT]Maximizing the Set Cardinality of Users Scheduled for Ultra-dense uRLLC Networks
    • [cs.IT]Relay-Assisted Cooperative Federated Learning
    • [cs.IT]Rethinking the Tradeoff in Integrated Sensing and Communication: Recognition Accuracy versus Communication Rate
    • [cs.IT]Support Recovery in Universal One-bit Compressed Sensing
    • [cs.IT]User Association in Dense mmWave Networks as Restless Bandits
    • [cs.LG]A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks
    • [cs.LG]Adaptive Transfer Learning on Graph Neural Networks
    • [cs.LG]Algorithm Selection on a Meta Level
    • [cs.LG]An Embedding of ReLU Networks and an Analysis of their Identifiability
    • [cs.LG]An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients
    • [cs.LG]Approximation Theory of Convolutional Architectures for Time Series Modelling
    • [cs.LG]Best-of-All-Worlds Bounds for Online Learning with Feedback Graphs
    • [cs.LG]ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE
    • [cs.LG]CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression
    • [cs.LG]Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning
    • [cs.LG]Constrained Policy Gradient Method for Safe and Fast Reinforcement Learning: a Neural Tangent Kernel Based Approach
    • [cs.LG]Edge of chaos as a guiding principle for modern neural network training
    • [cs.LG]Evaluating Probabilistic Inference in Deep Learning: Beyond Marginal Predictions
    • [cs.LG]Feature-Filter: Detecting Adversarial Examples through Filtering off Recessive Features
    • [cs.LG]FoleyGAN: Visually Guided Generative Adversarial Network-Based Synchronous Sound Generation in Silent Videos
    • [cs.LG]Follow Your Path: a Progressive Method for Knowledge Distillation
    • [cs.LG]Generative Video Transformer: Can Objects be the Words?
    • [cs.LG]Heterogeneous network-based drug repurposing for COVID-19
    • [cs.LG]Improving exploration in policy gradient search: Application to symbolic optimization
    • [cs.LG]Kernel Selection for Stein Variational Gradient Descent
    • [cs.LG]LENS: Layer Distribution Enabled Neural Architecture Search in Edge-Cloud Hierarchies
    • [cs.LG]Large-scale graph representation learning with very deep GNNs and self-supervision
    • [cs.LG]Latency-Memory Optimized Splitting of Convolution Neural Networks for Resource Constrained Edge Devices
    • [cs.LG]Learn2Hop: Learned Optimization on Rough Landscapes
    • [cs.LG]M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis
    • [cs.LG]Mining Topological Dependencies of Recurrent Congestion in Road Networks
    • [cs.LG]OnlineSTL: Scaling Time Series Decomposition by 100x
    • [cs.LG]Open Problem: Is There an Online Learning Algorithm That Learns Whenever Online Learning Is Possible?
    • [cs.LG]Parametric Scattering Networks
    • [cs.LG]Path Integrals for the Attribution of Model Uncertainties
    • [cs.LG]Precision-Weighted Federated Learning
    • [cs.LG]Predicting Driver Takeover Time in Conditionally Automated Driving
    • [cs.LG]Predicting Friction System Performance with Symbolic Regression and Genetic Programming with Factor Variables
    • [cs.LG]Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI
    • [cs.LG]Proximal Policy Optimization for Tracking Control Exploiting Future Reference Information
    • [cs.LG]Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Technical Challenges and Solutions
    • [cs.LG]Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion
    • [cs.LG]Significant Wave Height Prediction based on Wavelet Graph Neural Network
    • [cs.LG]Toward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural Language
    • [cs.LG]Transfer Learning for Credit Card Fraud Detection: A Journey from Research to Production
    • [cs.LG]VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition
    • [cs.LG]Wave-Informed Matrix Factorization withGlobal Optimality Guarantees
    • [cs.MA]Rational Verification for Probabilistic Systems
    • [cs.NE]Using Shape Constraints for Improving Symbolic Regression Models
    • [cs.NI]Into Summarization Techniques for IoT Data Discovery Routing
    • [cs.RO]A Portable Agricultural Robot for Continuous Apparent Soil ElectricalConductivity Measurements to Improve Irrigation Practices
    • [cs.RO]Attitude and In-orbit Residual Magnetic Moment Estimation of Small Satellites Using only Magnetometer
    • [cs.RO]Consensus-Informed Optimization Over Mixtures for Ambiguity-Aware Object SLAM
    • [cs.RO]Constellation Design of Remote Sensing Small Satellite for Infrastructure Monitoring in India
    • [cs.RO]Learning to Share Autonomy Across Repeated Interaction
    • [cs.RO]Ontology-Assisted Generalisation of Robot Action Execution Knowledge
    • [cs.RO]Reinforcement learning autonomously identifying the source of errors for agents in a group mission
    • [cs.SD]A Real-time Speaker Diarization System Based on Spatial Spectrum
    • [cs.SD]On Prosody Modeling for ASR+TTS based Voice Conversion
    • [cs.SD]Sequence-to-Sequence Piano Transcription with Transformers
    • [cs.SE]Multi-objective Test Case Selection Through Linkage Learning-based Crossover
    • [cs.SI]Analysis of External Content in the Vaccination Discussion on Twitter
    • [cs.SI]Predicting the 2020 US Presidential Election with Twitter
    • [cs.SI]Proximity in face-to-face interaction is associated with mobile phone communication
    • [econ.TH]Data Sharing Markets
    • [eess.AS]SVSNet: An End-to-end Speaker Voice Similarity Assessment Model
    • [eess.AS]Streaming End-to-End ASR based on Blockwise Non-Autoregressive Models
    • [eess.IV]A Review of Generative Adversarial Networks in Cancer Imaging: New Applications, New Solutions
    • [eess.IV]Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation
    • [eess.IV]Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT
    • [eess.IV]Confidence Aware Neural Networks for Skin Cancer Detection
    • [eess.IV]Convolutional module for heart localization and segmentation in MRI
    • [eess.IV]DeepSMILE: Self-supervised heterogeneity-aware multiple instance learning for DNA damage response defect classification directly from H&E whole-slide images
    • [eess.IV]LAPNet: Non-rigid Registration derived in k-space for Magnetic Resonance Imaging
    • [eess.IV]OSLO: On-the-Sphere Learning for Omnidirectional images and its application to 360-degree image compression
    • [eess.IV]Protecting Semantic Segmentation Models by Using Block-wise Image Encryption with Secret Key from Unauthorized Access
    • [eess.IV]Quality and Complexity Assessment of Learning-Based Image Compression Solutions
    • [eess.IV]SynthSeg: Domain Randomisation for Segmentation of Brain MRI Scans of any Contrast and Resolution
    • [eess.SP]Accelerating Edge Intelligence via Integrated Sensing and Communication
    • [eess.SP]Explicit Calibration of mmWave Phased Arrays with Phase Dependent Errors
    • [eess.SP]Modality Fusion Network and Personalized Attention in Momentary Stress Detection in the Wild
    • [eess.SY]A DoE-based approach for the implementation of structural surrogate models in the early stage design of box-wing aircraft
    • [math.AT]Entropy as a Topological Operad Derivation
    • [math.NA]Eigenvector Centrality and Uniform Dominant Eigenvalue of Graph Components
    • [math.NA]Positively Weighted Kernel Quadrature via Subsampling
    • [math.OA]Quantum smooth uncertainty principles for von Neumann bi-algebras
    • [math.OC]Asymptotic Escape of Spurious Critical Points on the Low-rank Matrix Manifold
    • [math.ST]Directional testing for high-dimensional multivariate normal distributions
    • [math.ST]Estimation of a regression function on a manifold by fully connected deep neural networks
    • [math.ST]Generalized maximum likelihood estimation of the mean of parameters of mixtures, with applications to sampling
    • [math.ST]Multi-Normex Distributions for the Sum of Random Vectors. Rates of Convergence
    • [math.ST]On Estimating Rank-One Spiked Tensors in the Presence of Heavy Tailed Errors
    • [math.ST]On some information-theoretic aspects of non-linear statistical inverse problems
    • [math.ST]Record-Based Transmuted Generalized Linear Exponential Distribution with Increasing, Decreasing and Bathtub Shaped Failure Rates
    • [math.ST]The Completion of Covariance Kernels
    • [math.ST]The Smoking Gun: Statistical Theory Improves Neural Network Estimates
    • [physics.flu-dyn]Hybrid neural network reduced order modelling for turbulent flows with geometric parameters
    • [physics.soc-ph]On node ranking in graphs
    • [q-fin.CP]AI in Finance: Challenges, Techniques and Opportunities
    • [q-fin.ST]Stock price prediction using BERT and GAN
    • [q-fin.TR]Order Book Queue Hawkes-Markovian Modeling
    • [quant-ph]Sample Complexity of Learning Quantum Circuits
    • [stat.AP]A Comparison of Value-Added Models for School Accountability
    • [stat.AP]A Non-ergodic Spectral Acceleration Ground Motion Model for California Developed with Random Vibration Theory
    • [stat.AP]BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data
    • [stat.AP]Pooled testing to isolate infected individuals
    • [stat.AP]Study of the Parent-of-origin effect in monogenic diseases with variable age of onset. Application on ATTRv
    • [stat.CO]JAGS, NIMBLE, Stan: a detailed comparison among Bayesian MCMC software
    • [stat.ME]Accounting for spatial confounding in epidemiological studies with individual-level exposures: An exposure-penalized spline approach
    • [stat.ME]Adaptively Sampling via Regional Variance-Based Sensitivities
    • [stat.ME]Conditional Wasserstein Barycenters and Interpolation/Extrapolation of Distributions
    • [stat.ME]Diagnosis of model-structural errors with a sliding time-window Bayesian analysis
    • [stat.ME]Inference for Change Points in High Dimensional Mean Shift Models
    • [stat.ME]Kpop: A kernel balancing approach for reducing specification assumptions in survey weighting
    • [stat.ME]Moving towards practical user-friendly synthesis: Scalable synthetic data methods for large confidential administrative databases using saturated count models
    • [stat.ME]Sparse composite likelihood selection
    • [stat.ML]A Bayesian Approach to Invariant Deep Neural Networks
    • [stat.ML]Adaptive wavelet distillation from neural networks through interpretations
    • [stat.ML]An induction proof of the backpropagation algorithm in matrix notation
    • [stat.ML]Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression
    • [stat.ML]Canonical Polyadic Decomposition and Deep Learning for Machine Fault Detection
    • [stat.ML]High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids
    • [stat.ML]Reward-Weighted Regression Converges to a Global Optimum

