astro-ph.GA - 星系天体物理学
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.ET - 新兴技术
cs.HC - 人机接口
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.NE - 神经与进化计算
cs.NI - 网络和互联网体系结构
cs.RO - 机器人学
cs.SE - 软件工程
cs.SI - 社交网络与信息网络
eess.IV - 图像与视频处理
eess.SP - 信号处理
math.CO - 组合数学
math.NA - 数值分析
math.PR - 概率
math.ST - 统计理论
physics.data-an - 数据分析、 统计和概率
q-bio.NC - 神经元与认知
q-bio.QM - 定量方法
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.GA]Bayesian Inference of Globular Cluster Properties Using Distribution Functions
• [cs.AI]Artificial Intelligence Algorithms for Natural Language Processing and the Semantic Web Ontology Learning
• [cs.AI]Phy-Q: A Benchmark for Physical Reasoning
• [cs.AI]Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study
• [cs.AI]The Horn Non-Clausal Class and its Polynomiality
• [cs.CL]A Generative Approach for Mitigating Structural Biases in Natural Language Inference
• [cs.CL]A Search Engine for Discovery of Biomedical Challenges and Directions
• [cs.CL]Automatic Rule Generation for Time Expression Normalization
• [cs.CL]Contrastive Domain Adaptation for Question Answering using Limited Text Corpora
• [cs.CL]Cross-Lingual Text Classification of Transliterated Hindi and Malayalam
• [cs.CL]Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
• [cs.CL]Discretized Integrated Gradients for Explaining Language Models
• [cs.CL]Dynamic Sliding Window for Meeting Summarization
• [cs.CL]Effective Sequence-to-Sequence Dialogue State Tracking
• [cs.CL]Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience
• [cs.CL]Explaining Classes through Word Attribution
• [cs.CL]Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization
• [cs.CL]Gray Cycles of Maximum Length Related to k-Character Substitutions
• [cs.CL]How Does Adversarial Fine-Tuning Benefit BERT?
• [cs.CL]Knowledge-Grounded Dialogue with Reward-Driven Knowledge Selection
• [cs.CL]Like Article, Like Audience: Enforcing Multimodal Correlations for Disinformation Detection
• [cs.CL]Linguistic Characterization of Divisive Topics Online: Case Studies on Contentiousness in Abortion, Climate Change, and Gun Control
• [cs.CL]MELM: Data Augmentation with Masked Entity Language Modeling for Cross-lingual NER
• [cs.CL]Monolingual versus Multilingual BERTology for Vietnamese Extractive Multi-Document Summarization
• [cs.CL]Plan-then-Generate: Controlled Data-to-Text Generation via Planning
• [cs.CL]Query-Focused Extractive Summarisation for Finding Ideal Answers to Biomedical and COVID-19 Questions
• [cs.CL]Robust Retrieval Augmented Generation for Zero-shot Slot Filling
• [cs.CL]Scheduled Sampling Based on Decoding Steps for Neural Machine Translation
• [cs.CL]Semi-Supervised Exaggeration Detection of Health Science Press Releases
• [cs.CL]T3-Vis: a visual analytic framework for Training and fine-Tuning Transformers in NLP
• [cs.CL]TNNT: The Named Entity Recognition Toolkit
• [cs.CL]TREND: Trigger-Enhanced Relation-Extraction Network for Dialogues
• [cs.CL]Task-Oriented Dialogue System as Natural Language Generation
• [cs.CL]The five Is: Key principles for interpretable and safe conversational AI
• [cs.CL]Thermostat: A Large Collection of NLP Model Explanations and Analysis Tools
• [cs.CL]Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution
• [cs.CL]Unsupervised Open-Domain Question Answering
• [cs.CL]Want To Reduce Labeling Cost? GPT-3 Can Help
• [cs.CL]When Retriever-Reader Meets Scenario-Based Multiple-Choice Questions
• [cs.CL]mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset
• [cs.CR]Backdoor Attacks on Pre-trained Models by Layerwise Weight Poisoning
• [cs.CR]Beyond Model Extraction: Imitation Attack for Black-Box NLP APIs
• [cs.CR]DLPFS: The Data Leakage Prevention FileSystem
• [cs.CR]DeepTaskAPT: Insider APT detection using Task-tree based Deep Learning
• [cs.CR]EG-Booster: Explanation-Guided Booster of ML Evasion Attacks
• [cs.CR]Generalizing Weighted Trees: A Bridge from Bitcoin to GHOST
• [cs.CR]Incorporating Deception into CyberBattleSim for Autonomous Defense
• [cs.CR]Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings
• [cs.CR]Segmentation Fault: A Cheap Defense Against Adversarial Machine Learning
• [cs.CV]A Novel Dataset for Keypoint Detection of quadruped Animals from Images
• [cs.CV]AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks
• [cs.CV]Attention-based Multi-Reference Learning for Image Super-Resolution
• [cs.CV]Automatic digital twin data model generation of building energy systems from piping and instrumentation diagrams
• [cs.CV]Automatic labelling of urban point clouds using data fusion
• [cs.CV]Dead Pixel Test Using Effective Receptive Field
• [cs.CV]Deep Learning on Edge TPUs
• [cs.CV]DepthTrack : Unveiling the Power of RGBD Tracking
• [cs.CV]Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classification Model for MIDOG Challenge
• [cs.CV]Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection
• [cs.CV]End-to-End Monocular Vanishing Point Detection Exploiting Lane Annotations
• [cs.CV]Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision
• [cs.CV]InSeGAN: A Generative Approach to Segmenting Identical Instances in Depth Images
• [cs.CV]Is First Person Vision Challenging for Object Tracking?
