今日学术视野(2021.11.4) - 《爱可可老师分享》

astro-ph.GA - 星系天体物理学
astro-ph.IM - 仪器仪表和天体物理学方法
cs.AI - 人工智能
cs.CL - 计算与语言
cs.CR - 加密与安全
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DC - 分布式、并行与集群计算
cs.GT - 计算机科学与博弈论
cs.HC - 人机接口
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.MA - 多代理系统
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
eess.AS - 语音处理
eess.IV - 图像与视频处理
eess.SY - 系统和控制
hep-th - 高能物理理论
math.OC - 优化与控制
math.ST - 统计理论
physics.ao-ph - 大气和海洋物理
physics.geo-ph - 地球物理学
physics.optics - 光学
physics.soc-ph - 物理学与社会
q-bio.NC - 神经元与认知
q-fin.ST - 统计金融学
quant-ph - 量子物理
stat.AP - 应用统计
stat.ME - 统计方法论
stat.ML - (统计)机器学习

• [astro-ph.GA]Robustness of deep learning algorithms in astronomy — galaxy morphology studies
• [astro-ph.IM]Realistic galaxy image simulation via score-based generative models
• [cs.AI]Classification of Goods Using Text Descriptions With Sentences Retrieval
• [cs.AI]Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification
• [cs.AI]Envelope Imbalance Learning Algorithm based on Multilayer Fuzzy C-means Clustering and Minimum Interlayer discrepancy
• [cs.AI]Graph Tree Deductive Networks
• [cs.AI]Improved Loss Function-Based Prediction Method of Extreme Temperatures in Greenhouses
• [cs.AI]Instructive artificial intelligence (AI) for human training, assistance, and explainability
• [cs.AI]Learning to Explore by Reinforcement over High-Level Options
• [cs.AI]Modeling and Automating Public Announcement Logic with Rela-tivized Common Knowledge as a Fragment of HOL in LogiKEy
• [cs.AI]Teaching Fairness, Accountability, Confidentiality, and Transparency in Artificial Intelligence through the Lens of Reproducibility
• [cs.CL]A Review of Dialogue Systems: From Trained Monkeys to Stochastic Parrots
• [cs.CL]ASMDD: Arabic Speech Mispronunciation Detection Dataset
• [cs.CL]Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Tasks
• [cs.CL]Assessing Effectiveness of Using Internal Signals for Check-Worthy Claim Identification in Unlabeled Data for Automated Fact-Checking
• [cs.CL]Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Model
• [cs.CL]Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP
• [cs.CL]HydraText: Multi-objective Optimization for Adversarial Textual Attack
• [cs.CL]Identifying causal associations in tweets using deep learning: Use case on diabetes-related tweets from 2017-2021
• [cs.CL]Improving Classifier Training Efficiency for Automatic Cyberbullying Detection with Feature Density
• [cs.CL]Integrating Pretrained Language Model for Dialogue Policy Learning
• [cs.CL]LMdiff: A Visual Diff Tool to Compare Language Models
• [cs.CL]Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey
• [cs.CL]Sequence Transduction with Graph-based Supervision
• [cs.CL]Switch Point biased Self-Training: Re-purposing Pretrained Models for Code-Switching
• [cs.CL]System Combination for Grammatical Error Correction Based on Integer Programming
• [cs.CL]Towards text-based phishing detection
• [cs.CL]UQuAD1.0: Development of an Urdu Question Answering Training Data for Machine Reading Comprehension
• [cs.CL]Zero-Shot Translation using Diffusion Models
• [cs.CR]A Comparative Analysis of Machine Learning Algorithms for Intrusion Detection in Edge-Enabled IoT Networks
• [cs.CR]Knowledge Cross-Distillation for Membership Privacy
• [cs.CV]A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods
• [cs.CV]A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation
• [cs.CV]A Tri-attention Fusion Guided Multi-modal Segmentation Network
• [cs.CV]Absolute distance prediction based on deep learning object detection and monocular depth estimation models
• [cs.CV]AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling
• [cs.CV]Attribute-Based Deep Periocular Recognition: Leveraging Soft Biometrics to Improve Periocular Recognition
• [cs.CV]Boundary Distribution Estimation to Precise Object Detection
• [cs.CV]CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds
• [cs.CV]Can Vision Transformers Perform Convolution?
• [cs.CV]Detect-and-Segment: a Deep Learning Approach to Automate Wound Image Segmentation
• [cs.CV]Distilling Object Detectors with Feature Richness
• [cs.CV]Estimating 3D Motion and Forces of Human-Object Interactions from Internet Videos
• [cs.CV]Evaluation of Human and Machine Face Detection using a Novel Distinctive Human Appearance Dataset
• [cs.CV]Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic Perspective
• [cs.CV]Gradient Frequency Modulation for Visually Explaining Video Understanding Models
• [cs.CV]HHP-Net: A light Heteroscedastic neural network for Head Pose estimation with uncertainty
• [cs.CV]HRViT: Multi-Scale High-Resolution Vision Transformer
• [cs.CV]HRViT: Multi-Scale High-Resolution Vision Transformer
• [cs.CV]Human Attention in Fine-grained Classification
• [cs.CV]Improving Contrastive Learning on Imbalanced Seed Data via Open-World Sampling
• [cs.CV]Joint Detection of Motion Boundaries and Occlusions
• [cs.CV]Livestock Monitoring with Transformer
• [cs.CV]Masking Modalities for Cross-modal Video Retrieval
• [cs.CV]MixFace: Improving Face Verification Focusing on Fine-grained Conditions
• [cs.CV]Neural Scene Flow Prior
• [cs.CV]PatchGame: Learning to Signal Mid-level Patches in Referential Games
• [cs.CV]Personalized One-Shot Lipreading for an ALS Patient
• [cs.CV]PolyTrack: Tracking with Bounding Polygons
• [cs.CV]Recognizing Families In the Wild (RFIW): The 5th Edition
• [cs.CV]Relational Self-Attention: What’s Missing in Attention for Video Understanding
• [cs.CV]Rethinking the Knowledge Distillation From the Perspective of Model Calibration
• [cs.CV]Sign-to-Speech Model for Sign Language Understanding: A Case Study of Nigerian Sign Language
• [cs.CV]StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN
• [cs.CV]Top1 Solution of QQ Browser 2021 Ai Algorithm Competition Track 1 : Multimodal Video Similarity
• [cs.CV]Using Synthetic Images To Uncover Population Biases In Facial Landmarks Detection
• [cs.CY]AI Ethics Statements — Analysis and lessons learnt from NeurIPS Broader Impact Statements
• [cs.CY]AI Ethics Statements — Analysis and lessons learnt from NeurIPS Broader Impact Statements
• [cs.CY]Location inference on social media data for agile monitoring of public health crises: An application to opioid use and abuse during the Covid-19 pandemic
• [cs.CY]On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services
• [cs.CY]Real-time Forecasting of Dockless Scooter-Sharing Demand: A Context-Aware Spatio-Temporal Multi-Graph Convolutional Network Approach
• [cs.DC]FedFly: Towards Migration in Edge-based Distributed Federated Learning
• [cs.DC]Implicit Model Specialization through DAG-based Decentralized Federated Learning
• [cs.DC]Towards Enabling I/O Awareness in Task-based Programming Models
• [cs.GT]Rational Agreement in the Presence of Crash Faults
• [cs.GT]Strategyproof and Proportionally Fair Facility Location
• [cs.HC]Hierarchical Decision Ensembles- An inferential framework for uncertain Human-AI collaboration in forensic examinations
• [cs.HC]UnProjection: Leveraging Inverse-Projections for Visual Analytics of High-Dimensional Data
• [cs.IR]Enhancing Top-N Item Recommendations by Peer Collaboration
• [cs.IR]Explaining Documents’ Relevance to Search Queries
• [cs.IT]Is RIS-Aided Massive MIMO Promising with ZF Detectors and Imperfect CSI?
• [cs.IT]Physical Channel Modeling for RIS-Empowered Wireless Networks in Sub-6 GHz Bands
• [cs.IT]The Secrecy Gain of Formally Unimodular Lattices on the Gaussian Wiretap Channel
• [cs.IT]Universal Path Gain Laws for Common Wireless Communication Environments
• [cs.LG]Arch-Net: Model Distillation for Architecture Agnostic Model Deployment
• [cs.LG]Bounds all around: training energy-based models with bidirectional bounds
• [cs.LG]Brain dynamics via Cumulative Auto-Regressive Self-Attention
• [cs.LG]Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm
• [cs.LG]Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces
• [cs.LG]Constructing Neural Network-Based Models for Simulating Dynamical Systems
• [cs.LG]DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks
• [cs.LG]Data-Driven System Identification of 6-DoF Ship Motion in Waves with Neural Networks
• [cs.LG]Deep neural networks as nested dynamical systems
• [cs.LG]DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method
• [cs.LG]Designing Inherently Interpretable Machine Learning Models
• [cs.LG]Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence
• [cs.LG]Elucidating Noisy Data via Uncertainty-Aware Robust Learning
• [cs.LG]FedGraph: Federated Graph Learning with Intelligent Sampling
• [cs.LG]Fitness Landscape Footprint: A Framework to Compare Neural Architecture Search Problems
• [cs.LG]Human-Level Control without Server-Grade Hardware
• [cs.LG]Investigating the locality of neural network training dynamics
• [cs.LG]Kernel Deformed Exponential Families for Sparse Continuous Attention
• [cs.LG]Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics
• [cs.LG]Learning to Operate an Electric Vehicle Charging Station Considering Vehicle-grid Integration