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

    • [astro-ph.CO]Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning
    Maria Han Veiga, Xi Meng, Oleg Y. Gnedin, Nickolay Y. Gnedin, Xun Huan
    http://arxiv.org/abs/2107.09082v1

    • [astro-ph.EP]DPNNet-2.0 Part I: Finding hidden planets from simulated images of protoplanetary disk gaps
    Sayantan Auddy, Ramit Dey, Min-Kai Lin, Cassandra Hall
    http://arxiv.org/abs/2107.09086v1

    • [astro-ph.HE]Dim but not entirely dark: Extracting the Galactic Center Excess’ source-count distribution with neural nets
    Florian List, Nicholas L. Rodd, Geraint F. Lewis
    http://arxiv.org/abs/2107.09070v1

    • [cond-mat.mtrl-sci]Establishing process-structure linkages using Generative Adversarial Networks
    Mohammad Safiuddin, CH Likith Reddy, Ganesh Vasantada, CHJNS Harsha, Srinu Gangolu
    http://arxiv.org/abs/2107.09402v1

    • [cs.AI]Learning Altruistic Behaviours in Reinforcement Learning without External Rewards
    Tim Franzmeyer, Mateusz Malinowski, João F. Henriques
    http://arxiv.org/abs/2107.09598v1

    • [cs.AI]MIMO: Mutual Integration of Patient Journey and Medical Ontology for Healthcare Representation Learning
    Xueping Peng, and Guodong Long, Tao Shen, Sen Wang, Zhendong Niu, Chengqi Zhang
    http://arxiv.org/abs/2107.09288v1

    • [cs.AI]Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
    Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
    http://arxiv.org/abs/2107.09645v1

    • [cs.AI]Semantic Reasoning with Differentiable Graph Transformations
    Alberto Cetoli
    http://arxiv.org/abs/2107.09579v1

    • [cs.AI]ThingFO v1.2’s Terms, Properties, Relationships and Axioms — Foundational Ontology for Things
    Luis Olsina
    http://arxiv.org/abs/2107.09129v1

    • [cs.AR]CREW: Computation Reuse and Efficient Weight Storage for Hardware-accelerated MLPs and RNNs
    Marc Riera, Jose-Maria Arnau, Antonio Gonzalez
    http://arxiv.org/abs/2107.09408v1

    • [cs.AR]Positive/Negative Approximate Multipliers for DNN Accelerators
    Ourania Spantidi, Georgios Zervakis, Iraklis Anagnostopoulos, Hussam Amrouch, Jörg Henkel
    http://arxiv.org/abs/2107.09366v1

    • [cs.AR]StreamBlocks: A compiler for heterogeneous dataflow computing (technical report)
    Endri Bezati, Mahyar Emami, Jörn Janneck, James Larus
    http://arxiv.org/abs/2107.09333v1

    • [cs.CE]Similarity metrics for Different Market Scenarios in Abides
    Diego Pino, Javier García, Fernando Fernández, Svitlana S Vyetrenko
    http://arxiv.org/abs/2107.09352v1

    • [cs.CL]BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledge
    Huiqiang Jiang, Guoxin Wang, Weile Chen, Chengxi Zhang, Börje F. Karlsson
    http://arxiv.org/abs/2107.09429v1

    • [cs.CL]Cross-Lingual BERT Contextual Embedding Space Mapping with Isotropic and Isometric Conditions
    Haoran Xu, Philipp Koehn
    http://arxiv.org/abs/2107.09186v1

    • [cs.CL]Different kinds of cognitive plausibility: why are transformers better than RNNs at predicting N400 amplitude?
    James A. Michaelov, Megan D. Bardolph, Seana Coulson, Benjamin K. Bergen
    http://arxiv.org/abs/2107.09648v1