• [cs.CV]Module-Power Prediction from PL Measurements using Deep Learning
• [cs.CV]One-shot domain adaptation for semantic face editing of real world images using StyleALAE
• [cs.CV]PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs
• [cs.CV]Pruning with Compensation: Efficient Channel Pruning for Deep Convolutional Neural Networks
• [cs.CV]Realistic Hands: A Hybrid Model for 3D Hand Reconstruction
• [cs.CV]S4-Crowd: Semi-Supervised Learning with Self-Supervised Regularisation for Crowd Counting
• [cs.CV]SMAC-Seg: LiDAR Panoptic Segmentation via Sparse Multi-directional Attention Clustering
• [cs.CV]ScatSimCLR: self-supervised contrastive learning with pretext task regularization for small-scale datasets
• [cs.CV]Scene Synthesis via Uncertainty-Driven Attribute Synchronization
• [cs.CV]Self-Calibrating Neural Radiance Fields
• [cs.CV]Self-balanced Learning For Domain Generalization
• [cs.CV]SemIE: Semantically-aware Image Extrapolation
• [cs.CV]Semi-supervised Image Classification with Grad-CAM Consistency
• [cs.CV]SimulLR: Simultaneous Lip Reading Transducer with Attention-Guided Adaptive Memory
• [cs.CV]Spectral Splitting and Aggregation Network for Hyperspectral Face Super-Resolution
• [cs.CV]Super-Resolution Appearance Transfer for 4D Human Performances
• [cs.CY]Tracing app technology: An ethical review in the COVID-19 era and directions for post-COVID-19
• [cs.CY]Why and How Governments Should Monitor AI Development
• [cs.DC]A High-Fidelity Flow Solver for Unstructured Meshes on Field-Programmable Gate Arrays
• [cs.DC]A log-linear #card=math&code=%282%2B5%2F6%29&id=gnW4r)-approximation algorithm for parallel machine scheduling with a single orthogonal resource
• [cs.DC]Building Time-Triggered Schedules for typed-DAG Tasks with alternative implementations
• [cs.DC]ExaWorks: Workflows for Exascale
• [cs.DC]PTRAIL — A python package for parallel trajectory data preprocessing
• [cs.DC]Population Protocols: Beyond Runtime Analysis
• [cs.ET]Intrinsic Spike Timing Dependent Plasticity in Stochastic Magnetic Tunnel Junctions Mediated by Heat Dynamics
• [cs.HC]ConVIScope: Visual Analytics for Exploring Patient Conversations
• [cs.IR]Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation
• [cs.IR]Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback
• [cs.IR]Zero Shot on the Cold-Start Problem: Model-Agnostic Interest Learning for Recommender Systems
• [cs.IT]Energy Minimization for IRS-aided WPCNs with Non-linear Energy Harvesting Model
• [cs.IT]Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups
• [cs.IT]Robust Symbol-Level Precoding and Passive Beamforming for IRS-Aided Communications
• [cs.IT]Spectral and Energy Efficiency of ACO-OFDM in Visible Light Communication Systems
• [cs.IT]Structural Properties of Optimal Test Channels for Gaussian Multivariate Partially Observable Distributed Sources
• [cs.IT]Successful Recovery Performance Guarantees of Noisy SOMP
• [cs.IT]Triple-Structured Compressive Sensing-based Channel Estimation for RIS-aided MU-MIMO Systems
• [cs.IT]Upper bounds on the length function for covering codes
• [cs.LG]A New Approach to Multilinear Dynamical Systems and Control
• [cs.LG]A manifold learning perspective on representation learning: Learning decoder and representations without an encoder
• [cs.LG]APS: Active Pretraining with Successor Features
• [cs.LG]Adaptive Label Smoothing To Regularize Large-Scale Graph Training
• [cs.LG]Approximation Methods for Partially Observed Markov Decision Processes (POMDPs)
• [cs.LG]Benchmarking the Accuracy and Robustness of Feedback Alignment Algorithms
• [cs.LG]Bubblewrap: Online tiling and real-time flow prediction on neural manifolds
• [cs.LG]Canoe : A System for Collaborative Learning for Neural Nets
• [cs.LG]Chi-square Loss for Softmax: an Echo of Neural Network Structure
• [cs.LG]Communication-Computation Efficient Device-Edge Co-Inference via AutoML
• [cs.LG]Deep Learning of Transferable MIMO Channel Modes for 6G V2X Communications
• [cs.LG]Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods
• [cs.LG]DoGR: Disaggregated Gaussian Regression for Reproducible Analysis of Heterogeneous Data
• [cs.LG]Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space
• [cs.LG]Fast Multi-label Learning
• [cs.LG]GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization
• [cs.LG]Heterogeneous Graph Neural Network with Multi-view Representation Learning
• [cs.LG]Learning Optimal Prescriptive Trees from Observational Data
• [cs.LG]Learning to Synthesize Programs as Interpretable and Generalizable Policies
• [cs.LG]Machine Learning Methods for Management UAV Flocks — a Survey
• [cs.LG]Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations
• [cs.LG]Medical SANSformers: Training self-supervised transformers without attention for Electronic Medical Records
• [cs.LG]Morphence: Moving Target Defense Against Adversarial Examples
• [cs.LG]Rapidly and accurately estimating brain strain and strain rate across head impact types with transfer learning and data fusion
• [cs.LG]Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning
• [cs.LG]Time Series Prediction using Deep Learning Methods in Healthcare
• [cs.LG]Towards Out-Of-Distribution Generalization: A Survey
• [cs.LG]Using a one dimensional parabolic model of the full-batch loss to estimate learning rates during training
• [cs.LG]WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU
• [cs.LG]When are Deep Networks really better than Random Forests at small sample sizes?
• [cs.NE]Spike time displacement based error backpropagation in convolutional spiking neural networks
• [cs.NI]A Hierarchical Stitching Algorithm for Coded Compressed Sensing
• [cs.NI]Latency-Redundancy Tradeoff in Distributed Read-Write Systems
• [cs.RO]A review of mobile robot motion planning methods: from classical motion planning workflows to reinforcement learning-based architectures
• [cs.RO]Autonomous Rollator: A Case Study in the Agebots Project
• [cs.RO]BotNet: A Simulator for Studying the Effects of Accurate Communication Models on Multi-agent and Swarm Control
• [cs.RO]Lane level context and hidden space characterization for autonomous driving
• [cs.RO]Learning Practically Feasible Policies for Online 3D Bin Packing
• [cs.RO]Manipulation of Camera Sensor Data via Fault Injection for Anomaly Detection Studies in Verification and Validation Activities For AI
• [cs.RO]Planning for Dexterous Ungrasping: Secure Ungrasping through Dexterous Manipulation
• [cs.RO]Riemannian Optimization for Distance Geometric Inverse Kinematics
• [cs.RO]Robotic Lime Picking by Considering Leaves as Permeable Obstacles
• [cs.RO]SURENA IV: Towards A Cost-effective Full-size Humanoid Robot for Real-world Scenarios