• [cs.LG]Likelihood-Free Inference in State-Space Models with Unknown Dynamics
• [cs.LG]LogAvgExp Provides a Principled and Performant Global Pooling Operator
• [cs.LG]LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision
• [cs.LG]Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
• [cs.LG]Low-Rank+Sparse Tensor Compression for Neural Networks
• [cs.LG]Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks
• [cs.LG]Meta-Learning to Improve Pre-Training
• [cs.LG]Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones
• [cs.LG]Modelling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives
• [cs.LG]Multi network InfoMax: A pre-training method involving graph convolutional networks
• [cs.LG]MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks
• [cs.LG]Nested Multiple Instance Learning with Attention Mechanisms
• [cs.LG]Nonstochastic Bandits and Experts with Arm-Dependent Delays
• [cs.LG]OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression
• [cs.LG]One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
• [cs.LG]Practical and Light-weight Secure Aggregation for Federated Submodel Learning
• [cs.LG]Predicting the Location of Bicycle-sharing Stations using OpenStreetMap Data
• [cs.LG]Privacy-Preserving Communication-Efficient Federated Multi-Armed Bandits
• [cs.LG]Procedural Generalization by Planning with Self-Supervised World Models
• [cs.LG]Provably efficient, succinct, and precise explanations
• [cs.LG]Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems
• [cs.LG]Robust Federated Learning via Over-The-Air Computation
• [cs.LG]Sig-Wasserstein GANs for Time Series Generation
• [cs.LG]Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks
• [cs.LG]Spatio-Temporal Variational Gaussian Processes
• [cs.LG]Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning
• [cs.LG]Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge
• [cs.LG]Time Series Comparisons in Deep Space Network
• [cs.LG]Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds
• [cs.LG]Transformers for prompt-level EMA non-response prediction
• [cs.LG]Understanding Entropic Regularization in GANs
• [cs.LG]Unintended Selection: Persistent Qualification Rate Disparities and Interventions
• [cs.LG]Variational message passing (VMP) applied to LDA
• [cs.LG]WaveSense: Efficient Temporal Convolutions with Spiking Neural Networks for Keyword Spotting
• [cs.LG]Word embeddings for topic modeling: an application to the estimation of the economic policy uncertainty index
• [cs.MA]ArchABM: an agent-based simulator of human interaction with the built environment. $今日学术视野(2021.11.4) - 图1$ and viral load analysis for indoor air quality
• [cs.NI]OnSlicing: Online End-to-End Network Slicing with Reinforcement Learning
• [cs.RO]A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policies
• [cs.RO]A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitives
• [cs.RO]A Minmax Utilization Algorithm for Network Traffic Scheduling of Industrial Robots
• [cs.RO]Differential Flatness and Flatness Inspired Control of Aerial Manipulators based on Lagrangian Reduction
• [cs.RO]Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels
• [cs.RO]Household Cloth Object Set: Fostering Benchmarking in Deformable Object Manipulation
• [cs.RO]Learning Eye-in-Hand Camera Calibration from a Single Image
• [cs.RO]Learning Robotic Ultrasound Scanning Skills via Human Demonstrations and Guided Explorations
• [cs.RO]SEED: Series Elastic End Effectors in 6D for Visuotactile Tool Use
• [cs.RO]Safe Online Gain Optimization for Variable Impedance Control
• [cs.RO]Simulation of Parallel-Jaw Grasping using Incremental Potential Contact Models
• [cs.RO]Trajectory Prediction with Graph-based Dual-scale Context Fusion
• [cs.SD]Evaluating robustness of You Only Hear Once(YOHO) Algorithm on noisy audios in the VOICe Dataset
• [cs.SD]Learning To Generate Piano Music With Sustain Pedals
• [cs.SD]RefineGAN: Universally Generating Waveform Better than Ground Truth with Highly Accurate Pitch and Intensity Responses
• [cs.SD]Synthesizing Speech from Intracranial Depth Electrodes using an Encoder-Decoder Framework
• [cs.SE]Do Names Echo Semantics? A Large-Scale Study of Identifiers Used in C++’s Named Casts
• [cs.SE]iCallee: Recovering Call Graphs for Binaries
• [cs.SI]A Network Science Perspective to Personalized Learning
• [cs.SI]Game of Life on Graphs
• [cs.SI]Impact of network topology on efficiency of proximity measures for community detection
• [cs.SI]Measuring and utilizing temporal network dissimilarity
• [cs.SI]Network Clustering for Latent State and Changepoint Detection
• [cs.SI]Overlapping and nonoverlapping models
• [cs.SI]Quality change: norm or exception? Measurement, Analysis and Detection of Quality Change in Wikipedia
• [eess.AS]Cross-lingual Transfer for Speech Processing using Acoustic Language Similarity
• [eess.AS]Recent Advances in End-to-End Automatic Speech Recognition
• [eess.IV]Accounting for Dependencies in Deep Learning Based Multiple Instance Learning for Whole Slide Imaging
• [eess.IV]Comparing Bayesian Models for Organ Contouring in Headand Neck Radiotherapy
• [eess.IV]Comprehensive and Clinically Accurate Head and Neck Organs at Risk Delineation via Stratified Deep Learning: A Large-scale Multi-Institutional Study
• [eess.IV]Constructing High-Order Signed Distance Maps from Computed Tomography Data with Application to Bone Morphometry
• [eess.IV]Explainable Medical Image Segmentation via Generative Adversarial Networks and Layer-wise Relevance Propagation
• [eess.IV]Federated Split Vision Transformer for COVID-19CXR Diagnosis using Task-Agnostic Training
• [eess.IV]ISP-Agnostic Image Reconstruction for Under-Display Cameras
• [eess.IV]Out of distribution detection for skin and malaria images
• [eess.IV]PointNu-Net: Simultaneous Multi-tissue Histology Nuclei Segmentation and Classification in the Clinical Wild
• [eess.IV]Progressive observation of Covid-19 vaccination effects on skin-cellular structures by use of Intelligent Laser Speckle Classification (ILSC)
• [eess.IV]Sub-cortical structure segmentation database for young population
• [eess.SY]OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets
• [hep-th]Learning Size and Shape of Calabi-Yau Spaces
• [math.OC]A comparison of mixed-variables Bayesian optimization approaches
• [math.OC]Minimax Optimization: The Case of Convex-Submodular
• [math.ST]Asymptotic in a class of network models with sub-Gamma perturbations
• [math.ST]Detecting Whether a Stochastic Process is Finitely Expressed in a Basis
• [physics.ao-ph]AIRCC-Clim: a user-friendly tool for generating regional probabilistic climate change scenarios and risk measures
• [physics.geo-ph]Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modelling
• [physics.optics]Cascadable all-optical NAND gates using diffractive networks
• [physics.soc-ph]Emergence and structure of decentralised trade networks around dark web marketplaces
• [q-bio.NC]Evaluating deep transfer learning for whole-brain cognitive decoding
• [q-bio.NC]Major Depressive Disorder Recognition and Cognitive Analysis Based on Multi-layer Brain Functional Connectivity Networks
• [q-bio.NC]Recurrent neural network models for working memory of continuous variables: activity manifolds, connectivity patterns, and dynamic codes
• [q-fin.ST]Stock Price Prediction Using Time Series, Econometric, Machine Learning, and Deep Learning Models
• [quant-ph]Towards an Optimal Hybrid Algorithm for EV Charging Stations Placement using Quantum Annealing and Genetic Algorithms
• [stat.AP]BayesDLMfMRI: Bayesian Matrix-Variate Dynamic Linear Models for Task-based fRMI Modeling in R
• [stat.AP]Computing with R-INLA: Accuracy and reproducibility with implications for the analysis of COVID-19 data
• [stat.ME]A framework for causal segmentation analysis with machine learning in large-scale digital experiments
• [stat.ME]A robust partial least squares approach for function-on-function regression
• [stat.ME]Adjusting for misclassification of an exposure in an individual participant data meta-analysis
• [stat.ME]An Asymptotic Analysis of Minibatch-Based Momentum Methods for Linear Regression Models
• [stat.ME]Dynamic statistical inference in massive datastreams
• [stat.ME]High-dimensional Simultaneous Inference on Non-Gaussian VAR Model via De-biased Estimator
• [stat.ME]Inference in high-dimensional online changepoint detection
• [stat.ME]Leveraging Population Outcomes to Improve the Generalization of Experimental Results
• [stat.ML]A Recommendation System to Enhance Midwives’ Capacities in Low-Income Countries
• [stat.ML]Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees
• [stat.ML]Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers
• [stat.ML]Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters
• [stat.ML]Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging
• [stat.ML]Faster Convex Lipschitz Regression via 2-block ADMM
• [stat.ML]Nearly Optimal Algorithms for Level Set Estimation
• [stat.ML]Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Applications
• [stat.ML]Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group