    • [cs.CL]Improving Sentence-Level Relation Extraction through Curriculum Learning
    Seongsik Park, Harksoo Kim
    http://arxiv.org/abs/2107.09332v1

    • [cs.CL]Learning ULMFiT and Self-Distillation with Calibration for Medical Dialogue System
    Shuang Ao, Xeno Acharya
    http://arxiv.org/abs/2107.09625v1

    • [cs.CL]More Parameters? No Thanks!
    Zeeshan Khan, Kartheek Akella, Vinay P. Namboodiri, C V Jawahar
    http://arxiv.org/abs/2107.09622v1

    • [cs.CL]Neural Abstructions: Abstractions that Support Construction for Grounded Language Learning
    Kaylee Burns, Christopher D. Manning, Li Fei-Fei
    http://arxiv.org/abs/2107.09285v1

    • [cs.CL]Paraphrasing via Ranking Many Candidates
    Joosung Lee
    http://arxiv.org/abs/2107.09274v1

    • [cs.CL]Seed Words Based Data Selection for Language Model Adaptation
    Roberto Gretter, Marco Matassoni, Daniele Falavigna
    http://arxiv.org/abs/2107.09433v1

    • [cs.CL]Sequence Model with Self-Adaptive Sliding Window for Efficient Spoken Document Segmentation
    Qinglin Zhang, Qian Chen, Yali Li, Jiaqing Liu, Wen Wang
    http://arxiv.org/abs/2107.09278v1

    • [cs.CL]Simultaneous Speech Translation for Live Subtitling: from Delay to Display
    Alina Karakanta, Sara Papi, Matteo Negri, Marco Turchi
    http://arxiv.org/abs/2107.08807v2

    • [cs.CL]Token-Level Supervised Contrastive Learning for Punctuation Restoration
    Qiushi Huang, Tom Ko, H Lilian Tang, Xubo Liu, Bo Wu
    http://arxiv.org/abs/2107.09099v1

    • [cs.CL]WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset
    Luyu Wang, Yujia Li, Ozlem Aslan, Oriol Vinyals
    http://arxiv.org/abs/2107.09556v1

    • [cs.CR]GNN4IP: Graph Neural Network for Hardware Intellectual Property Piracy Detection
    Rozhin Yasaei, Shih-Yuan Yu, Emad Kasaeyan Naeini, Mohammad Abdullah Al Faruque
    http://arxiv.org/abs/2107.09130v1

    • [cs.CR]Image-Hashing-Based Anomaly Detection for Privacy-Preserving Online Proctoring
    Waheeb Yaqub, Manoranjan Mohanty, Basem Suleiman
    http://arxiv.org/abs/2107.09373v1

    • [cs.CV]A Comparison of Supervised and Unsupervised Deep Learning Methods for Anomaly Detection in Images
    Vincent Wilmet, Sauraj Verma, Tabea Redl, Håkon Sandaker, Zhenning Li
    http://arxiv.org/abs/2107.09204v1

    • [cs.CV]Accelerating deep neural networks for efficient scene understanding in automotive cyber-physical systems
    Stavros Nousias, Erion-Vasilis Pikoulis, Christos Mavrokefalidis, Aris S. Lalos
    http://arxiv.org/abs/2107.09101v1

    • [cs.CV]Active 3D Shape Reconstruction from Vision and Touch
    Edward J. Smith, David Meger, Luis Pineda, Roberto Calandra, Jitendra Malik, Adriana Romero, Michal Drozdzal
    http://arxiv.org/abs/2107.09584v1

    • [cs.CV]Attention-Guided NIR Image Colorization via Adaptive Fusion of Semantic and Texture Clues
    Xingxing Yang, Jie Chen, Zaifeng Yang, Zhenghua Chen
    http://arxiv.org/abs/2107.09237v1

    • [cs.CV]Audio2Head: Audio-driven One-shot Talking-head Generation with Natural Head Motion
    Suzhen Wang, Lincheng Li, Yu Ding, Changjie Fan, Xin Yu
    http://arxiv.org/abs/2107.09293v1

    • [cs.CV]Boosting few-shot classification with view-learnable contrastive learning
    Xu Luo, Yuxuan Chen, Liangjian Wen, Lili Pan, Zenglin Xu
    http://arxiv.org/abs/2107.09242v1

    • [cs.CV]Built-in Elastic Transformations for Improved Robustness
    Sadaf Gulshad, Ivan Sosnovik, Arnold Smeulders
    http://arxiv.org/abs/2107.09391v1

    • [cs.CV]Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
    Kazuma Fujii, Suehiro Daiki, Nishimura Kazuya, Bise Ryoma
    http://arxiv.org/abs/2107.09289v1

    • [cs.CV]Compound Figure Separation of Biomedical Images with Side Loss
    Tianyuan Yao, Chang Qu, Quan Liu, Ruining Deng, Yuanhan Tian, Jiachen Xu, Aadarsh Jha, Shunxing Bao, Mengyang Zhao, Agnes B. Fogo, Bennett A. Landman, Catie Chang, Haichun Yang, Yuankai Huo
    http://arxiv.org/abs/2107.08650v1

    • [cs.CV]Critic Guided Segmentation of Rewarding Objects in First-Person Views
    Andrew Melnik, Augustin Harter, Christian Limberg, Krishan Rana, Niko Suenderhauf, Helge Ritter
    http://arxiv.org/abs/2107.09540v1

    • [cs.CV]DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation
    Li Gao, Jing Zhang, Lefei Zhang, Dacheng Tao
    http://arxiv.org/abs/2107.09600v1

    • [cs.CV]Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography
    Olivia Byrnes, Wendy La, Hu Wang, Congbo Ma, Minhui Xue, Qi Wu
    http://arxiv.org/abs/2107.09287v1

    • [cs.CV]DeepSocNav: Social Navigation by Imitating Human Behaviors
    Juan Pablo de Vicente, Alvaro Soto
    http://arxiv.org/abs/2107.09170v1

    • [cs.CV]Discriminator-Free Generative Adversarial Attack
    Shaohao Lu, Yuqiao Xian, Ke Yan, Yi Hu, Xing Sun, Xiaowei Guo, Feiyue Huang, Wei-Shi Zheng
    http://arxiv.org/abs/2107.09225v1

    • [cs.CV]Examining the Human Perceptibility of Black-Box Adversarial Attacks on Face Recognition
    Benjamin Spetter-Goldstein, Nataniel Ruiz, Sarah Adel Bargal
    http://arxiv.org/abs/2107.09126v1

    • [cs.CV]Face.evoLVe: A High-Performance Face Recognition Library
    Qingzhong Wang, Pengfei Zhang, Haoyi Xiong, Jian Zhao
    http://arxiv.org/abs/2107.08621v2

    • [cs.CV]Image Fusion Transformer
    Vibashan VS, Jeya Maria Jose Valanarasu, Poojan Oza, Vishal M. Patel
    http://arxiv.org/abs/2107.09011v2

    • [cs.CV]InsPose: Instance-Aware Networks for Single-Stage Multi-Person Pose Estimation
    Dahu Shi, Xing Wei, Xiaodong Yu, Wenming Tan, Ye Ren, Shiliang Pu
    http://arxiv.org/abs/2107.08982v2