• [cs.RO]The Interaction Flow Editor: A New Human-Robot Interaction RapidPrototyping Interface
• [cs.RO]Through the Looking Glass: Diminishing Occlusions in Robot Vision Systems with Mirror Reflections
• [cs.SE]Towards a Common Testing Terminology for Software Engineering and Artificial Intelligence Experts
• [cs.SI]Control Scenarios for Probabilistic SIR Epidemics on Social-Connection Graphs
• [cs.SI]Modularity and Heavy-Tailed Degree Distributions
• [cs.SI]Network psychometrics and cognitive network science open new ways for detecting, understanding and tackling the complexity of math anxiety: A review
• [cs.SI]On Comparing and Enhancing Common Approaches to Network Community Detection
• [cs.SI]The emojification of sentiment on social media: Collection and analysis of a longitudinal Twitter sentiment dataset
• [eess.IV]Iterative Filter Adaptive Network for Single Image Defocus Deblurring
• [eess.IV]OARnet: Automated organs-at-risk delineation in Head and Neck CT images
• [eess.IV]Simultaneous Nuclear Instance and Layer Segmentation in Oral Epithelial Dysplasia
• [eess.IV]The Application of Convolutional Neural Networks for Tomographic Reconstruction of Hyperspectral Images
• [eess.SP]Unit-Modulus Wireless Federated Learning Via Penalty Alternating Minimization
• [math.CO]Graphs with minimum degree-based entropy
• [math.NA]An FEA surrogate model with Boundary Oriented Graph Embedding approach
• [math.PR]On the Number of Faces and Radii of Cells Induced by Gaussian Spherical Tessellations
• [math.ST]New Highly Efficient High-Breakdown Estimator of Multivariate Scatter and Location for Elliptical Distributions
• [math.ST]Uniform Consistency in Nonparametric Mixture Models
• [physics.data-an]Toward AI-enhanced online-characterization and shaping of ultrashort X-ray free-electron laser pulses
• [q-bio.NC]Astrocytes mediate analogous memory in a multi-layer neuron-astrocytic network
• [q-bio.QM]Clustering of Pain Dynamics in Sickle Cell Disease from Sparse, Uneven Samples
• [q-bio.QM]Temporal Deep Learning Architecture for Prediction of COVID-19 Cases in India
• [quant-ph]Identifying optimal cycles in quantum thermal machines with reinforcement-learning
• [quant-ph]Recent advances for quantum classifiers
• [stat.AP]A practical guide to causal discovery with cohort data
• [stat.AP]Comments on The clinical meaningfulness of a treatment’s effect on a time-to-event variable
• [stat.AP]Optimal Daily Trading of Battery Operations Using Arbitrage Spreads
• [stat.AP]Regional estimates of reproduction numbers with application to COVID-19
• [stat.CO]A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example
• [stat.ME]Comparison of cause specific rate functions of panel count data with multiple modes of recurrence
• [stat.ME]Double Machine Learning for Partially Linear Mixed-Effects Models with Repeated Measurements
• [stat.ME]Functional Data Representation with Merge Trees
• [stat.ME]On Proximal Causal Inference With Synthetic Controls
• [stat.ME]Spatial Blind Source Separation in the Presence of a Drift
• [stat.ME]Variable Selection in Regression Model with AR(p) Error Terms Based on Heavy Tailed Distributions
• [stat.ML]A Subsampling Based Method for Causal Discovery on Discrete Data
• [stat.ML]Bayesian learning of forest and tree graphical models
• [stat.ML]Decision Tree-Based Predictive Models for Academic Achievement Using College Students’ Support Networks
• [stat.ML]Disentanglement Analysis with Partial Information Decomposition
• [stat.ML]Evaluating the Robustness of Off-Policy Evaluation
• [stat.ML]On the interpretation of black-box default prediction models: an Italian Small and Medium Enterprises case
·····································
• [astro-ph.GA]Bayesian Inference of Globular Cluster Properties Using Distribution Functions
Gwendolyn M. Eadie, Jeremy J. Webb, Jeffrey S. Rosenthal
http://arxiv.org/abs/2108.13491v1
• [cs.AI]Artificial Intelligence Algorithms for Natural Language Processing and the Semantic Web Ontology Learning
Bryar A. Hassan, Tarik A. Rashid
http://arxiv.org/abs/2108.13772v1
• [cs.AI]Phy-Q: A Benchmark for Physical Reasoning
Cheng Xue, Vimukthini Pinto, Chathura Gamage, Ekaterina Nikonova, Peng Zhang, Jochen Renz
http://arxiv.org/abs/2108.13696v1
• [cs.AI]Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study
Pavel Andreev, Alexander Fritzler, Dmitry Vetrov
http://arxiv.org/abs/2108.13996v1
• [cs.AI]The Horn Non-Clausal Class and its Polynomiality
Gonzalo E. Imaz
http://arxiv.org/abs/2108.13744v1
• [cs.CL]A Generative Approach for Mitigating Structural Biases in Natural Language Inference
Dimion Asael, Zachary Ziegler, Yonatan Belinkov
http://arxiv.org/abs/2108.14006v1
• [cs.CL]A Search Engine for Discovery of Biomedical Challenges and Directions
Dan Lahav, Jon Saad Falcon, Bailey Kuehl, Sophie Johnson, Sravanthi Parasa, Noam Shomron, Duen Horng Chau, Diyi Yang, Eric Horvitz, Daniel S. Weld, Tom Hope
http://arxiv.org/abs/2108.13751v1
• [cs.CL]Automatic Rule Generation for Time Expression Normalization
Wentao Ding, Jianhao Chen, Jinmao Li, Yuzhong Qu
http://arxiv.org/abs/2108.13658v1
• [cs.CL]Contrastive Domain Adaptation for Question Answering using Limited Text Corpora
Zhenrui Yue, Bernhard Kratzwald, Stefan Feuerriegel
http://arxiv.org/abs/2108.13854v1
• [cs.CL]Cross-Lingual Text Classification of Transliterated Hindi and Malayalam
Jitin Krishnan, Antonios Anastasopoulos, Hemant Purohit, Huzefa Rangwala
http://arxiv.org/abs/2108.13620v1
• [cs.CL]Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Ningyu Zhang, Luoqiu Li, Xiang Chen, Shumin Deng, Zhen Bi, Chuanqi Tan, Fei Huang, Huajun Chen
http://arxiv.org/abs/2108.13161v2
• [cs.CL]Discretized Integrated Gradients for Explaining Language Models
Soumya Sanyal, Xiang Ren
http://arxiv.org/abs/2108.13654v1
• [cs.CL]Dynamic Sliding Window for Meeting Summarization
Zhengyuan Liu, Nancy F. Chen
http://arxiv.org/abs/2108.13629v1
• [cs.CL]Effective Sequence-to-Sequence Dialogue State Tracking
Jeffrey Zhao, Mahdis Mahdieh, Ye Zhang, Yuan Cao, Yonghui Wu
http://arxiv.org/abs/2108.13990v1
• [cs.CL]Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience
George Chrysostomou, Nikolaos Aletras
http://arxiv.org/abs/2108.13759v1
• [cs.CL]Explaining Classes through Word Attribution
Samuel Rönnqvist, Amanda Myntti, Aki-Juhani Kyröläinen, Sampo Pyysalo, Veronika Laippala, Filip Ginter
http://arxiv.org/abs/2108.13653v1
• [cs.CL]Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization
Faisal Ladhak, Esin Durmus, He He, Claire Cardie, Kathleen McKeown
http://arxiv.org/abs/2108.13684v1
• [cs.CL]Gray Cycles of Maximum Length Related to k-Character Substitutions
Jean Néraud
http://arxiv.org/abs/2108.13659v1
• [cs.CL]How Does Adversarial Fine-Tuning Benefit BERT?