·····································

• [astro-ph.GA]Robustness of deep learning algorithms in astronomy — galaxy morphology studies
A. Ćiprijanović, D. Kafkes, G. N. Perdue, K. Pedro, G. Snyder, F. J. Sánchez, S. Madireddy, S. M. Wild, B. Nord
http://arxiv.org/abs/2111.00961v2

• [astro-ph.IM]Realistic galaxy image simulation via score-based generative models
Michael J. Smith, James E. Geach, Ryan A. Jackson, Nikhil Arora, Connor Stone, Stéphane Courteau
http://arxiv.org/abs/2111.01713v1

• [cs.AI]Classification of Goods Using Text Descriptions With Sentences Retrieval
Eunji Lee, Sundong Kim, Sihyun Kim, Sungwon Park, Meeyoung Cha, Soyeon Jung, Suyoung Yang, Yeonsoo Choi, Sungdae Ji, Minsoo Song, Heeja Kim
http://arxiv.org/abs/2111.01663v1

• [cs.AI]Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification
Clémence Réda, Andrea Tirinzoni, Rémy Degenne
http://arxiv.org/abs/2111.01479v1

• [cs.AI]Envelope Imbalance Learning Algorithm based on Multilayer Fuzzy C-means Clustering and Minimum Interlayer discrepancy
Fan Li, Xiaoheng Zhang, Pin Wang, Yongming Li
http://arxiv.org/abs/2111.01371v1

• [cs.AI]Graph Tree Deductive Networks
Seokjun Kim, Jaeeun Jang, Hyeoncheol Kim
http://arxiv.org/abs/2111.01431v1

• [cs.AI]Improved Loss Function-Based Prediction Method of Extreme Temperatures in Greenhouses
Liao Qu, Shuaiqi Huang, Yunsong Jia, Xiang
858
Li
http://arxiv.org/abs/2111.01366v1

• [cs.AI]Instructive artificial intelligence (AI) for human training, assistance, and explainability
Nicholas Kantack, Nina Cohen, Nathan Bos, Corey Lowman, James Everett, Timothy Endres
http://arxiv.org/abs/2111.01726v1

• [cs.AI]Learning to Explore by Reinforcement over High-Level Options
Liu Juncheng, McCane Brendan, Mills Steven
http://arxiv.org/abs/2111.01364v1

• [cs.AI]Modeling and Automating Public Announcement Logic with Rela-tivized Common Knowledge as a Fragment of HOL in LogiKEy
Christoph Benzmüller, Sebastian Reiche
http://arxiv.org/abs/2111.01654v1

• [cs.AI]Teaching Fairness, Accountability, Confidentiality, and Transparency in Artificial Intelligence through the Lens of Reproducibility
Ana Lucic, Maurits Bleeker, Sami Jullien, Samarth Bhargav, Maarten de Rijke
http://arxiv.org/abs/2111.00826v2

• [cs.CL]A Review of Dialogue Systems: From Trained Monkeys to Stochastic Parrots
Atharv Singh Patlan, Shiven Tripathi, Shubham Korde
http://arxiv.org/abs/2111.01414v1

• [cs.CL]ASMDD: Arabic Speech Mispronunciation Detection Dataset
Salah A. Aly, Abdelrahman Salah, Hesham M. Eraqi
http://arxiv.org/abs/2111.01136v1

• [cs.CL]Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Tasks
Aakanksha Naik, Jill Lehman, Carolyn Rose
http://arxiv.org/abs/2111.01340v1

• [cs.CL]Assessing Effectiveness of Using Internal Signals for Check-Worthy Claim Identification in Unlabeled Data for Automated Fact-Checking
Archita Pathak, Rohini K. Srihari
http://arxiv.org/abs/2111.01706v1

• [cs.CL]Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Model
Hind Saleh, Areej Alhothali, Kawthar Moria
http://arxiv.org/abs/2111.01515v1

• [cs.CL]Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP
Trapit Bansal, Karthick Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum
http://arxiv.org/abs/2111.01322v1

• [cs.CL]HydraText: Multi-objective Optimization for Adversarial Textual Attack
Shengcai Liu, Ning Lu, Cheng Chen, Chao Qian, Ke Tang
http://arxiv.org/abs/2111.01528v1

• [cs.CL]Identifying causal associations in tweets using deep learning: Use case on diabetes-related tweets from 2017-2021
Adrian Ahne, Vivek Khetan, Xavier Tannier, Md Imbessat Hassan Rizvi, Thomas Czernichow, Francisco Orchard, Charline Bour, Andrew Fano, Guy Fagherazzi
http://arxiv.org/abs/2111.01225v1

• [cs.CL]Improving Classifier Training Efficiency for Automatic Cyberbullying Detection with Feature Density
Juuso Eronen, Michal Ptaszynski, Fumito Masui, Aleksander Pohl, Gniewosz Leliwa, Michal Wroczynski
http://arxiv.org/abs/2111.01689v1

• [cs.CL]Integrating Pretrained Language Model for Dialogue Policy Learning
Hongru Wang, Huimin Wang, Zezhong Wang, Kam-Fai Wong
http://arxiv.org/abs/2111.01398v1

• [cs.CL]LMdiff: A Visual Diff Tool to Compare Language Models
Hendrik Strobelt, Benjamin Hoover, Arvind Satyanarayan, Sebastian Gehrmann
http://arxiv.org/abs/2111.01582v1

• [cs.CL]Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey
Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heinz, Dan Roth
http://arxiv.org/abs/2111.01243v1

• [cs.CL]Sequence Transduction with Graph-based Supervision
Niko Moritz, Takaaki Hori, Shinji Watanabe, Jonathan Le Roux
http://arxiv.org/abs/2111.01272v1

• [cs.CL]Switch Point biased Self-Training: Re-purposing Pretrained Models for Code-Switching
Parul Chopra, Sai Krishna Rallabandi, Alan W Black, Khyathi Raghavi Chandu
http://arxiv.org/abs/2111.01231v1

• [cs.CL]System Combination for Grammatical Error Correction Based on Integer Programming
Ruixi Lin, Hwee Tou Ng
http://arxiv.org/abs/2111.01465v1

• [cs.CL]Towards text-based phishing detection
Gilchan Park, Julia M. Taylor
http://arxiv.org/abs/2111.01676v1