    • [cs.CV]Learning a Sensor-invariant Embedding of Satellite Data: A Case Study for Lake Ice Monitoring
    Manu Tom, Yuchang Jiang, Emmanuel Baltsavias, Konrad Schindler
    http://arxiv.org/abs/2107.09092v1

    • [cs.CV]Locality-aware Channel-wise Dropout for Occluded Face Recognition
    Mingjie He, Jie Zhang, Shiguang Shan, Xiao Liu, Zhongqin Wu, Xilin Chen
    http://arxiv.org/abs/2107.09270v1

    • [cs.CV]Monocular Visual Analysis for Electronic Line Calling of Tennis Games
    Yuanzhou Chen, Shaobo Cai, Yuxin Wang, Junchi Yan
    http://arxiv.org/abs/2107.09255v1

    • [cs.CV]Multi-Modal Temporal Convolutional Network for Anticipating Actions in Egocentric Videos
    Olga Zatsarynna, Yazan Abu Farha, Juergen Gall
    http://arxiv.org/abs/2107.09504v1

    • [cs.CV]QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries
    Jie Lei, Tamara L. Berg, Mohit Bansal
    http://arxiv.org/abs/2107.09609v1

    • [cs.CV]RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank
    Wenlong Zhang, Yihao Liu, Chao Dong, Yu Qiao
    http://arxiv.org/abs/2107.09427v1

    • [cs.CV]ReSSL: Relational Self-Supervised Learning with Weak Augmentation
    Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu
    http://arxiv.org/abs/2107.09282v1

    • [cs.CV]S2Looking: A Satellite Side-Looking Dataset for Building Change Detection
    Li Shen, Yao Lu, Hao Chen, Hao Wei, Donghai Xie, Jiabao Yue, Rui Chen, Yue Zhang, Ao Zhang, Shouye Lv, Bitao Jiang
    http://arxiv.org/abs/2107.09244v1

    • [cs.CV]Saliency for free: Saliency prediction as a side-effect of object recognition
    Carola Figueroa-Flores, David Berga, Joost van der Weijer, Bogdan Raducanu
    http://arxiv.org/abs/2107.09628v1

    • [cs.CV]Self-Supervised Domain Adaptation for Diabetic Retinopathy Grading using Vessel Image Reconstruction
    Duy M. H. Nguyen, Truong T. N. Mai, Ngoc T. T. Than, Alexander Prange, Daniel Sonntag
    http://arxiv.org/abs/2107.09372v1

    • [cs.CV]Separating Skills and Concepts for Novel Visual Question Answering
    Spencer Whitehead, Hui Wu, Heng Ji, Rogerio Feris, Kate Saenko
    http://arxiv.org/abs/2107.09106v1

    • [cs.CV]SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models
    Moonbin Yim, Yoonsik Kim, Han-Cheol Cho, Sungrae Park
    http://arxiv.org/abs/2107.09313v1

    • [cs.CV]Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision
    Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng
    http://arxiv.org/abs/2107.09249v1

    • [cs.CV]Towards Privacy-preserving Explanations in Medical Image Analysis
    H. Montenegro, W. Silva, J. S. Cardoso
    http://arxiv.org/abs/2107.09652v1

    • [cs.CV]Understanding Gender and Racial Disparities in Image Recognition Models
    Rohan Mahadev, Anindya Chakravarti
    http://arxiv.org/abs/2107.09211v1

    • [cs.CV]Video Crowd Localization with Multi-focus Gaussian Neighbor Attention and a Large-Scale Benchmark
    Haopeng Li, Lingbo Liu, Kunlin Yang, Shinan Liu, Junyu Gao, Bin Zhao, Rui Zhang, Jun Hou
    http://arxiv.org/abs/2107.08645v2

    • [cs.CY]Diversity in Sociotechnical Machine Learning Systems
    Sina Fazelpour, Maria De-Arteaga
    http://arxiv.org/abs/2107.09163v1

    • [cs.CY]From Teaching to Coaching: A Case Study of a Technical Communication Course
    Rayed Alghamdi, Seyed M. Buhari, Madini O. Alassafi
    http://arxiv.org/abs/2107.09533v1

    • [cs.CY]IT ambidexterity driven patient agility and hospital patient service performance: a variance approach
    Rogier van de Wetering
    http://arxiv.org/abs/2107.09415v1

    • [cs.CY]Multi-Layered Diagnostics for Smart Cities
    Jungheum Park, Hyunji Chung, Joanna F. DeFranco
    http://arxiv.org/abs/2107.09284v1

    • [cs.CY]The role of IT ambidexterity, digital dynamic capability and knowledge processes as enablers of patient agility: an empirical study
    Rogier van de Wetering, Johan Versendaal
    http://arxiv.org/abs/2107.09419v1

    • [cs.CY]Toward Trustworthy Urban IT Systems: The Bright and Dark Sides of Smart City Development
    Jungheum Park, Hyunji Chung
    http://arxiv.org/abs/2107.09283v1

    • [cs.DC]A New Design Framework for Heterogeneous Uncoded Storage Elastic Computing
    Mingyue Ji, Xiang Zhang, Kai Wan
    http://arxiv.org/abs/2107.09657v1

    • [cs.DC]Online Deployment Algorithms for Microservice Systems with Complex Dependencies
    Xiang He, Zhiying Tu, Markus Wagner, Xiaofei Xu, Zhongjie Wang
    http://arxiv.org/abs/2107.09308v1

    • [cs.DL]Temporal search in the scientific space predicts breakthrough inventions
    Chao Min, Qing Ke
    http://arxiv.org/abs/2107.09176v1

    • [cs.HC]Readability Research: An Interdisciplinary Approach
    Sofie Beier, Sam Berlow, Esat Boucaud, Zoya Bylinskii, Tianyuan Cai, Jenae Cohn, Kathy Crowley, Stephanie L. Day, Tilman Dingler, Jonathan Dobres, Jennifer Healey, Rajiv Jain, Marjorie Jordan, Bernard Kerr, Qisheng Li, Dave B. Miller, Susanne Nobles, Alexandra Papoutsaki, Jing Qian, Tina Rezvanian, Shelley Rodrigo, Ben D. Sawyer, Shannon M. Sheppard, Bram Stein, Rick Treitman, Jen Vanek, Shaun Wallace, Benjamin Wolfe
    http://arxiv.org/abs/2107.09615v1

    • [cs.IR]Learned Sorted Table Search and Static Indexes in Small Space: Methodological and Practical Insights via an Experimental Study
    Domenico Amato, Raffaele Giancarlo, Giosuè Lo Bosco
    http://arxiv.org/abs/2107.09480v1

    • [cs.IT]A DNN-based OTFS Transceiver with Delay-Doppler Channel Training and IQI Compensation
    Ashwitha Naikoti, A. Chockalingam
    http://arxiv.org/abs/2107.09376v1

    • [cs.IT]Exploring the Non-Overlapping Visibility Regions in XL-MIMO Random Access Protocol
    José Carlos Marinello Filho, Glauber Brante, Richard Demo Souza, Taufik Abrão
    http://arxiv.org/abs/2107.09169v1