Javid Ebrahimi, Hao Yang, Wei Zhang
http://arxiv.org/abs/2108.13602v1
• [cs.CL]Knowledge-Grounded Dialogue with Reward-Driven Knowledge Selection
Shilei Liu, Xiaofeng Zhao, Bochao Li, Feiliang Ren
http://arxiv.org/abs/2108.13686v1
• [cs.CL]Like Article, Like Audience: Enforcing Multimodal Correlations for Disinformation Detection
Liesbeth Allein, Marie-Francine Moens, Domenico Perrotta
http://arxiv.org/abs/2108.13892v1
• [cs.CL]Linguistic Characterization of Divisive Topics Online: Case Studies on Contentiousness in Abortion, Climate Change, and Gun Control
Jacob Beel, Tong Xiang, Sandeep Soni, Diyi Yang
http://arxiv.org/abs/2108.13556v1
• [cs.CL]MELM: Data Augmentation with Masked Entity Language Modeling for Cross-lingual NER
Ran Zhou, Ruidan He, Xin Li, Lidong Bing, Erik Cambria, Luo Si, Chunyan Miao
http://arxiv.org/abs/2108.13655v1
• [cs.CL]Monolingual versus Multilingual BERTology for Vietnamese Extractive Multi-Document Summarization
Huy To Quoc, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen, Anh Gia-Tuan Nguyen
http://arxiv.org/abs/2108.13741v1
• [cs.CL]Plan-then-Generate: Controlled Data-to-Text Generation via Planning
Yixuan Su, David Vandyke, Sihui Wang, Yimai Fang, Nigel Collier
http://arxiv.org/abs/2108.13740v1
• [cs.CL]Query-Focused Extractive Summarisation for Finding Ideal Answers to Biomedical and COVID-19 Questions
Diego Mollá, Urvashi Khanna, Dima Galat, Vincent Nguyen, Maciej Rybinski
http://arxiv.org/abs/2108.12189v2
• [cs.CL]Robust Retrieval Augmented Generation for Zero-shot Slot Filling
Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Alfio Gliozzo
http://arxiv.org/abs/2108.13934v1
• [cs.CL]Scheduled Sampling Based on Decoding Steps for Neural Machine Translation
Yijin Liu, Fandong Meng, Yufeng Chen, Jinan Xu, Jie Zhou
http://arxiv.org/abs/2108.12963v2
• [cs.CL]Semi-Supervised Exaggeration Detection of Health Science Press Releases
Dustin Wright, Isabelle Augenstein
http://arxiv.org/abs/2108.13493v1
• [cs.CL]T3-Vis: a visual analytic framework for Training and fine-Tuning Transformers in NLP
Raymond Li, Wen Xiao, Lanjun Wang, Hyeju Jang, Giuseppe Carenini
http://arxiv.org/abs/2108.13587v1
• [cs.CL]TNNT: The Named Entity Recognition Toolkit
Sandaru Seneviratne, Sergio J. Rodríguez Méndez, Xuecheng Zhang, Pouya G. Omran, Kerry Taylor, Armin Haller
http://arxiv.org/abs/2108.13700v1
• [cs.CL]TREND: Trigger-Enhanced Relation-Extraction Network for Dialogues
Po-Wei Lin, Shang-Yu Su, Yun-Nung Chen
http://arxiv.org/abs/2108.13811v1
• [cs.CL]Task-Oriented Dialogue System as Natural Language Generation
Weizhi Wang, Zhirui Zhang, Junliang Guo, Boxing Chen, Weihua Luo
http://arxiv.org/abs/2108.13679v1
• [cs.CL]The five Is: Key principles for interpretable and safe conversational AI
Mattias Wahde, Marco Virgolin
http://arxiv.org/abs/2108.13766v1
• [cs.CL]Thermostat: A Large Collection of NLP Model Explanations and Analysis Tools
Nils Feldhus, Robert Schwarzenberg, Sebastian Möller
http://arxiv.org/abs/2108.13961v1
• [cs.CL]Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution
Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder
http://arxiv.org/abs/2108.13530v1
• [cs.CL]Unsupervised Open-Domain Question Answering
Pengfei Zhu, Xiaoguang Li, Jian Li, Hai Zhao
http://arxiv.org/abs/2108.13817v1
• [cs.CL]Want To Reduce Labeling Cost? GPT-3 Can Help
Shuohang Wang, Yang Liu, Yichong Xu, Chenguang Zhu, Michael Zeng
http://arxiv.org/abs/2108.13487v1
• [cs.CL]When Retriever-Reader Meets Scenario-Based Multiple-Choice Questions
Zixian Huang, Ao Wu, Yulin Shen, Gong Cheng, Yuzhong Qu
http://arxiv.org/abs/2108.13875v1
• [cs.CL]mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset
Luiz Henrique Bonifacio, Israel Campiotti, Roberto Lotufo, Rodrigo Nogueira
http://arxiv.org/abs/2108.13897v1
• [cs.CR]Backdoor Attacks on Pre-trained Models by Layerwise Weight Poisoning
Linyang Li, Demin Song, Xiaonan Li, Jiehang Zeng, Ruotian Ma, Xipeng Qiu
http://arxiv.org/abs/2108.13888v1
• [cs.CR]Beyond Model Extraction: Imitation Attack for Black-Box NLP APIs
Qiongkai Xu, Xuanli He, Lingjuan Lyu, Lizhen Qu, Gholamreza Haffari
http://arxiv.org/abs/2108.13873v1
• [cs.CR]DLPFS: The Data Leakage Prevention FileSystem
Stefano Braghin, Marco Simioni, Mathieu Sinn
http://arxiv.org/abs/2108.13785v1
• [cs.CR]DeepTaskAPT: Insider APT detection using Task-tree based Deep Learning
Mohammad Mamun, Kevin Shi
http://arxiv.org/abs/2108.13989v1
• [cs.CR]EG-Booster: Explanation-Guided Booster of ML Evasion Attacks
Abderrahmen Amich, Birhanu Eshete
http://arxiv.org/abs/2108.13930v1
• [cs.CR]Generalizing Weighted Trees: A Bridge from Bitcoin to GHOST
Ignacio Amores-Sesar, Christian Cachin, Anna Parker
http://arxiv.org/abs/2108.13502v1
• [cs.CR]Incorporating Deception into CyberBattleSim for Autonomous Defense
Erich Walter, Kimberly Ferguson-Walter, Ahmad Ridley
http://arxiv.org/abs/2108.13980v1
• [cs.CR]Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings
Mazda Moayeri, Soheil Feizi
http://arxiv.org/abs/2108.13797v1
• [cs.CR]Segmentation Fault: A Cheap Defense Against Adversarial Machine Learning
Doha Al Bared, Mohamed Nassar
http://arxiv.org/abs/2108.13617v1
• [cs.CV]A Novel Dataset for Keypoint Detection of quadruped Animals from Images
Prianka Banik, Lin Li, Xishuang Dong
http://arxiv.org/abs/2108.13958v1
• [cs.CV]AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks
Jingfei Chang, Yang Lu, Ping Xue, Yiqun Xu, Zhen Wei
http://arxiv.org/abs/2108.13591v1
• [cs.CV]Attention-based Multi-Reference Learning for Image Super-Resolution
Marco Pesavento, Marco Volino, Adrian Hilton
http://arxiv.org/abs/2108.13697v1
• [cs.CV]Automatic digital twin data model generation of building energy systems from piping and instrumentation diagrams
Florian Stinner, Martin Wiecek, Marc Baranski, Alexander Kümpel, Dirk Müller
http://arxiv.org/abs/2108.13912v1
• [cs.CV]Automatic labelling of urban point clouds using data fusion
Daan Bloembergen, Chris Eijgenstein
http://arxiv.org/abs/2108.13757v1
• [cs.CV]Dead Pixel Test Using Effective Receptive Field
Bum Jun Kim, Hyeyeon Choi, Hyeonah Jang, Dong Gu Lee, Wonseok Jeong, Sang Woo Kim
http://arxiv.org/abs/2108.13576v1
• [cs.CV]Deep Learning on Edge TPUs
Andreas M Kist
http://arxiv.org/abs/2108.13732v1
• [cs.CV]DepthTrack : Unveiling the Power of RGBD Tracking
Song Yan, Jinyu Yang, Jani Käpylä, Feng Zheng, Aleš Leonardis, Joni-Kristian Kämäräinen
http://arxiv.org/abs/2108.13962v1
• [cs.CV]Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classification Model for MIDOG Challenge
Jingtang Liang, Cheng Wang, Yujie Cheng, Zheng Wang, Fang Wang, Liyu Huang, Zhibin Yu, Yubo Wang
http://arxiv.org/abs/2108.13983v1
• [cs.CV]Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection
Baisong Zhang, Weiqing Min, Jing Wang, Sujuan Hou, Qiang Hou, Yuanjie Zheng, Shuqiang Jiang
http://arxiv.org/abs/2108.13775v1
• [cs.CV]End-to-End Monocular Vanishing Point Detection Exploiting Lane Annotations
Hiroto Honda, Motoki Kimura, Takumi Karasawa, Yusuke Uchida
http://arxiv.org/abs/2108.13699v1
• [cs.CV]Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision
Bo Li, Xinyang Jiang, Donglin Bai, Yuge Zhang, Ningxin Zheng, Xuanyi Dong, Lu Liu, Yuqing Yang, Dongsheng Li
http://arxiv.org/abs/2108.13465v1
• [cs.CV]InSeGAN: A Generative Approach to Segmenting Identical Instances in Depth Images
Anoop Cherian, Goncalo Dias Pais, Siddarth Jain, Tim K. Marks, Alan Sullivan
http://arxiv.org/abs/2108.13865v1
• [cs.CV]Is First Person Vision Challenging for Object Tracking?