• [cs.CL]UQuAD1.0: Development of an Urdu Question Answering Training Data for Machine Reading Comprehension
Samreen Kazi, Shakeel Khoja
http://arxiv.org/abs/2111.01543v1

• [cs.CL]Zero-Shot Translation using Diffusion Models
Eliya Nachmani, Shaked Dovrat
http://arxiv.org/abs/2111.01471v1

• [cs.CR]A Comparative Analysis of Machine Learning Algorithms for Intrusion Detection in Edge-Enabled IoT Networks
Poornima Mahadevappa, Syeda Mariam Muzammal, Raja Kumar Murugesan
http://arxiv.org/abs/2111.01383v1

• [cs.CR]Knowledge Cross-Distillation for Membership Privacy
Rishav Chourasia, Batnyam Enkhtaivan, Kunihiro Ito, Junki Mori, Isamu Teranishi, Hikaru Tsuchida
http://arxiv.org/abs/2111.01363v1

• [cs.CV]A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods
Mohammad Baradaran, Robert Bergevin
http://arxiv.org/abs/2111.01604v1

• [cs.CV]A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation
Yuan-Hao Lee, Fu-En Yang, Yu-Chiang Frank Wang
http://arxiv.org/abs/2111.01418v1

• [cs.CV]A Tri-attention Fusion Guided Multi-modal Segmentation Network
Tongxue Zhou, Su Ruan, Pierre Vera, Stéphane Canu
http://arxiv.org/abs/2111.01623v1

• [cs.CV]Absolute distance prediction based on deep learning object detection and monocular depth estimation models
Armin Masoumian, David G. F. Marei, Saddam Abdulwahab, Julian Cristiano, Domenec Puig, Hatem A. Rashwan
http://arxiv.org/abs/2111.01715v1

• [cs.CV]AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling
Alexandros Stergiou, Ronald Poppe
http://arxiv.org/abs/2111.00772v2

• [cs.CV]Attribute-Based Deep Periocular Recognition: Leveraging Soft Biometrics to Improve Periocular Recognition
Veeru Talreja, Nasser M. Nasrabadi, Matthew C. Valenti
http://arxiv.org/abs/2111.01325v1

• [cs.CV]Boundary Distribution Estimation to Precise Object Detection
Haoran Zhou, Hang Huang, Rui Zhao, Wei Wang, Qingguo Zhou
http://arxiv.org/abs/2111.01396v1

• [cs.CV]CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds
Enxu Li, Ryan Razani, Yixuan Xu, Bingbing Liu
http://arxiv.org/abs/2111.01723v1

• [cs.CV]Can Vision Transformers Perform Convolution?
Shanda Li, Xiangning Chen, Di He, Cho-Jui Hsieh
http://arxiv.org/abs/2111.01353v1

• [cs.CV]Detect-and-Segment: a Deep Learning Approach to Automate Wound Image Segmentation
Gaetano Scebba, Jia Zhang, Sabrina Catanzaro, Carina Mihai, Oliver Distler, Martin Berli, Walter Karlen
http://arxiv.org/abs/2111.01590v1

• [cs.CV]Distilling Object Detectors with Feature Richness
Zhixing Du, Rui Zhang, Ming Chang, Xishan Zhang, Shaoli Liu, Tianshi Chen, Yunji Chen
http://arxiv.org/abs/2111.00674v2

• [cs.CV]Estimating 3D Motion and Forces of Human-Object Interactions from Internet Videos
Zongmian Li, Jiri Sedlar, Justin Carpentier, Ivan Laptev, Nicolas Mansard, Josef Sivic
http://arxiv.org/abs/2111.01591v1

• [cs.CV]Evaluation of Human and Machine Face Detection using a Novel Distinctive Human Appearance Dataset
Necdet Gurkan, Jordan W. Suchow
http://arxiv.org/abs/2111.00660v2

• [cs.CV]Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic Perspective
Yuxi Li, Ning Xu, Wenjie Yang, John See, Weiyao Lin
http://arxiv.org/abs/2111.01323v1

• [cs.CV]Gradient Frequency Modulation for Visually Explaining Video Understanding Models
Xinmiao Lin, Wentao Bao, Matthew Wright, Yu Kong
http://arxiv.org/abs/2111.01215v1

• [cs.CV]HHP-Net: A light Heteroscedastic neural network for Head Pose estimation with uncertainty
Giorgio Cantarini, Federico Figari Tomenotti, Nicoletta Noceti, Francesca Odone
http://arxiv.org/abs/2111.01440v1

• [cs.CV]HRViT: Multi-Scale High-Resolution Vision Transformer
Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan
http://arxiv.org/abs/
g/abs/2111.01236v1
g/abs/2111.01236v1)

• [cs.CV]Human Attention in Fine-grained Classification
Yao Rong, Wenjia Xu, Zeynep Akata, Enkelejda Kasneci
http://arxiv.org/abs/2111.01628v1

• [cs.CV]Improving Contrastive Learning on Imbalanced Seed Data via Open-World Sampling
Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang
http://arxiv.org/abs/2111.01004v1

• [cs.CV]Joint Detection of Motion Boundaries and Occlusions
Hannah Halin Kim, Shuzhi Yu, Carlo Tomasi
http://arxiv.org/abs/2111.01261v1

• [cs.CV]Livestock Monitoring with Transformer
Bhavesh Tangirala, Ishan Bhandari, Daniel Laszlo, Deepak K. Gupta, Rajat M. Thomas, Devanshu Arya
http://arxiv.org/abs/2111.00801v2

• [cs.CV]Masking Modalities for Cross-modal Video Retrieval
Valentin Gabeur, Arsha Nagrani, Chen Sun, Karteek Alahari, Cordelia Schmid
http://arxiv.org/abs/2111.01300v1

• [cs.CV]MixFace: Improving Face Verification Focusing on Fine-grained Conditions
Junuk Jung, Sungbin Son, Joochan Park, Yongjun Park, Seonhoon Lee, Heung-Seon Oh
http://arxiv.org/abs/2111.01717v1

• [cs.CV]Neural Scene Flow Prior
Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey
http://arxiv.org/abs/2111.01253v1

• [cs.CV]PatchGame: Learning to Signal Mid-level Patches in Referential Games
Kamal Gupta, Gowthami Somepalli, Anubhav Gupta, Vinoj Jayasundara, Matthias Zwicker, Abhinav Shrivastava
http://arxiv.org/abs/2111.01785v1

• [cs.CV]Personalized One-Shot Lipreading for an ALS Patient
Bipasha Sen, Aditya Agarwal, Rudrabha Mukhopadhyay, Vinay Namboodiri, C V Jawahar
http://arxiv.org/abs/2111.01740v1

• [cs.CV]PolyTrack: Tracking with Bounding Polygons
Gaspar Faure, Hughes Perreault, Guillaume-Alexandre Bilodeau, Nicolas Saunier
http://arxiv.org/abs/2111.01606v1

• [cs.CV]Recognizing Families In the Wild (RFIW): The 5th Edition
Joseph P. Robinson, Can Qin, Ming Shao, Matthew A. Turk, Rama Chellappa, Yun Fu
http://arxiv.org/abs/2111.00598v2

• [cs.CV]Relational Self-Attention: What’s Missing in Attention for Video Understanding
Manjin Kim, Heeseung Kwon, Chunyu Wang, Suha Kwak, Minsu Cho
http://arxiv.org/abs/2111.01673v1

• [cs.CV]Rethinking the Knowledge Distillation From the Perspective of Model Calibration
Lehan Yang, Jincen Song
http://arxiv.org/abs/2111.01684v1

• [cs.CV]Sign-to-Speech Model for Sign Language Understanding: A Case Study of Nigerian Sign Language
Steven Kolawole, Opeyemi Osakuade, Nayan Saxena, Babatunde Kazeem Olorisade
http://arxiv.org/abs/2111.00995v2

• [cs.CV]StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN
Min Jin Chong, Hsin-Ying Lee, David Forsyth
http://arxiv.org/abs/2111.01619v1

• [cs.CV]Top1 Solution of QQ Browser 2021 Ai Algorithm Competition Track 1 : Multimodal Video Similarity
Zhuoran Ma, Majing Lou, Xuan Ouyang
http://arxiv.org/abs/2111.01677v1