    • [cs.IT]How Does Cell-Free Massive MIMO Support Multiple Federated Learning Groups?
    Tung T. Vu, Hien Quoc Ngo, Thomas L. Marzetta, Michail Matthaiou
    http://arxiv.org/abs/2107.09577v1

    • [cs.IT]Maximizing the Set Cardinality of Users Scheduled for Ultra-dense uRLLC Networks
    Shiwen He, Jun Yuan, Zhenyu An, Yunshan Yi, Yongming Huang
    http://arxiv.org/abs/2107.09404v1

    • [cs.IT]Relay-Assisted Cooperative Federated Learning
    Zehong Lin, Hang Liu, Ying-Jun Angela Zhang
    http://arxiv.org/abs/2107.09518v1

    • [cs.IT]Rethinking the Tradeoff in Integrated Sensing and Communication: Recognition Accuracy versus Communication Rate
    Guoliang Li, Shuai Wang, Jie Li, Rui Wang, Fan Liu, Meihong Zhang, Xiaohui Peng, Tony Xiao Han
    http://arxiv.org/abs/2107.09621v1

    • [cs.IT]Support Recovery in Universal One-bit Compressed Sensing
    Arya Mazumdar, Soumyabrata Pal
    http://arxiv.org/abs/2107.09091v1

    • [cs.IT]User Association in Dense mmWave Networks as Restless Bandits
    S. K. Singh, V. S. Borkar, G. S. Kasbekar
    http://arxiv.org/abs/2107.09153v1

    • [cs.LG]A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks
    Erion-Vasilis Pikoulis, Christos Mavrokefalidis, Aris S. Lalos
    http://arxiv.org/abs/2107.09095v1

    • [cs.LG]Adaptive Transfer Learning on Graph Neural Networks
    Xueting Han, Zhenhuan Huang, Bang An, Jing Bai
    http://arxiv.org/abs/2107.08765v2

    • [cs.LG]Algorithm Selection on a Meta Level
    Alexander Tornede, Lukas Gehring, Tanja Tornede, Marcel Wever, Eyke Hüllermeier
    http://arxiv.org/abs/2107.09414v1

    • [cs.LG]An Embedding of ReLU Networks and an Analysis of their Identifiability
    Pierre Stock, Rémi Gribonval
    http://arxiv.org/abs/2107.09370v1

    • [cs.LG]An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients
    João Carvalho, Davide Tateo, Fabio Muratore, Jan Peters
    http://arxiv.org/abs/2107.09359v1

    • [cs.LG]Approximation Theory of Convolutional Architectures for Time Series Modelling
    Haotian Jiang, Zhong Li, Qianxiao Li
    http://arxiv.org/abs/2107.09355v1

    • [cs.LG]Best-of-All-Worlds Bounds for Online Learning with Feedback Graphs
    Liad Erez, Tomer Koren
    http://arxiv.org/abs/2107.09572v1

    • [cs.LG]ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE
    Qingzhong Ai, Lirong He, Shiyu Liu, Zenglin Xu
    http://arxiv.org/abs/2107.09286v1

    • [cs.LG]CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression
    Zhize Li, Peter Richtárik
    http://arxiv.org/abs/2107.09461v1

    • [cs.LG]Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning
    Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer
    http://arxiv.org/abs/2107.09562v1

    • [cs.LG]Constrained Policy Gradient Method for Safe and Fast Reinforcement Learning: a Neural Tangent Kernel Based Approach
    Balázs Varga, Balázs Kulcsár, Morteza Haghir Chehreghani
    http://arxiv.org/abs/2107.09139v1

    • [cs.LG]Edge of chaos as a guiding principle for modern neural network training
    Lin Zhang, Ling Feng, Kan Chen, Choy Heng Lai
    http://arxiv.org/abs/2107.09437v1

    • [cs.LG]Evaluating Probabilistic Inference in Deep Learning: Beyond Marginal Predictions
    Xiuyuan Lu, Ian Osband, Benjamin Van Roy, Zheng Wen
    http://arxiv.org/abs/2107.09224v1

    • [cs.LG]Feature-Filter: Detecting Adversarial Examples through Filtering off Recessive Features
    Hui Liu, Bo Zhao, Yuefeng Peng, Jiabao Guo, Peng Liu
    http://arxiv.org/abs/2107.09502v1

    • [cs.LG]FoleyGAN: Visually Guided Generative Adversarial Network-Based Synchronous Sound Generation in Silent Videos
    Sanchita Ghose, John J. Prevost
    http://arxiv.org/abs/2107.09262v1

    • [cs.LG]Follow Your Path: a Progressive Method for Knowledge Distillation
    Wenxian Shi, Yuxuan Song, Hao Zhou, Bohan Li, Lei Li
    http://arxiv.org/abs/2107.09305v1

    • [cs.LG]Generative Video Transformer: Can Objects be the Words?
    Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn
    http://arxiv.org/abs/2107.09240v1

    • [cs.LG]Heterogeneous network-based drug repurposing for COVID-19
    Shuting Jin, Xiangxiang Zeng, Wei Huang, Feng Xia, Changzhi Jiang, Xiangrong Liu, Shaoliang Peng
    http://arxiv.org/abs/2107.09217v1

    • [cs.LG]Improving exploration in policy gradient search: Application to symbolic optimization
    Mikel Landajuela Larma, Brenden K. Petersen, Soo K. Kim, Claudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol
    http://arxiv.org/abs/2107.09158v1

    • [cs.LG]Kernel Selection for Stein Variational Gradient Descent
    Qingzhong Ai, Shiyu Liu, Zenglin Xu
    http://arxiv.org/abs/2107.09338v1

    • [cs.LG]LENS: Layer Distribution Enabled Neural Architecture Search in Edge-Cloud Hierarchies
    Mohanad Odema, Nafiul Rashid, Berken Utku Demirel, Mohammad Abdullah Al Faruque
    http://arxiv.org/abs/2107.09309v1

    • [cs.LG]Large-scale graph representation learning with very deep GNNs and self-supervision
    Ravichandra Addanki, Peter W. Battaglia, David Budden, Andreea Deac, Jonathan Godwin, Thomas Keck, Wai Lok Sibon Li, Alvaro Sanchez-Gonzalez, Jacklynn Stott, Shantanu Thakoor, Petar Veličković
    http://arxiv.org/abs/2107.09422v1

    • [cs.LG]Latency-Memory Optimized Splitting of Convolution Neural Networks for Resource Constrained Edge Devices
    Tanmay Jain, Avaneesh, Rohit Verma, Rajeev Shorey
    http://arxiv.org/abs/2107.09123v1

    • [cs.LG]Learn2Hop: Learned Optimization on Rough Landscapes
    Amil Merchant, Luke Metz, Sam Schoenholz, Ekin Dogus Cubuk
    http://arxiv.org/abs/2107.09661v1

    • [cs.LG]M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis
    Xingbo Wang, Jianben He, Zhihua Jin, Muqiao Yang, Yong Wang, Huamin Qu
    http://arxiv.org/abs/2107.08264v2

    • [cs.LG]Mining Topological Dependencies of Recurrent Congestion in Road Networks
    Nicolas Tempelmeier, Udo Feuerhake, Oskar Wage, Elena Demidova
    http://arxiv.org/abs/2107.09554v1