Matteo Dunnhofer, Antonino Furnari, Giovanni Maria Farinella, Christian Micheloni
http://arxiv.org/abs/2108.13665v1
• [cs.CV]Module-Power Prediction from PL Measurements using Deep Learning
Mathis Hoffmann, Johannes Hepp, Bernd Doll, Claudia Buerhop-Lutz, Ian Marius Peters, Christoph Brabec, Andreas Maier, Vincent Christlein
http://arxiv.org/abs/2108.13640v1
• [cs.CV]One-shot domain adaptation for semantic face editing of real world images using StyleALAE
Ravi Kiran Reddy, Kumar Shubham, Gopalakrishnan Venkatesh, Sriram Gandikota, Sarthak Khoche, Dinesh Babu Jayagopi, Gopalakrishnan Srinivasaraghavan
http://arxiv.org/abs/2108.13876v1
• [cs.CV]PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs
Vidhya Kamakshi, Uday Gupta, Narayanan C Krishnan
http://arxiv.org/abs/2108.13828v1
• [cs.CV]Pruning with Compensation: Efficient Channel Pruning for Deep Convolutional Neural Networks
Zhouyang Xie, Yan Fu, Shengzhao Tian, Junlin Zhou, Duanbing Chen
http://arxiv.org/abs/2108.13728v1
• [cs.CV]Realistic Hands: A Hybrid Model for 3D Hand Reconstruction
Michael Seeber, Martin R. Oswald, Roi Poranne
http://arxiv.org/abs/2108.13995v1
• [cs.CV]S4-Crowd: Semi-Supervised Learning with Self-Supervised Regularisation for Crowd Counting
Haoran Duan, Yu Guan
http://arxiv.org/abs/2108.13969v1
• [cs.CV]SMAC-Seg: LiDAR Panoptic Segmentation via Sparse Multi-directional Attention Clustering
Enxu Li, Ryan Razani, Yixuan Xu, Liu Bingbing
http://arxiv.org/abs/2108.13588v1
• [cs.CV]ScatSimCLR: self-supervised contrastive learning with pretext task regularization for small-scale datasets
Vitaliy Kinakh, Olga Taran, Svyatoslav Voloshynovskiy
http://arxiv.org/abs/2108.13939v1
• [cs.CV]Scene Synthesis via Uncertainty-Driven Attribute Synchronization
Haitao Yang, Zaiwei Zhang, Siming Yan, Haibin Huang, Chongyang Ma, Yi Zheng, Chandrajit Bajaj, Qixing Huang
http://arxiv.org/abs/2108.13499v1
• [cs.CV]Self-Calibrating Neural Radiance Fields
Yoonwoo Jeong, Seokjun Ahn, Christopher Choy, Animashree Anandkumar, Minsu Cho, Jaesik Park
http://arxiv.org/abs/2108.13826v1
• [cs.CV]Self-balanced Learning For Domain Generalization
Jin Kim, Jiyoung Lee, Jungin Park, Dongbo Min, Kwanghoon Sohn
http://arxiv.org/abs/2108.13597v1
• [cs.CV]SemIE: Semantically-aware Image Extrapolation
Bholeshwar Khurana, Soumya Ranjan Dash, Abhishek Bhatia, Aniruddha Mahapatra, Hrituraj Singh, Kuldeep Kulkarni
http://arxiv.org/abs/2108.13702v1
• [cs.CV]Semi-supervised Image Classification with Grad-CAM Consistency
Juyong Lee, Seunghyuk Cho
http://arxiv.org/abs/2108.13673v1
• [cs.CV]SimulLR: Simultaneous Lip Reading Transducer with Attention-Guided Adaptive Memory
Zhijie Lin, Zhou Zhao, Haoyuan Li, Jinglin Liu, Meng Zhang, Xingshan Zeng, Xiaofei He
http://arxiv.org/abs/2108.13630v1
• [cs.CV]Spectral Splitting and Aggregation Network for Hyperspectral Face Super-Resolution
Junjun Jiang, Chenyang Wang, Kui Jiang, Xianming Liu, Jiayi Ma
http://arxiv.org/abs/2108.13584v1
• [cs.CV]Super-Resolution Appearance Transfer for 4D Human Performances
Marco Pesavento, Marco Volino, Adrian Hilton
http://arxiv.org/abs/2108.13739v1
• [cs.CY]Tracing app technology: An ethical review in the COVID-19 era and directions for post-COVID-19
Saleh Afroogh, Amir Esmalian, Ali Mostafavi, Ali Akbari, Kambiz Rasoulkhani, Shahriar Esmaeili, Ehsan Hajiramezanali
http://arxiv.org/abs/2108.12673v2
• [cs.CY]Why and How Governments Should Monitor AI Development
Jess Whittlestone, Jack Clark
http://arxiv.org/abs/2108.12427v2
• [cs.DC]A High-Fidelity Flow Solver for Unstructured Meshes on Field-Programmable Gate Arrays
Martin Karp, Artur Podobas, Tobias Kenter, Niclas Jansson, Christian Plessl, Philipp Schlatter, Stefano Markidis
http://arxiv.org/abs/2108.12188v2
• [cs.DC]A log-linear #card=math&code=%282%2B5%2F6%29&id=dTHrS)-approximation algorithm for parallel machine scheduling with a single orthogonal resource
Adrian Naruszko, Bartłomiej Przybylski, Krzysztof Rzadca
http://arxiv.org/abs/2108.13716v1
• [cs.DC]Building Time-Triggered Schedules for typed-DAG Tasks with alternative implementations
Houssam-Eddine Zahaf, Nicola Capodieci
http://arxiv.org/abs/2108.13871v1
• [cs.DC]ExaWorks: Workflows for Exascale
Aymen Al-Saadi, Dong H. Ahn, Yadu Babuji, Kyle Chard, James Corbett, Mihael Hategan, Stephen Herbein, Shantenu Jha, Daniel Laney, Andre Merzky, Todd Munson, Michael Salim, Mikhail Titov, Matteo Turilli, Justin M. Wozniak
http://arxiv.org/abs/2108.13521v1
• [cs.DC]PTRAIL — A python package for parallel trajectory data preprocessing
Salman Haidri, Yaksh J. Haranwala, Vania Bogorny, Chiara Renso, Vinicius Prado da Fonseca, Amilcar Soares
http://arxiv.org/abs/2108.13202v1
• [cs.DC]Population Protocols: Beyond Runtime Analysis
Javier Esparza
http://arxiv.org/abs/2108.13449v1
• [cs.ET]Intrinsic Spike Timing Dependent Plasticity in Stochastic Magnetic Tunnel Junctions Mediated by Heat Dynamics
Humberto Inzunza Velarde, Jheel Nagaria, Zihan Yin, Ajey Jacob, Akhilesh Jaiswal
http://arxiv.org/abs/2108.12684v1
• [cs.HC]ConVIScope: Visual Analytics for Exploring Patient Conversations
Raymond Li, Enamul Hoque, Giuseppe Carenini, Richard Lester, Raymond Chau
http://arxiv.org/abs/2108.13514v1
• [cs.IR]Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation
Ioannis Partalas
http://arxiv.org/abs/2108.13824v1
• [cs.IR]Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback
HongChien Yu, Chenyan Xiong, Jamie Callan
http://arxiv.org/abs/2108.13454v1
• [cs.IR]Zero Shot on the Cold-Start Problem: Model-Agnostic Interest Learning for Recommender Systems
Philip J. Feng, Pingjun Pan, Tingting Zhou, Hongxiang Chen, Chuanjiang Luo
http://arxiv.org/abs/2108.13592v1
• [cs.IT]Energy Minimization for IRS-aided WPCNs with Non-linear Energy Harvesting Model
Piao Zeng, Qingqing Wu, Deli Qiao
http://arxiv.org/abs/2108.13603v1
• [cs.IT]Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups
Tung T. Vu, Hien Quoc Ngo, Duy T. Ngo, Minh N Dao, Erik G. Larsson
http://arxiv.org/abs/2108.13512v1
• [cs.IT]Robust Symbol-Level Precoding and Passive Beamforming for IRS-Aided Communications