• [cs.CV]Using Synthetic Images To Uncover Population Biases In Facial Landmarks Detection
Ran Shadmi, Jonathan Laserson, Gil Elbaz
http://arxiv.org/abs/2111.01683v1

• [cs.CY]AI Ethics Statements — Analysis and lessons learnt from NeurIPS Broader Impact Statements
Carolyn Ashurst, Emmie Hine, Paul Sedille, Alexis Carlier
http://arxiv.org/abs/2111.01705v1

• [cs.CY]Location inference on social media data for agile monitoring of public health crises: An application to opioid use and abuse during the Covid-19 pandemic
Angela E. Kilby, Charlie Denhart
http://arxiv.org/abs/2111.01778v1

• [cs.CY]On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services
Eren Kurshan, Jiahao Chen, Victor Storchan, Hongda Shen
http://arxiv.org/abs/2111.01306v1

• [cs.CY]Real-time Forecasting of Dockless Scooter-Sharing Demand: A Context-Aware Spatio-Temporal Multi-Graph Convolutional Network Approach
Yiming Xu, Mudit Paliwal, Xilei Zhao
http://arxiv.org/abs/2111.01355v1

• [cs.DC]FedFly: Towards Migration in Edge-based Distributed Federated Learning
Rehmat Ullah, Di Wu, Paul Harvey, Peter Kilpatrick, Ivor Spence, Blesson Varghese
http://arxiv.org/abs/2111.01516v1

• [cs.DC]Implicit Model Specialization through DAG-based Decentralized Federated Learning
Jossekin Beilharz, Bjarne Pfitzner, Robert Schmid, Paul Geppert, Bernd Arnrich, Andreas Polze
http://arxiv.org/abs/2111.01257v1

• [cs.DC]Towards Enabling I/O Awareness in Task-based Programming Models
Hatem Elshazly, Jorge Ejarque, Francesc Lordan, Rosa M. Badia
http://arxiv.org/abs/2111.01504v1

• [cs.GT]Rational Agreement in the Presence of Crash Faults
Alejandro Ranchal-Pedrosa, Vincent Gramoli
http://arxiv.org/abs/2111.01425v1

• [cs.GT]Strategyproof and Proportionally Fair Facility Location
Haris Aziz, Alexander Lam, Barton E. Lee, Toby Walsh
http://arxiv.org/abs/2111.01566v1

• [cs.HC]Hierarchical Decision Ensembles- An inferential framework for uncertain Human-AI collaboration in forensic examinations
Ganesh Krishnan, Heike Hofmann
http://arxiv.org/abs/2111.01131v1

• [cs.HC]UnProjection: Leveraging Inverse-Projections for Visual Analytics of High-Dimensional Data
Mateus Espadoto, Gabriel Appleby, Ashley Suh, Dylan Cashman, Mingwei Li, Carlos Scheidegger, Erik W Anderson, Remco Chang, Alexandru C Telea
http://arxiv.org/abs/2111.01744v1

• [cs.IR]Enhancing Top-N Item Recommendations by Peer Collaboration
Yang Sun, Fajie Yuan, Min Yang, Alexandros Karatzoglou, Shen Li, Xiaoyan Zhao
http://arxiv.org/abs/2111.00429v2

• [cs.IR]Explaining Documents’ Relevance to Search Queries
Razieh Rahimi, Youngwoo Kim, Hamed Zamani, James Allan
http://arxiv.org/abs/2111.01314v1

• [cs.IT]Is RIS-Aided Massive MIMO Promising with ZF Detectors and Imperfect CSI?
Kangda Zhi, Cunhua Pan, Gui Zhou, Hong Ren, Maged Elkashlan, Robert Schober
http://arxiv.org/abs/2111.01585v1

• [cs.IT]Physical Channel Modeling for RIS-Empowered Wireless Networks in Sub-6 GHz Bands
Fatih Kilinc, Ibrahim Yildirim, Ertugrul Basar
http://arxiv.org/abs/2111.01537v1

• [cs.IT]The Secrecy Gain of Formally Unimodular Lattices on the Gaussian Wiretap Channel
Maiara F. Bollauf, Hsuan-Yin Lin, Øyvind Ytrehus
http://arxiv.org/abs/2111.01439v1

• [cs.IT]Universal Path Gain Laws for Common Wireless Communication Environments
Dmitry Chizhik, Jinfeng Du, Reinaldo A. Valenzuela
http://arxiv.org/abs/2111.01758v1

• [cs.LG]Arch-Net: Model Distillation for Architecture Agnostic Model Deployment
Weixin Xu, Zipeng Feng, Shuangkang Fang, Song Yuan, Yi Yang, Shuchang Zhou
http://arxiv.org/abs/2111.01135v1

• [cs.LG]Bounds all around: training energy-based models with bidirectional bounds
Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
http://arxiv.org/abs/2111.00929v2

• [cs.LG]Brain dynamics via Cumulative Auto-Regressive Self-Attention
Usman Mahmood, Zening Fu, Vince Calhoun, Sergey Plis
http://arxiv.org/abs/2111.01271v1

• [cs.LG]Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm
Yuheng Bu, Gholamali Aminian, Laura Toni, Miguel Rodrigues, Gregory Wornell
http://arxiv.org/abs/2111.01635v1

• [cs.LG]Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces
Aryan Deshwal, Janardhan Rao Doppa
http://arxiv.org/abs/2111.01186v1

• [cs.LG]Constructing Neural Network-Based Models for Simulating Dynamical Systems
Christian Møldrup Legaard, Thomas Schranz, Gerald Schweiger, Ján Drgoňa, Basak Falay, Cláudio Gomes, Alexandros Iosifidis, Mahdi Abkar, Peter Gorm Larsen
http://arxiv.org/abs/2111.01495v1

• [cs.LG]DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks
Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad, Shilpa Rao
http://arxiv.org/abs/2111.01482v1

• [cs.LG]Data-Driven System Identification of 6-DoF Ship Motion in Waves with Neural Networks
Kevin M. Silva, Kevin J. Maki
http://arxiv.org/abs/2111.01773v1

• [cs.LG]Deep neural networks as nested dynamical systems
David I. Spivak, Timothy Hosgood
http://arxiv.org/abs/2111.01297v1

• [cs.LG]DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method
Zhongjian Wang, Jack Xin, Zhiwen Zhang
http://arxiv.org/abs/2111.01356v1

• [cs.LG]Designing Inherently Interpretable Machine Learning Models
Agus Sudjianto, Aijun Zhang
http://arxiv.org/abs/2111.01743v1

• [cs.LG]Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence
Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis
http://arxiv.org/abs/2111.01177v1

• [cs.LG]Elucidating Noisy Data via Uncertainty-Aware Robust Learning
Jeongeun Park, Seungyoun Shin, Sangheum Hwang, Sungjoon Choi
http://arxiv.org/abs/2111.01632v1

• [cs.LG]FedGraph: Federated Graph Learning with Intelligent Sampling
Fahao Chen, Peng Li, Toshiaki Miyazaki, Celimuge Wu
http://arxiv.org/abs/2111.01370v1

• [cs.LG]Fitness Landscape Footprint: A Framework to Compare Neural Architecture Search Problems
Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu
http://arxiv.org/abs/2111.01584v1

• [cs.LG]Human-Level Control without Server-Grade Hardware
Brett Daley, Christopher Amato
http://arxiv.org/abs/2111.01264v1

• [cs.LG]Investigating the locality of neural network training dynamics
Soham Dan, Phanideep Gampa, Anirbit Mukherjee
http://arxiv.org/abs/2111.01166v1

• [cs.LG]Kernel Deformed Exponential Families for Sparse Continuous Attention
Alexander Moreno, Supriya Nagesh, Zhenke Wu, Walter Dempsey, James M. Rehg
http://arxiv.org/abs/2111.01222v1

• [cs.LG]Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics
Matthias Weissenbacher, Samarth Sinha, Animesh Garg, Yoshinobu Kawahara
http://arxiv.org/abs/2111.01365v1

• [cs.LG]Learning to Operate an Electric Vehicle Charging Station Considering Vehicle-grid Integration
Zuzhao Ye, Yuanqi Gao, Nanpeng Yu
http://arxiv.org/abs/2111.01294v1