    • [cs.LG]OnlineSTL: Scaling Time Series Decomposition by 100x
    Abhinav Mishra, Ram Sriharsha, Sichen Zhong
    http://arxiv.org/abs/2107.09110v1

    • [cs.LG]Open Problem: Is There an Online Learning Algorithm That Learns Whenever Online Learning Is Possible?
    Steve Hanneke
    http://arxiv.org/abs/2107.09542v1

    • [cs.LG]Parametric Scattering Networks
    Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
    http://arxiv.org/abs/2107.09539v1

    • [cs.LG]Path Integrals for the Attribution of Model Uncertainties
    Iker Perez, Piotr Skalski, Alec Barns-Graham, Jason Wong, David Sutton
    http://arxiv.org/abs/2107.08756v2

    • [cs.LG]Precision-Weighted Federated Learning
    Jonatan Reyes, Lisa Di Jorio, Cecile Low-Kam, Marta Kersten-Oertel
    http://arxiv.org/abs/2107.09627v1

    • [cs.LG]Predicting Driver Takeover Time in Conditionally Automated Driving
    Jackie Ayoub, Na Du, X. Jessie Yang, Feng Zhou
    http://arxiv.org/abs/2107.09545v1

    • [cs.LG]Predicting Friction System Performance with Symbolic Regression and Genetic Programming with Factor Variables
    Gabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel
    http://arxiv.org/abs/2107.09484v1

    • [cs.LG]Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI
    Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang
    http://arxiv.org/abs/2107.08821v1

    • [cs.LG]Proximal Policy Optimization for Tracking Control Exploiting Future Reference Information
    Jana Mayer, Johannes Westermann, Juan Pedro Gutiérrez H. Muriedas, Uwe Mettin, Alexander Lampe
    http://arxiv.org/abs/2107.09647v1

    • [cs.LG]Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Technical Challenges and Solutions
    Eike Petersen, Yannik Potdevin, Esfandiar Mohammadi, Stephan Zidowitz, Sabrina Breyer, Dirk Nowotka, Sandra Henn, Ludwig Pechmann, Martin Leucker, Philipp Rostalski, Christian Herzog
    http://arxiv.org/abs/2107.09546v1

    • [cs.LG]Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion
    Daniel Kunin, Javier Sagastuy-Brena, Lauren Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins
    http://arxiv.org/abs/2107.09133v1

    • [cs.LG]Significant Wave Height Prediction based on Wavelet Graph Neural Network
    Delong Chen, Fan Liu, Zheqi Zhang, Xiaomin Lu, Zewen Li
    http://arxiv.org/abs/2107.09483v1

    • [cs.LG]Toward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural Language
    Kevin Eloff, Herman Engelbrecht
    http://arxiv.org/abs/2107.09356v1

    • [cs.LG]Transfer Learning for Credit Card Fraud Detection: A Journey from Research to Production
    Wissam Siblini, Guillaume Coter, Rémy Fabry, Liyun He-Guelton, Frédéric Oblé, Bertrand Lebichot, Yann-Aël Le Borgne, Gianluca Bontempi
    http://arxiv.org/abs/2107.09323v1

    • [cs.LG]VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition
    Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui
    http://arxiv.org/abs/2107.08861v2

    • [cs.LG]Wave-Informed Matrix Factorization withGlobal Optimality Guarantees
    Harsha Vardhan Tetali, Joel B. Harley, Benjamin D. Haeffele
    http://arxiv.org/abs/2107.09144v1

    • [cs.MA]Rational Verification for Probabilistic Systems
    Julian Gutierrez, Lewis Hammond, Anthony Lin, Muhammad Najib, Michael Wooldridge
    http://arxiv.org/abs/2107.09119v1

    • [cs.NE]Using Shape Constraints for Improving Symbolic Regression Models
    Christian Haider, Fabricio Olivetti de França, Bogdan Burlacu, Gabriel Kronberger
    http://arxiv.org/abs/2107.09458v1

    • [cs.NI]Into Summarization Techniques for IoT Data Discovery Routing
    Hieu Tran, Son Nguyen, I-Ling Yen, Farokh Bastani
    http://arxiv.org/abs/2107.09558v1

    • [cs.RO]A Portable Agricultural Robot for Continuous Apparent Soil ElectricalConductivity Measurements to Improve Irrigation Practices
    Merrick Campbell, Keran Ye, Elia Scudiero, Konstantinos Karydis
    http://arxiv.org/abs/2107.09219v1

    • [cs.RO]Attitude and In-orbit Residual Magnetic Moment Estimation of Small Satellites Using only Magnetometer
    Raunak Srivastava, Roshan Sah, Kaushik Das
    http://arxiv.org/abs/2107.09257v1

    • [cs.RO]Consensus-Informed Optimization Over Mixtures for Ambiguity-Aware Object SLAM
    Ziqi Lu, Qiangqiang Huang, Kevin Doherty, John J. Leonard
    http://arxiv.org/abs/2107.09265v1

    • [cs.RO]Constellation Design of Remote Sensing Small Satellite for Infrastructure Monitoring in India
    Roshan Sah, Raunak Srivastava, Kaushik Das
    http://arxiv.org/abs/2107.09253v1

    • [cs.RO]Learning to Share Autonomy Across Repeated Interaction
    Ananth Jonnavittula, Dylan P. Losey
    http://arxiv.org/abs/2107.09650v1

    • [cs.RO]Ontology-Assisted Generalisation of Robot Action Execution Knowledge
    Alex Mitrevski, Paul G. Plöger, Gerhard Lakemeyer
    http://arxiv.org/abs/2107.09353v1

    • [cs.RO]Reinforcement learning autonomously identifying the source of errors for agents in a group mission
    Keishu Utimula, Ken-taro Hayaschi, Kousuke Nakano, Kenta Hongo, Ryo Maezono
    http://arxiv.org/abs/2107.09232v1

    • [cs.SD]A Real-time Speaker Diarization System Based on Spatial Spectrum
    Siqi Zheng, Weilong Huang, Xianliang Wang, Hongbin Suo, Jinwei Feng, Zhijie Yan
    http://arxiv.org/abs/2107.09321v1

    • [cs.SD]On Prosody Modeling for ASR+TTS based Voice Conversion
    Wen-Chin Huang, Tomoki Hayashi, Xinjian Li, Shinji Watanabe, Tomoki Toda
    http://arxiv.org/abs/2107.09477v1

    • [cs.SD]Sequence-to-Sequence Piano Transcription with Transformers
    Curtis Hawthorne, Ian Simon, Rigel Swavely, Ethan Manilow, Jesse Engel
    http://arxiv.org/abs/2107.09142v1

    • [cs.SE]Multi-objective Test Case Selection Through Linkage Learning-based Crossover
    Mitchell Olsthoorn, Annibale Panichella
    http://arxiv.org/abs/2107.08454v2

    • [cs.SI]Analysis of External Content in the Vaccination Discussion on Twitter
    Richard Kuzma, Iain J. Cruickshank, Kathleen M. Carley
    http://arxiv.org/abs/2107.09183v1