Guangyang Zhang, Chao Shen, Bo Ai, Zhangdui Zhong
http://arxiv.org/abs/2108.13782v1
• [cs.IT]Spectral and Energy Efficiency of ACO-OFDM in Visible Light Communication Systems
Shuai Ma, Ruixin Yang, Xiong Deng, Xintong Ling, Xun Zhang, Fuhui Zhou, Shiyin Li, Derrick Wing Kwan Ng
http://arxiv.org/abs/2108.13906v1
• [cs.IT]Structural Properties of Optimal Test Channels for Gaussian Multivariate Partially Observable Distributed Sources
Michail Gkagkos, Evagoras Stylianou, Charalambos D. Charalambous
http://arxiv.org/abs/2108.13488v1
• [cs.IT]Successful Recovery Performance Guarantees of Noisy SOMP
Wei Zhang, Taejoon Kim
http://arxiv.org/abs/2108.13855v1
• [cs.IT]Triple-Structured Compressive Sensing-based Channel Estimation for RIS-aided MU-MIMO Systems
Xu Shi, Jintao Wang, Guozhi Chen, Jian Song
http://arxiv.org/abs/2108.13765v1
• [cs.IT]Upper bounds on the length function for covering codes
Alexander A. Davydov, Stefano Marcugini, Fernanda Pambianco
http://arxiv.org/abs/2108.13609v1
• [cs.LG]A New Approach to Multilinear Dynamical Systems and Control
Randy C. Hoover, Kyle Caudle, Karen Braman
http://arxiv.org/abs/2108.13583v1
• [cs.LG]A manifold learning perspective on representation learning: Learning decoder and representations without an encoder
Viktoria Schuster, Anders Krogh
http://arxiv.org/abs/2108.13910v1
• [cs.LG]APS: Active Pretraining with Successor Features
Hao Liu, Pieter Abbeel
http://arxiv.org/abs/2108.13956v1
• [cs.LG]Adaptive Label Smoothing To Regularize Large-Scale Graph Training
Kaixiong Zhou, Ninghao Liu, Fan Yang, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu
http://arxiv.org/abs/2108.13555v1
• [cs.LG]Approximation Methods for Partially Observed Markov Decision Processes (POMDPs)
Caleb M. Bowyer
http://arxiv.org/abs/2108.13965v1
• [cs.LG]Benchmarking the Accuracy and Robustness of Feedback Alignment Algorithms
Albert Jiménez Sanfiz, Mohamed Akrout
http://arxiv.org/abs/2108.13446v1
• [cs.LG]Bubblewrap: Online tiling and real-time flow prediction on neural manifolds
Anne Draelos, Pranjal Gupta, Na Young Jun, Chaichontat Sriworarat, John Pearson
http://arxiv.org/abs/2108.13941v1
• [cs.LG]Canoe : A System for Collaborative Learning for Neural Nets
Harshit Daga, Yiwen Chen, Aastha Agrawal, Ada Gavrilovska
http://arxiv.org/abs/2108.12124v2
• [cs.LG]Chi-square Loss for Softmax: an Echo of Neural Network Structure
Zeyu Wang, Meiqing Wang
http://arxiv.org/abs/2108.13822v1
• [cs.LG]Communication-Computation Efficient Device-Edge Co-Inference via AutoML
Xinjie Zhang, Jiawei Shao, Yuyi Mao, Jun Zhang
http://arxiv.org/abs/2108.13009v2
• [cs.LG]Deep Learning of Transferable MIMO Channel Modes for 6G V2X Communications
Lorenzo Cazzella, Dario Tagliaferri, Marouan Mizmizi, Damiano Badini, Christian Mazzucco, Matteo Matteucci, Umberto Spagnolini
http://arxiv.org/abs/2108.13831v1
• [cs.LG]Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods
Tobias Alt, Karl Schrader, Joachim Weickert, Pascal Peter, Matthias Augustin
http://arxiv.org/abs/2108.13993v1
• [cs.LG]DoGR: Disaggregated Gaussian Regression for Reproducible Analysis of Heterogeneous Data
Nazanin Alipourfard, Keith Burghardt, Kristina Lerman
http://arxiv.org/abs/2108.13581v1
• [cs.LG]Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space
Linus Scheibenreif, Michael Mommert, Damian Borth
http://arxiv.org/abs/2108.13902v1
• [cs.LG]Fast Multi-label Learning
Xiuwen Gong, Dong Yuan, Wei Bao
http://arxiv.org/abs/2108.13570v1
• [cs.LG]GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization
Yen-Hsiu Chou, Shenda Hong, Chenxi Sun, Derun Cai, Moxian Song, Hongyan Li
http://arxiv.org/abs/2108.13858v1
• [cs.LG]Heterogeneous Graph Neural Network with Multi-view Representation Learning
Zezhi Shao, Yongjun Xu, Wei Wei, Fei Wang, Zhao Zhang, Feida Zhu
http://arxiv.org/abs/2108.13650v1
• [cs.LG]Learning Optimal Prescriptive Trees from Observational Data
Nathanael Jo, Sina Aghaei, Andrés Gómez, Phebe Vayanos
http://arxiv.org/abs/2108.13628v1
• [cs.LG]Learning to Synthesize Programs as Interpretable and Generalizable Policies
Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim
http://arxiv.org/abs/2108.13643v1
• [cs.LG]Machine Learning Methods for Management UAV Flocks — a Survey
Rina Azoulay, Yoram Haddad, Shulamit Reches
http://arxiv.org/abs/2108.13448v1
• [cs.LG]Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations
Shameem A. Puthiya Parambath, Christos Anagnostopoulos, Roderick Murray-Smith, Sean MacAvaney, Evangelos Zervas
http://arxiv.org/abs/2108.13810v1
• [cs.LG]Medical SANSformers: Training self-supervised transformers without attention for Electronic Medical Records
Yogesh Kumar, Alexander Ilin, Henri Salo, Sangita Kulathinal, Maarit K. Leinonen, Pekka Marttinen
http://arxiv.org/abs/2108.13672v1
• [cs.LG]Morphence: Moving Target Defense Against Adversarial Examples
Abderrahmen Amich, Birhanu Eshete
http://arxiv.org/abs/2108.13952v1
• [cs.LG]Rapidly and accurately estimating brain strain and strain rate across head impact types with transfer learning and data fusion
Xianghao Zhan, Yuzhe Liu, Nicholas J. Cecchi, Olivier Gevaert, Michael M. Zeineh, Gerald A. Grant, David B. Camarillo
http://arxiv.org/abs/2108.13577v1
• [cs.LG]Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning
Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu
http://arxiv.org/abs/2108.13886v1
• [cs.LG]Time Series Prediction using Deep Learning Methods in Healthcare
Mohammad Amin Morid, Olivia R. Liu Sheng, Joseph Dunbar
http://arxiv.org/abs/2108.13461v1
• [cs.LG]Towards Out-Of-Distribution Generalization: A Survey
Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui
http://arxiv.org/abs/2108.13624v1
• [cs.LG]Using a one dimensional parabolic model of the full-batch loss to estimate learning rates during training
Maximus Mutschler, Andreas Zell
http://arxiv.org/abs/2108.13880v1
• [cs.LG]WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU
Tian Lan, Sunil Srinivasa, Stephan Zheng
http://arxiv.org/abs/2108.13976v1
• [cs.LG]When are Deep Networks really better than Random Forests at small sample sizes?