• [cs.LG]Likelihood-Free Inference in State-Space Models with Unknown Dynamics
Alexander Aushev, Thong Tran, Henri Pesonen, Andrew Howes, Samuel Kaski
http://arxiv.org/abs/2111.01555v1

• [cs.LG]LogAvgExp Provides a Principled and Performant Global Pooling Operator
Scott C. Lowe, Thomas Trappenberg, Sageev Oore
http://arxiv.org/abs/2111.01742v1

• [cs.LG]LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision
Thorsten Wittkopp, Philipp Wiesner, Dominik Scheinert, Alexander Acker
http://arxiv.org/abs/2111.01657v1

• [cs.LG]Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
Prateek Yadav, Peter Hase, Mohit Bansal
http://arxiv.org/abs/2111.01235v1

• [cs.LG]Low-Rank+Sparse Tensor Compression for Neural Networks
Cole Hawkins, Haichuan Yang, Meng Li, Liangzhen Lai, Vikas Chandra
http://arxiv.org/abs/2111.01697v1

• [cs.LG]Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks
Maksym Yatsura, Jan Hendrik Metzen, Matthias Hein
http://arxiv.org/abs/2111.01714v1

• [cs.LG]Meta-Learning to Improve Pre-Training
Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud
http://arxiv.org/abs/2111.01754v1

• [cs.LG]Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones
Yushi Bai, Rex Ying, Hongyu Ren, Jure Leskovec
http://arxiv.org/abs/2110.14923v2

• [cs.LG]Modelling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives
Hua-Liang Wei, S. A. Billings
http://arxiv.org/abs/2111.01763v1

• [cs.LG]Multi network InfoMax: A pre-training method involving graph convolutional networks
Usman Mahmood, Zening Fu, Vince Calhoun, Sergey Plis
http://arxiv.org/abs/2111.01276v1

• [cs.LG]MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks
Nicholas Hoernle, Rafael Michael Karampatsis, Vaishak Belle, Kobi Gal
http://arxiv.org/abs/2111.01564v1

• [cs.LG]Nested Multiple Instance Learning with Attention Mechanisms
Saul Fuster, Trygve Eftestøl, Kjersti Engan
http://arxiv.org/abs/2111.00947v2

• [cs.LG]Nonstochastic Bandits and Experts with Arm-Dependent Delays
Dirk van der Hoeven, Nicolò Cesa-Bianchi
http://arxiv.org/abs/2111.01589v1

• [cs.LG]OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression
Chen Zhang, Shifeng Zhang, Fabio Maria Carlucci, Zhenguo Li
http://arxiv.org/abs/2111.01662v1

• [cs.LG]One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
Bingqian Lu, Jianyi Yang, Weiwen Jiang, Yiyu Shi, Shaolei Ren
http://arxiv.org/abs/2111.01203v1

• [cs.LG]Practical and Light-weight Secure Aggregation for Federated Submodel Learning
Jamie Cui, Cen Chen, Tiandi Ye, Li Wang
http://arxiv.org/abs/2111.01432v1

• [cs.LG]Predicting the Location of Bicycle-sharing Stations using OpenStreetMap Data
Kamil Raczycki
http://arxiv.org/abs/2111.01722v1

• [cs.LG]Privacy-Preserving Communication-Efficient Federated Multi-Armed Bandits
Tan Li, Linqi Song
http://arxiv.org/abs/2111.01570v1

• [cs.LG]Procedural Generalization by Planning with Self-Supervised World Models
Ankesh Anand, Jacob Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Théophane Weber, Jessica B. Hamrick
http://arxiv.org/abs/2111.01587v1

• [cs.LG]Provably efficient, succinct, and precise explanations
Guy Blanc, Jane Lange, Li-Yang Tan
http://arxiv.org/abs/2111.01576v1

• [cs.LG]Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems
Jimmy T. H. Smith, Scott W. Linderman, David Sussillo
http://arxiv.org/abs/2111.01256v1

• [cs.LG]Robust Federated Learning via Over-The-Air Computation
Houssem Sifaou, Geoffrey Ye Li
http://arxiv.org/abs/2111.01221v1

• [cs.LG]Sig-Wasserstein GANs for Time Series Generation
Hao Ni, Lukasz Szpruch, Marc Sabate-Vidales, Baoren Xiao, Magnus Wiese, Shujian Liao
http://arxiv.org/abs/2111.01207v1

• [cs.LG]Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks
Xiang Huang, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Lei Chen, Bin Dong
http://arxiv.org/abs/2111.01394v1

• [cs.LG]Spatio-Temporal Variational Gaussian Processes
Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas
http://arxiv.org/abs/2111.01732v1

• [cs.LG]Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning
Bleema Rosenfeld, Osvaldo Simeone, Bipin Rajendran
http://arxiv.org/abs/2111.01750v1

• [cs.LG]Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge
Reda Ouhamma, Odalric Maillard, Vianney Perchet
http://arxiv.org/abs/2111.01602v1

• [cs.LG]Time Series Comparisons in Deep Space Network
Kyongsik Yun, Rishi Verma, Umaa Rebbapragada
http://arxiv.org/abs/2111.01393v1

• [cs.LG]Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds
Yujia Huang, Huan Zhang, Yuanyuan Shi, J Zico Kolter, Anima Anandkumar
http://arxiv.org/abs/2111.01395v1

• [cs.LG]Transformers for prompt-level EMA non-response prediction
Supriya Nagesh, Alexander Moreno, Stephanie M. Carpenter, Jamie Yap, Soujanya Chatterjee, Steven Lloyd Lizotte, Neng Wan, Santosh Kumar, Cho Lam, David W. Wetter, Inbal Nahum-Shani, James M. Rehg
http://arxiv.org/abs/2111.01193v1

• [cs.LG]Understanding Entropic Regularization in GANs
Daria Reshetova, Yikun Bai, Xiugang Wu, Ayfer Ozgur
http://arxiv.org/abs/2111.01387v1

• [cs.LG]Unintended Selection: Persistent Qualification Rate Disparities and Interventions
Reilly Raab, Yang Liu
http://arxiv.org/abs/2111.01201v1

• [cs.LG]Variational message passing (VMP) applied to LDA
Rebecca M. C. Taylor, Johan A. du Preez
http://arxiv.org/abs/2111.01480v1

• [cs.LG]WaveSense: Efficient Temporal Convolutions with Spiking Neural Networks for Keyword Spotting
Philipp Weidel, Sadique Sheik
http://arxiv.org/abs/2111.01456v1

• [cs.LG]Word embeddings for topic modeling: an application to the estimation of the economic policy uncertainty index
Hairo U. Miranda Belmonte, Victor Muñiz-Sánchez, Francisco Corona
http://arxiv.org/abs/2111.00057v1

• [cs.MA]ArchABM: an agent-based simulator of human interaction with the built environment. $今日学术视野(2021.11.4) - 图2$ and viral load analysis for indoor air quality
Iñigo Martinez, Jan L. Bruse, Ane M. Florez-Tapia, Elisabeth Viles, Igor G. Olaizola
http://arxiv.org/abs/2111.01484v1

• [cs.NI]OnSlicing: Online End-to-End Network Slicing with Reinforcement Learning
Qiang Liu, Nakjung Choi, Tao Han
http://arxiv.org/abs/2111.01616v1

• [cs.RO]A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policies
Jan Blumenkamp, Steven Morad, Jennifer Gielis, Qingbiao Li, Amanda Prorok
http://arxiv.org/abs/2111.01777v1

• [cs.RO]A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitives
Zohar Feldman, Hanna Ziesche, Ngo Anh Vien, Dotan Di Castro
http://arxiv.org/abs/2111.01510v1

• [cs.RO]A Minmax Utilization Algorithm for Network Traffic Scheduling of Industrial Robots
Yantong Wang, Vasilis Friderikos, Sebastian Andraos
http://arxiv.org/abs/2111.01413v1

• [cs.RO]Differential Flatness and Flatness Inspired Control of Aerial Manipulators based on Lagrangian Reduction
Skylar X. Wei, Peder Harderup, Joel Burdick
http://arxiv.org/abs/2111.01302v1