    • [cs.SI]Predicting the 2020 US Presidential Election with Twitter
    Michael Caballero
    http://arxiv.org/abs/2107.09640v1

    • [cs.SI]Proximity in face-to-face interaction is associated with mobile phone communication
    Tobias Bornakke, Talayeh Aledavood, Jari Saramäki, Sam G. B. Roberts
    http://arxiv.org/abs/2107.08872v2

    • [econ.TH]Data Sharing Markets
    Mohammad Rasouli, Michael I. Jordan
    http://arxiv.org/abs/2107.08630v2

    • [eess.AS]SVSNet: An End-to-end Speaker Voice Similarity Assessment Model
    Cheng-Hung Hu, Yu-Huai Peng, Junichi Yamagishi, Yu Tsao, Hsin-Min Wang
    http://arxiv.org/abs/2107.09392v1

    • [eess.AS]Streaming End-to-End ASR based on Blockwise Non-Autoregressive Models
    Tianzi Wang, Yuya Fujita, Xuankai Chang, Shinji Watanabe
    http://arxiv.org/abs/2107.09428v1

    • [eess.IV]A Review of Generative Adversarial Networks in Cancer Imaging: New Applications, New Solutions
    Richard Osuala, Kaisar Kushibar, Lidia Garrucho, Akis Linardos, Zuzanna Szafranowska, Stefan Klein, Ben Glocker, Oliver Diaz, Karim Lekadir
    http://arxiv.org/abs/2107.09543v1

    • [eess.IV]Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation
    Marius Memmel, Camila Gonzalez, Anirban Mukhopadhyay
    http://arxiv.org/abs/2107.08751v2

    • [eess.IV]Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT
    Gerda Bortsova, Daniel Bos, Florian Dubost, Meike W. Vernooij, M. Kamran Ikram, Gijs van Tulder, Marleen de Bruijne
    http://arxiv.org/abs/2107.09442v1

    • [eess.IV]Confidence Aware Neural Networks for Skin Cancer Detection
    Donya Khaledyan, AmirReza Tajally, Reza Sarkhosh, Afshar Shamsi, Hamzeh Asgharnezhad, Abbas Khosravi, Saeid Nahavandi
    http://arxiv.org/abs/2107.09118v1

    • [eess.IV]Convolutional module for heart localization and segmentation in MRI
    Daniel Lima, Catharine Graves, Marco Gutierrez, Bruno Brandoli, Jose Rodrigues-Jr
    http://arxiv.org/abs/2107.09134v1

    • [eess.IV]DeepSMILE: Self-supervised heterogeneity-aware multiple instance learning for DNA damage response defect classification directly from H&E whole-slide images
    Yoni Schirris, Efstratios Gavves, Iris Nederlof, Hugo Mark Horlings, Jonas Teuwen
    http://arxiv.org/abs/2107.09405v1

    • [eess.IV]LAPNet: Non-rigid Registration derived in k-space for Magnetic Resonance Imaging
    Thomas Küstner, Jiazhen Pan, Haikun Qi, Gastao Cruz, Christopher Gilliam, Thierry Blu, Bin Yang, Sergios Gatidis, René Botnar, Claudia Prieto
    http://arxiv.org/abs/2107.09060v1

    • [eess.IV]OSLO: On-the-Sphere Learning for Omnidirectional images and its application to 360-degree image compression
    Navid Mahmoudian Bidgoli, Roberto G. de A. Azevedo, Thomas Maugey, Aline Roumy, Pascal Frossard
    http://arxiv.org/abs/2107.09179v1

    • [eess.IV]Protecting Semantic Segmentation Models by Using Block-wise Image Encryption with Secret Key from Unauthorized Access
    Hiroki Ito, MaungMaung AprilPyone, Hitoshi Kiya
    http://arxiv.org/abs/2107.09362v1

    • [eess.IV]Quality and Complexity Assessment of Learning-Based Image Compression Solutions
    João Dick, Brunno Abreu, Mateus Grellert, Sergio Bampi
    http://arxiv.org/abs/2107.09136v1

    • [eess.IV]SynthSeg: Domain Randomisation for Segmentation of Brain MRI Scans of any Contrast and Resolution
    Benjamin Billot, Douglas N. Greve, Oula Puonti, Axel Thielscher, Koen Van Leemput, Bruce Fischl, Adrian V. Dalca, Juan Eugenio Iglesias
    http://arxiv.org/abs/2107.09559v1

    • [eess.SP]Accelerating Edge Intelligence via Integrated Sensing and Communication
    Tong Zhang, Shuai Wang, Guoliang Li, Fan Liu, Guangxu Zhu, Rui Wang
    http://arxiv.org/abs/2107.09574v1

    • [eess.SP]Explicit Calibration of mmWave Phased Arrays with Phase Dependent Errors
    Joyson Sebastian, Pranav Dayal, Kee-Bong Song, Walid AliAhmad
    http://arxiv.org/abs/2107.09561v1

    • [eess.SP]Modality Fusion Network and Personalized Attention in Momentary Stress Detection in the Wild
    Han Yu, Thomas Vaessen, Inez Myin-Germeys, Akane Sano
    http://arxiv.org/abs/2107.09510v1

    • [eess.SY]A DoE-based approach for the implementation of structural surrogate models in the early stage design of box-wing aircraft
    Vittorio Cipolla, Vincenzo Binante, Karim Abu Salem, Giuseppe Palaia, Davide Zanetti
    http://arxiv.org/abs/2107.07865v2

    • [math.AT]Entropy as a Topological Operad Derivation
    Tai-Danae Bradley
    http://arxiv.org/abs/2107.09581v1

    • [math.NA]Eigenvector Centrality and Uniform Dominant Eigenvalue of Graph Components
    Collins Anguzua, Christopher Engströmb, John Mango Magero, Henry Kasumbaa, Sergei Silvestrov, Benard Abola
    http://arxiv.org/abs/2107.09137v1

    • [math.NA]Positively Weighted Kernel Quadrature via Subsampling
    Satoshi Hayakawa, Harald Oberhauser, Terry Lyons
    http://arxiv.org/abs/2107.09597v1

    • [math.OA]Quantum smooth uncertainty principles for von Neumann bi-algebras
    Linzhe Huang, Zhengwei Liu, Jinsong Wu
    http://arxiv.org/abs/2107.09057v1

    • [math.OC]Asymptotic Escape of Spurious Critical Points on the Low-rank Matrix Manifold
    Thomas Y. Hou, Zhenzhen Li, Ziyun Zhang
    http://arxiv.org/abs/2107.09207v1

    • [math.ST]Directional testing for high-dimensional multivariate normal distributions
    Caizhu Huang, Claudia Di Caterina, Nicola Sartori
    http://arxiv.org/abs/2107.09418v1

    • [math.ST]Estimation of a regression function on a manifold by fully connected deep neural networks
    Michael Kohler, Sophie Langer, Ulrich Reif
    http://arxiv.org/abs/2107.09532v1

    • [math.ST]Generalized maximum likelihood estimation of the mean of parameters of mixtures, with applications to sampling
    Eitan Greenshtein, Ya’acov Ritov
    http://arxiv.org/abs/2107.09296v1