Haoyin Xu, Michael Ainsworth, Yu-Chung Peng, Madi Kusmanov, Sambit Panda, Joshua T. Vogelstein
http://arxiv.org/abs/2108.13637v1
• [cs.NE]Spike time displacement based error backpropagation in convolutional spiking neural networks
Maryam Mirsadeghi, Majid Shalchian, Saeed Reza Kheradpisheh, Timothée Masquelier
http://arxiv.org/abs/2108.13621v1
• [cs.NI]A Hierarchical Stitching Algorithm for Coded Compressed Sensing
Yi-Jheng Lin, Chia-Ming Chang, Cheng-Shang Chang
http://arxiv.org/abs/2108.13760v1
• [cs.NI]Latency-Redundancy Tradeoff in Distributed Read-Write Systems
Saraswathy Ramanathan, Gaurav Gautam, Vikram Srinivasan, Parimal Parag
http://arxiv.org/abs/2108.13949v1
• [cs.RO]A review of mobile robot motion planning methods: from classical motion planning workflows to reinforcement learning-based architectures
Zichen He, Jiawei Wang, Chunwei Song
http://arxiv.org/abs/2108.13619v1
• [cs.RO]Autonomous Rollator: A Case Study in the Agebots Project
Jonas Frei, Anina Havelka, Markus Wüst, Einar Nielsen, Andreas Ziltner, Katrin S. Lohan
http://arxiv.org/abs/2108.13648v1
• [cs.RO]BotNet: A Simulator for Studying the Effects of Accurate Communication Models on Multi-agent and Swarm Control
Mark Selden, Jason Zhou, Felipe Campos, Nathan Lambert, Daniel Drew, Kristofer S. J. Pister
http://arxiv.org/abs/2108.13606v1
• [cs.RO]Lane level context and hidden space characterization for autonomous driving
Alexandre Armand, Corentin Sanchez, Philippe Xu, Alexandre Arm, Philippe Bonnifait
http://arxiv.org/abs/2108.13664v1
• [cs.RO]Learning Practically Feasible Policies for Online 3D Bin Packing
Hang Zhao, Chenyang Zhu, Xin Xu, Hui Huang, Kai Xu
http://arxiv.org/abs/2108.13680v1
• [cs.RO]Manipulation of Camera Sensor Data via Fault Injection for Anomaly Detection Studies in Verification and Validation Activities For AI
Alim Kerem Erdogmus, Assist. Prof. Dr. Ugur Yayan
http://arxiv.org/abs/2108.13803v1
• [cs.RO]Planning for Dexterous Ungrasping: Secure Ungrasping through Dexterous Manipulation
Chung Hee Kim, Ka Hei Mak, Jungwon Seo
http://arxiv.org/abs/2108.13580v1
• [cs.RO]Riemannian Optimization for Distance Geometric Inverse Kinematics
Filip Marić, Matthew Giamou, Adam W. Hall, Soroush Khoubyarian, Ivan Petrović, Jonathan Kelly
http://arxiv.org/abs/2108.13720v1
• [cs.RO]Robotic Lime Picking by Considering Leaves as Permeable Obstacles
Heramb Nemlekar, Ziang Liu, Suraj Kothawade, Sherdil Niyaz, Barath Raghavan, Stefanos Nikolaidis
http://arxiv.org/abs/2108.13889v1
• [cs.RO]SURENA IV: Towards A Cost-effective Full-size Humanoid Robot for Real-world Scenarios
Aghil Yousefi-Koma, Behnam Maleki, Hessam Maleki, Amin Amani, Mohammad Ali Bazrafshani, Hossein Keshavarz, Ala Iranmanesh, Alireza Yazdanpanah, Hamidreza Alai, Sahel Salehi, Mahyar Ashkvari, Milad Mousavi, Milad Shafiee Ashtiani
http://arxiv.org/abs/2108.13515v1
• [cs.RO]The Interaction Flow Editor: A New Human-Robot Interaction RapidPrototyping Interface
Matthew Huggins, Anastasia K. Ostrowski, Andrew Rapo, Eric Woudenberg, Cynthia Breazeal, Hae Won Park
http://arxiv.org/abs/2108.13838v1
• [cs.RO]Through the Looking Glass: Diminishing Occlusions in Robot Vision Systems with Mirror Reflections
Kentaro Yoshioka, Hidenori Okuni, Tuan Thanh Ta, Akihide Sai
http://arxiv.org/abs/2108.13599v1
• [cs.SE]Towards a Common Testing Terminology for Software Engineering and Artificial Intelligence Experts
Lisa Jöckel, Thomas Bauer, Michael Kläs, Marc P. Hauer, Janek Groß
http://arxiv.org/abs/2108.13837v1
• [cs.SI]Control Scenarios for Probabilistic SIR Epidemics on Social-Connection Graphs
Jan B. Broekaert, Davide La Torre
http://arxiv.org/abs/2108.13714v1
• [cs.SI]Modularity and Heavy-Tailed Degree Distributions
Larry Wilson
http://arxiv.org/abs/2108.13450v1
• [cs.SI]Network psychometrics and cognitive network science open new ways for detecting, understanding and tackling the complexity of math anxiety: A review
Massimo Stella
http://arxiv.org/abs/2108.13800v1
• [cs.SI]On Comparing and Enhancing Common Approaches to Network Community Detection
Niko Motschnig, Alexander Ramharter, Oliver Schweiger, Philipp Zabka, Klaus-Tycho Foerster
http://arxiv.org/abs/2108.13482v1
• [cs.SI]The emojification of sentiment on social media: Collection and analysis of a longitudinal Twitter sentiment dataset
Wenjie Yin, Rabab Alkhalifa, Arkaitz Zubiaga
http://arxiv.org/abs/2108.13898v1
• [eess.IV]Iterative Filter Adaptive Network for Single Image Defocus Deblurring
Junyong Lee, Hyeongseok Son, Jaesung Rim, Sunghyun Cho, Seungyong Lee
http://arxiv.org/abs/2108.13610v1
• [eess.IV]OARnet: Automated organs-at-risk delineation in Head and Neck CT images
Mumtaz Hussain Soomro, Hamidreza Nourzadeh, Victor Gabriel Leandro Alves, Wookjin Choi, Jeffrey V. Siebers
http://arxiv.org/abs/2108.13987v1
• [eess.IV]Simultaneous Nuclear Instance and Layer Segmentation in Oral Epithelial Dysplasia
Adam J. Shephard, Simon Graham, R. M. Saad Bashir, Mostafa Jahanifar, Hanya Mahmood, Syed Ali Khurram, Nasir M. Rajpoot
http://arxiv.org/abs/2108.13904v1
• [eess.IV]The Application of Convolutional Neural Networks for Tomographic Reconstruction of Hyperspectral Images
Wei-Chih Huang, Mads Svanborg Peters, Mads Juul Ahlebaek, Mads Toudal Frandsen, René Lynge Eriksen, Bjarke Jørgensen