• [cs.RO]Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels
Noémie Jaquier, Viacheslav Borovitskiy, Andrei Smolensky, Alexander Terenin, Tamim Asfour, Leonel Rozo
http://arxiv.org/abs/2111.01460v1

• [cs.RO]Household Cloth Object Set: Fostering Benchmarking in Deformable Object Manipulation
Irene Garcia-Camacho, Júlia Borràs, Berk Calli, Adam Norton, Guillem Alenyà
http://arxiv.org/abs/2111.01527v1

• [cs.RO]Learning Eye-in-Hand Camera Calibration from a Single Image
Eugene Valassakis, Kamil Dreczkowski, Edward Johns
http://arxiv.org/abs/2111.01245v1

• [cs.RO]Learning Robotic Ultrasound Scanning Skills via Human Demonstrations and Guided Explorations
Xutian Deng, Yiting Chen, Fei Chen, Miao Li
http://arxiv.org/abs/2111.01625v1

• [cs.RO]SEED: Series Elastic End Effectors in 6D for Visuotactile Tool Use
H. J. Terry Suh, Naveen Kuppuswamy, Tao Pang, Paul Mitiguy, Alex Alspach, Russ Tedrake
http://arxiv.org/abs/2111.01376v1

• [cs.RO]Safe Online Gain Optimization for Variable Impedance Control
Changhao Wang, Zhian Kuang, Xiang Zhang, Masayoshi Tomizuka
http://arxiv.org/abs/2111.01258v1

• [cs.RO]Simulation of Parallel-Jaw Grasping using Incremental Potential Contact Models
Chung Min Kim, Michael Danielczuk, Isabella Huang, Ken Goldberg
http://arxiv.org/abs/2111.01391v1

• [cs.RO]Trajectory Prediction with Graph-based Dual-scale Context Fusion
Lu Zhang, Peiliang Li, Jing Chen, Shaojie Shen
http://arxiv.org/abs/2111.01592v1

• [cs.SD]Evaluating robustness of You Only Hear Once(YOHO) Algorithm on noisy audios in the VOICe Dataset
Soham Tiwari, Kshitiz Lakhotia, Manjunath Mulimani
http://arxiv.org/abs/2111.01205v1

• [cs.SD]Learning To Generate Piano Music With Sustain Pedals
Joann Ching, Yi-Hsuan Yang
http://arxiv.org/abs/2111.01216v1

• [cs.SD]RefineGAN: Universally Generating Waveform Better than Ground Truth with Highly Accurate Pitch and Intensity Responses
Shengyuan Xu, Wenxiao Zhao, Jing Guo
http://arxiv.org/abs/2111.00962v2

• [cs.SD]Synthesizing Speech from Intracranial Depth Electrodes using an Encoder-Decoder Framework
Jonas Kohler, Maarten C. Ottenhoff, Sophocles Goulis, Miguel Angrick, Albert J. Colon, Louis Wagner, Simon Tousseyn, Pieter L. Kubben, Christian Herff
http://arxiv.org/abs/2111.01457v1

• [cs.SE]Do Names Echo Semantics? A Large-Scale Study of Identifiers Used in C++’s Named Casts
Constantin Cezar Petrescu, Sam Smith, Rafail Giavrimis, Santanu Kumar Dash
http://arxiv.org/abs/2111.01577v1

• [cs.SE]iCallee: Recovering Call Graphs for Binaries
Wenyu Zhu, Zhiyao Feng, Zihan Zhang, Chao Zhang, Zhijian Ou, Min Yang
http://arxiv.org/abs/2111.01415v1

• [cs.SI]A Network Science Perspective to Personalized Learning
Ralucca Gera, Akrati Saxena, D’Marie Bartolf, Simona Tick
http://arxiv.org/abs/2111.01321v1

• [cs.SI]Game of Life on Graphs
Mikhail Krechetov
http://arxiv.org/abs/2111.01780v1

• [cs.SI]Impact of network topology on efficiency of proximity measures for community detection
Rinat Aynulin
http://arxiv.org/abs/2111.01229v1

• [cs.SI]Measuring and utilizing temporal network dissimilarity
Xiu-Xiu Zhan, Chuang Liu, Zhipeng Wang, Huijuang Wang, Petter Holme, Zi-Ke Zhang
http://arxiv.org/abs/2111.01334v1

• [cs.SI]Network Clustering for Latent State and Changepoint Detection
Madeline Navarro, Genevera I. Allen, Michael Weylandt
http://arxiv.org/abs/2111.01273v1

• [cs.SI]Overlapping and nonoverlapping models
Huan Qing
http://arxiv.org/abs/2111.01392v1

• [cs.SI]Quality change: norm or exception? Measurement, Analysis and Detection of Quality Change in Wikipedia
Paramita Das, Bhanu Prakash Reddy Guda, Sasi Bhusan Seelaboyina, Soumya Sarkar, Animesh Mukherjee
http://arxiv.org/abs/2111.01496v1

• [eess.AS]Cross-lingual Transfer for Speech Processing using Acoustic Language Similarity
Peter Wu, Jiatong Shi, Yifan Zhong, Shinji Watanabe, Alan W Black
http://arxiv.org/abs/2111.01326v1

• [eess.AS]Recent Advances in End-to-End Automatic Speech Recognition
Jinyu Li
http://arxiv.org/abs/2111.01690v1

• [eess.IV]Accounting for Dependencies in Deep Learning Based Multiple Instance Learning for Whole Slide Imaging
Andriy Myronenko, Ziyue Xu, Dong Yang, Holger Roth, Daguang Xu
http://arxiv.org/abs/2111.01556v1

• [eess.IV]Comparing Bayesian Models for Organ Contouring in Headand Neck Radiotherapy
Prerak Mody, Nicolas Chaves-de-Plaza, Klaus Hildebrandt, Rene van Egmond, Huib de Ridder, Marius Staring
http://arxiv.org/abs/2111.01134v1

• [eess.IV]Comprehensive and Clinically Accurate Head and Neck Organs at Risk Delineation via Stratified Deep Learning: A Large-scale Multi-Institutional Study
Dazhou Guo, Jia Ge, Xianghua Ye, Senxiang Yan, Yi Xin, Yuchen Song, Bing-shen Huang, Tsung-Min Hung, Zhuotun Zhu, Ling Peng, Yanping Ren, Rui Liu, Gong Zhang, Mengyuan Mao, Xiaohua Chen, Zhongjie Lu, Wenxiang Li, Yuzhen Chen, Lingyun Huang, Jing Xiao, Adam P. Harrison, Le Lu, Chien-Yu Lin, Dakai Jin, Tsung-Ying Ho
http://arxiv.org/abs/2111.01544v1

• [eess.IV]Constructing High-Order Signed Distance Maps from Computed Tomography Data with Application to Bone Morphometry
Bryce A. Besler, Tannis D. Kemp, Nils D. Forkert, Steven K. Boyd
http://arxiv.org/abs/2111.01350v1

• [eess.IV]Explainable Medical Image Segmentation via Generative Adversarial Networks and Layer-wise Relevance Propagation
Awadelrahman M. A. Ahmed, Leen A. M. Ali
http://arxiv.org/abs/2111.01665v1

• [eess.IV]Federated Split Vision Transformer for COVID-19CXR Diagnosis using Task-Agnostic Training
Sangjoon Park, Gwanghyun Kim, Jeongsol Kim, Boah Kim, Jong Chul Ye
http://arxiv.org/abs/2111.01338v1

• [eess.IV]ISP-Agnostic Image Reconstruction for Under-Display Cameras
Miao Qi, Yuqi Li, Wolfgang Heidrich
http://arxiv.org/abs/2111.01511v1

• [eess.IV]Out of distribution detection for skin and malaria images
Muhammad Zaida, Shafaqat Ali, Mohsen Ali, Sarfaraz Hussein, Asma Saadia, Waqas Sultani
http://arxiv.org/abs/2111.01505v1

• [eess.IV]PointNu-Net: Simultaneous Multi-tissue Histology Nuclei Segmentation and Classification in the Clinical Wild
Kai Yao, Kaizhu Huang, Jie Sun, Amir Hussain, Curran Jude
http://arxiv.org/abs/2111.01557v1