    • [math.ST]Multi-Normex Distributions for the Sum of Random Vectors. Rates of Convergence
    Marie Kratz, Evgeny Prokopenko
    http://arxiv.org/abs/2107.09409v1

    • [math.ST]On Estimating Rank-One Spiked Tensors in the Presence of Heavy Tailed Errors
    Arnab Auddy, Ming Yuan
    http://arxiv.org/abs/2107.09660v1

    • [math.ST]On some information-theoretic aspects of non-linear statistical inverse problems
    Richard Nickl, Gabriel Paternain
    http://arxiv.org/abs/2107.09488v1

    • [math.ST]Record-Based Transmuted Generalized Linear Exponential Distribution with Increasing, Decreasing and Bathtub Shaped Failure Rates
    M. Arshad, M. Khetan, V. Kumar, A. K. Pathak
    http://arxiv.org/abs/2107.09316v1

    • [math.ST]The Completion of Covariance Kernels
    Kartik G. Waghmare, Victor M. Panaretos
    http://arxiv.org/abs/2107.07350v2

    • [math.ST]The Smoking Gun: Statistical Theory Improves Neural Network Estimates
    Alina Braun, Michael Kohler, Sophie Langer, Harro Walk
    http://arxiv.org/abs/2107.09550v1

    • [physics.flu-dyn]Hybrid neural network reduced order modelling for turbulent flows with geometric parameters
    Matteo Zancanaro, Markus Mrosek, Giovanni Stabile, Carsten Othmer, Gianluigi Rozza
    http://arxiv.org/abs/2107.09591v1

    • [physics.soc-ph]On node ranking in graphs
    Ekaterina Dudkina, Michelangelo Bin, Jane Breen, Emanuele Crisostomi, Pietro Ferraro, Steve Kirkland, Jakub Marecek, Roderick Murray-Smith, Thomas Parisini, Lewi Stone, Serife Yilmaz, Robert Shorten
    http://arxiv.org/abs/2107.09487v1

    • [q-fin.CP]AI in Finance: Challenges, Techniques and Opportunities
    Longbing Cao
    http://arxiv.org/abs/2107.09051v1

    • [q-fin.ST]Stock price prediction using BERT and GAN
    Priyank Sonkiya, Vikas Bajpai, Anukriti Bansal
    http://arxiv.org/abs/2107.09055v1

    • [q-fin.TR]Order Book Queue Hawkes-Markovian Modeling
    Philip Protter, Qianfan Wu, Shihao Yang
    http://arxiv.org/abs/2107.09629v1

    • [quant-ph]Sample Complexity of Learning Quantum Circuits
    Haoyuan Cai, Qi Ye, Dong-Ling Deng
    http://arxiv.org/abs/2107.09078v1

    • [stat.AP]A Comparison of Value-Added Models for School Accountability
    George Leckie, Lucy Prior
    http://arxiv.org/abs/2107.09410v1

    • [stat.AP]A Non-ergodic Spectral Acceleration Ground Motion Model for California Developed with Random Vibration Theory
    Grigorios Lavrentiadis, Norman A. Abrahamson
    http://arxiv.org/abs/2107.09125v1

    • [stat.AP]BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data
    Meini Tang, Chee-Ming Ting, Hernando Ombao
    http://arxiv.org/abs/2107.09160v1

    • [stat.AP]Pooled testing to isolate infected individuals
    Matthew Aldridge
    http://arxiv.org/abs/2107.09633v1

    • [stat.AP]Study of the Parent-of-origin effect in monogenic diseases with variable age of onset. Application on ATTRv
    Flora Alarcon, Violaine Planté-Bordeneuve, Gregory Nuel
    http://arxiv.org/abs/2107.09365v1

    • [stat.CO]JAGS, NIMBLE, Stan: a detailed comparison among Bayesian MCMC software
    Mario Beraha, Daniele Falco, Alessandra Guglielmi
    http://arxiv.org/abs/2107.09357v1

    • [stat.ME]Accounting for spatial confounding in epidemiological studies with individual-level exposures: An exposure-penalized spline approach
    Jennifer F. Bobb, Maricela F. Cruz, Stephen J. Mooney, Adam Drewnowski, David Arterburn, Andrea J. Cook
    http://arxiv.org/abs/2107.08072v1

    • [stat.ME]Adaptively Sampling via Regional Variance-Based Sensitivities
    Brian W. Bush, Joanne Wendelberger, Rebecca Hanes
    http://arxiv.org/abs/2107.09538v1

    • [stat.ME]Conditional Wasserstein Barycenters and Interpolation/Extrapolation of Distributions
    Jianing Fan, Hans-Georg Müller
    http://arxiv.org/abs/2107.09218v1

    • [stat.ME]Diagnosis of model-structural errors with a sliding time-window Bayesian analysis
    Han-Fang Hsueh, Anneli Guthke, Thomas Wöhling, Wolfgang Nowak
    http://arxiv.org/abs/2107.09399v1

    • [stat.ME]Inference for Change Points in High Dimensional Mean Shift Models
    Abhishek Kaul, George Michailidis
    http://arxiv.org/abs/2107.09150v1

    • [stat.ME]Kpop: A kernel balancing approach for reducing specification assumptions in survey weighting
    Erin Hartman, Chad Hazlett, Ciara Sterbenz
    http://arxiv.org/abs/2107.08075v1

    • [stat.ME]Moving towards practical user-friendly synthesis: Scalable synthetic data methods for large confidential administrative databases using saturated count models
    James Jackson, Robin Mitra, Brian Francis, Iain Dove
    http://arxiv.org/abs/2107.08062v1

    • [stat.ME]Sparse composite likelihood selection
    Claudia Di Caterina, Davide Ferrari
    http://arxiv.org/abs/2107.09586v1

    • [stat.ML]A Bayesian Approach to Invariant Deep Neural Networks
    Nikolaos Mourdoukoutas, Marco Federici, Georges Pantalos, Mark van der Wilk, Vincent Fortuin
    http://arxiv.org/abs/2107.09301v1

    • [stat.ML]Adaptive wavelet distillation from neural networks through interpretations
    Wooseok Ha, Chandan Singh, Francois Lanusse, Eli Song, Song Dang, Kangmin He, Srigokul Upadhyayula, Bin Yu
    http://arxiv.org/abs/2107.09145v1

    • [stat.ML]An induction proof of the backpropagation algorithm in matrix notation
    Dirk Ostwald, Franziska Usée
    http://arxiv.org/abs/2107.09384v1

    • [stat.ML]Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression
    William T. Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick
    http://arxiv.org/abs/2107.09194v1

    • [stat.ML]Canonical Polyadic Decomposition and Deep Learning for Machine Fault Detection
    Frusque Gaetan, Michau Gabriel, Fink Olga
    http://arxiv.org/abs/2107.09519v1

    • [stat.ML]High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids
    Liang Ding, Rui Tuo, Xiaowei Zhang
    http://arxiv.org/abs/2107.08595v2

    • [stat.ML]Reward-Weighted Regression Converges to a Global Optimum
    Miroslav Štrupl, Francesco Faccio, Dylan R. Ashley, Rupesh Kumar Srivastava, Jürgen Schmidhuber
    http://arxiv.org/abs/2107.09088v1