http://arxiv.org/abs/2108.13458v1
• [eess.SP]Unit-Modulus Wireless Federated Learning Via Penalty Alternating Minimization
Shuai Wang, Dachuan Li, Rui Wang, Qi Hao, Yik-Chung Wu, Derrick Wing Kwan Ng
http://arxiv.org/abs/2108.13669v1
• [math.CO]Graphs with minimum degree-based entropy
Yanni Dong, Maximilien Gadouleau, Pengfei Wan, Shenggui Zhang
http://arxiv.org/abs/2108.13884v1
• [math.NA]An FEA surrogate model with Boundary Oriented Graph Embedding approach
Xingyu Fu, Fengfeng Zhou, Dheeraj Peddireddy, Zhengyang Kang, Martin Byung-Guk Jun, Vaneet Aggarwal
http://arxiv.org/abs/2108.13509v1
• [math.PR]On the Number of Faces and Radii of Cells Induced by Gaussian Spherical Tessellations
Eric Lybrand, Anna Ma, Rayan Saab
http://arxiv.org/abs/2108.13523v1
• [math.ST]New Highly Efficient High-Breakdown Estimator of Multivariate Scatter and Location for Elliptical Distributions
Justin A. Fishbone, Lamine Mili
http://arxiv.org/abs/2108.13567v1
• [math.ST]Uniform Consistency in Nonparametric Mixture Models
Bryon Aragam, Ruiyi Yang
http://arxiv.org/abs/2108.14003v1
• [physics.data-an]Toward AI-enhanced online-characterization and shaping of ultrashort X-ray free-electron laser pulses
Kristina Dingel, Thorsten Otto, Lutz Marder, Lars Funke, Arne Held, Sara Savio, Andreas Hans, Gregor Hartmann, David Meier, Jens Viefhaus, Bernhard Sick, Arno Ehresmann, Markus Ilchen, Wolfram Helml
http://arxiv.org/abs/2108.13979v1
• [q-bio.NC]Astrocytes mediate analogous memory in a multi-layer neuron-astrocytic network
Yuliya Tsybina, Innokentiy Kastalskiy, Mikhail Krivonosov, Alexey Zaikin, Victor Kazantsev, Alexander Gorban, Susanna Gordleeva
http://arxiv.org/abs/2108.13414v1
• [q-bio.QM]Clustering of Pain Dynamics in Sickle Cell Disease from Sparse, Uneven Samples
Gary K. Nave Jr., Swati Padhee, Amanuel Alambo, Tanvi Banerjee, Nirmish Shah, Daniel M. Abrams
http://arxiv.org/abs/2108.13963v1
• [q-bio.QM]Temporal Deep Learning Architecture for Prediction of COVID-19 Cases in India
Hanuman Verma, Saurav Mandal, Akshansh Gupta
http://arxiv.org/abs/2108.13823v1
• [quant-ph]Identifying optimal cycles in quantum thermal machines with reinforcement-learning
Paolo Andrea Erdman, Frank Noé
http://arxiv.org/abs/2108.13525v1
• [quant-ph]Recent advances for quantum classifiers
Weikang Li, Dong-Ling Deng
http://arxiv.org/abs/2108.13421v1
• [stat.AP]A practical guide to causal discovery with cohort data
Ryan M. Andrews, Ronja Foraita, Vanessa Didelez, Janine Witte
http://arxiv.org/abs/2108.13395v2
• [stat.AP]Comments on The clinical meaningfulness of a treatment’s effect on a time-to-event variable
Christos Argyropoulos
http://arxiv.org/abs/2108.13575v1
• [stat.AP]Optimal Daily Trading of Battery Operations Using Arbitrage Spreads
Ekaterina Abramova, Derek Bunn
http://arxiv.org/abs/2108.13511v1
• [stat.AP]Regional estimates of reproduction numbers with application to COVID-19
Jan Pablo Burgard, Stefan Heyder, Thomas Hotz, Tyll Krueger
http://arxiv.org/abs/2108.13842v1
• [stat.CO]A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example
Fernando Alarid-Escudero, Eline M. Krijkamp, Eva A. Enns, Alan Yang, M. G. Myriam Hunink, Petros Pechlivanoglou, Hawre Jalal
http://arxiv.org/abs/2108.13552v1
• [stat.ME]Comparison of cause specific rate functions of panel count data with multiple modes of recurrence
Sankaran P. G., Ashlin Mathew, P. M., Sreedevi E. P.
http://arxiv.org/abs/2108.13967v1
• [stat.ME]Double Machine Learning for Partially Linear Mixed-Effects Models with Repeated Measurements
Corinne Emmenegger, Peter Bühlmann
http://arxiv.org/abs/2108.13657v1
• [stat.ME]Functional Data Representation with Merge Trees
Matteo Pegoraro, Piercesare Secchi
http://arxiv.org/abs/2108.13147v2
• [stat.ME]On Proximal Causal Inference With Synthetic Controls
Xu Shi, Wang Miao, Mengtong Hu, Eric Tchetgen Tchetgen
http://arxiv.org/abs/2108.13935v1
• [stat.ME]Spatial Blind Source Separation in the Presence of a Drift
Christoph Muehlmann, Peter Filzmoser, Klaus Nordhausen
http://arxiv.org/abs/2108.13813v1
• [stat.ME]Variable Selection in Regression Model with AR(p) Error Terms Based on Heavy Tailed Distributions
Yetkin Tuaç, Olcay Arslan
http://arxiv.org/abs/2108.13755v1
• [stat.ML]A Subsampling Based Method for Causal Discovery on Discrete Data
Austin Goddard, Yu Xiang
http://arxiv.org/abs/2108.13984v1
• [stat.ML]Bayesian learning of forest and tree graphical models
Edmund Jones
http://arxiv.org/abs/2108.13992v1
• [stat.ML]Decision Tree-Based Predictive Models for Academic Achievement Using College Students’ Support Networks
Anthony Frazier, Joethi Silva, Rachel Meilak, Indranil Sahoo, David Chan, Michael Broda
http://arxiv.org/abs/2108.13947v1
• [stat.ML]Disentanglement Analysis with Partial Information Decomposition
Seiya Tokui, Issei Sato
http://arxiv.org/abs/2108.13753v1
• [stat.ML]Evaluating the Robustness of Off-Policy Evaluation
Yuta Saito, Takuma Udagawa, Haruka Kiyohara, Kazuki Mogi, Yusuke Narita, Kei Tateno
http://arxiv.org/abs/2108.13703v1
• [stat.ML]On the interpretation of black-box default prediction models: an Italian Small and Medium Enterprises case
Lisa Crosato, Caterina Liberati, Marco Repetto
http://arxiv.org/abs/2108.13914v1