• [eess.IV]Progressive observation of Covid-19 vaccination effects on skin-cellular structures by use of Intelligent Laser Speckle Classification (ILSC)
Ahmet Orun, Fatih Kurugollu
http://arxiv.org/abs/2111.01682v1

• [eess.IV]Sub-cortical structure segmentation database for young population
Jayanthi Sivaswamy, Alphin J Thottupattu, Mythri V, Raghav Mehta, R Sheelakumari, Chandrasekharan Kesavadas
http://arxiv.org/abs/2111.01561v1

• [eess.SY]OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets
Trager Joswig-Jones, Ahmed S. Zamzam, Kyri Baker
http://arxiv.org/abs/2111.01228v1

• [hep-th]Learning Size and Shape of Calabi-Yau Spaces
Magdalena Larfors, Andre Lukas, Fabian Ruehle, Robin Schneider
http://arxiv.org/abs/2111.01436v1

• [math.OC]A comparison of mixed-variables Bayesian optimization approaches
Jhouben Cuesta-Ramirez, Rodolphe Le Riche, Olivier Roustant, Guillaume Perrin, Cedric Durantin, Alain Gliere
http://arxiv.org/abs/2111.01533v1

• [math.OC]Minimax Optimization: The Case of Convex-Submodular
Arman Adibi, Aryan Mokhtari, Hamed Hassani
http://arxiv.org/abs/2111.01262v1

• [math.ST]Asymptotic in a class of network models with sub-Gamma perturbations
Jiaxin Guo, Haoyu Wei, Xiaoyu Lei, Jing Luo
http://arxiv.org/abs/2111.01301v1

• [math.ST]Detecting Whether a Stochastic Process is Finitely Expressed in a Basis
Neda Mohammadi, Victor M. Panaretos
http://arxiv.org/abs/2111.01542v1

• [physics.ao-ph]AIRCC-Clim: a user-friendly tool for generating regional probabilistic climate change scenarios and risk measures
Francisco Estrada, Oscar Calderón-Bustamante, Wouter Botzen, Julián A. Velasco, Richard S. J. Tol
http://arxiv.org/abs/2111.01762v1

• [physics.geo-ph]Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modelling
Samuel J. Jackson, Yufu Niu, Sojwal Manoorkar, Peyman Mostaghimi, Ryan T. Armstrong
http://arxiv.org/abs/2111.01270v1

• [physics.optics]Cascadable all-optical NAND gates using diffractive networks
Yi Luo, Deniz Mengu, Aydogan Ozcan
http://arxiv.org/abs/2111.01404v1

• [physics.soc-ph]Emergence and structure of decentralised trade networks around dark web marketplaces
Matthieu Nadini, Alberto Bracci, Abeer ElBahrawy, Philip Gradwell, Alexander Teytelboym, Andrea Baronchelli
http://arxiv.org/abs/2111.01774v1

• [q-bio.NC]Evaluating deep transfer learning for whole-brain cognitive decoding
Armin W. Thomas, Ulman Lindenberger, Wojciech Samek, Klaus-Robert Müller
http://arxiv.org/abs/2111.01562v1

• [q-bio.NC]Major Depressive Disorder Recognition and Cognitive Analysis Based on Multi-layer Brain Functional Connectivity Networks
Xiaofang Sun, Xiangwei Zheng, Yonghui Xu, Lizhen Cui, Bin Hu
http://arxiv.org/abs/2111.01351v1

• [q-bio.NC]Recurrent neural network models for working memory of continuous variables: activity manifolds, connectivity patterns, and dynamic codes
Christopher J. Cueva, Adel Ardalan, Misha Tsodyks, Ning Qian
http://arxiv.org/abs/2111.01275v1

• [q-fin.ST]Stock Price Prediction Using Time Series, Econometric, Machine Learning, and Deep Learning Models
Ananda Chatterjee, Hrisav Bhowmick, Jaydip Sen
http://arxiv.org/abs/2111.01137v1

• [quant-ph]Towards an Optimal Hybrid Algorithm for EV Charging Stations Placement using Quantum Annealing and Genetic Algorithms
Aman Chandra, Jitesh Lalwani, Babita Jajodia
http://arxiv.org/abs/2111.01622v1

• [stat.AP]BayesDLMfMRI: Bayesian Matrix-Variate Dynamic Linear Models for Task-based fRMI Modeling in R
Johnatan Cardona Jiménez
http://arxiv.org/abs/2111.01318v1

• [stat.AP]Computing with R-INLA: Accuracy and reproducibility with implications for the analysis of COVID-19 data
Kori Khan, Hengrui Luo, Wenna Xi
http://arxiv.org/abs/2111.01285v1

• [stat.ME]A framework for causal segmentation analysis with machine learning in large-scale digital experiments
Nima S. Hejazi, Wenjing Zheng, Sathya Anand
http://arxiv.org/abs/2111.01223v1

• [stat.ME]A robust partial least squares approach for function-on-function regression
Ufuk Beyaztas, Han Lin Shang
http://arxiv.org/abs/2111.01238v1

• [stat.ME]Adjusting for misclassification of an exposure in an individual participant data meta-analysis
Valentijn M. T. de Jong, Harlan Campbell, Lauren Maxwell, Thomas Jaenisch, Paul Gustafson, Thomas P. A. Debray
http://arxiv.org/abs/2111.01650v1

• [stat.ME]An Asymptotic Analysis of Minibatch-Based Momentum Methods for Linear Regression Models
Yuan Gao, Xuening Zhu, Haobo Qi, Guodong Li, Riquan Zhang, Hansheng Wang
http://arxiv.org/abs/2111.01507v1

• [stat.ME]Dynamic statistical inference in massive datastreams
Jingshen Wang, Lilun Du, Changliang Zou, Zhenke Wu
http://arxiv.org/abs/2111.01339v1

• [stat.ME]High-dimensional Simultaneous Inference on Non-Gaussian VAR Model via De-biased Estimator
Linbo Liu, Danna Zhang
http://arxiv.org/abs/2111.01382v1

• [stat.ME]Inference in high-dimensional online changepoint detection
Yudong Chen, Tengyao Wang, Richard J. Samworth
http://arxiv.org/abs/2111.01640v1

• [stat.ME]Leveraging Population Outcomes to Improve the Generalization of Experimental Results
Melody Huang, Naoki Egami, Erin Hartman, Luke Miratrix
http://arxiv.org/abs/2111.01357v1

• [stat.ML]A Recommendation System to Enhance Midwives’ Capacities in Low-Income Countries
Anna Guitart, Afsaneh Heydari, Eniola Olaleye, Jelena Ljubicic, Ana Fernández del Río, África Periáñez, Lauren Bellhouse
http://arxiv.org/abs/2111.01786v1

• [stat.ML]Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees
William J. Wilkinson, Simo Särkkä, Arno Solin
http://arxiv.org/abs/2111.01721v1

• [stat.ML]Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers
Wei Zhou, Xin He, Wei Zhong, Junhui Wang
http://arxiv.org/abs/2111.01560v1

• [stat.ML]Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters
Conor Rosato, Paul Horridge, Thomas B. Schön, Simon Maskell
http://arxiv.org/abs/2111.01409v1

• [stat.ML]Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging
Ali Hashemi, Yijing Gao, Chang Cai, Sanjay Ghosh, Klaus-Robert Müller, Srikantan S. Nagarajan, Stefan Haufe
http://arxiv.org/abs/2111.01692v1

• [stat.ML]Faster Convex Lipschitz Regression via 2-block ADMM
Ali Siahkamari, Durmus Alp Emre Acar, Christopher Liao, Kelly Geyer, Venkatesh Saligrama, Brian Kulis
http://arxiv.org/abs/2111.01348v1

• [stat.ML]Nearly Optimal Algorithms for Level Set Estimation
Blake Mason, Romain Camilleri, Subhojyoti Mukherjee, Kevin Jamieson, Robert Nowak, Lalit Jain
http://arxiv.org/abs/2111.01768v1

• [stat.ML]Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Applications
Sloan Nietert, Rachel Cummings, Ziv Goldfeld
http://arxiv.org/abs/2111.01361v1

• [stat.ML]Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group
Zhenbang Wang, Emanuel Ben-David, Martin Slawski
http://arxiv.org/abs/2111.01767v1