cond-mat.stat-mech - 统计数学
cs.AI - 人工智能
cs.AR - 硬件体系结构
cs.CL - 计算与语言
cs.CR - 加密与安全
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DC - 分布式、并行与集群计算
cs.HC - 人机接口
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.NI - 网络和互联网体系结构
cs.RO - 机器人学
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
eess.SY - 系统和控制
math.NA - 数值分析
math.ST - 统计理论
physics.flu-dyn - 流体动力学
physics.soc-ph - 物理学与社会
stat.AP - 应用统计
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [cond-mat.stat-mech]The typical set and entropy in stochastic systems with arbitrary phase space growth
• [cs.AI]A brief history of AI: how to prevent another winter (a critical review)
• [cs.AI]An Oracle and Observations for the OpenAI Gym / ALE Freeway Environment
• [cs.AI]CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models
• [cs.AI]Efficient Communication in Multi-Agent Distributed Reinforcement Learning
• [cs.AI]Integration of Data and Theory for Accelerated Derivable Symbolic Discovery
• [cs.AI]Multi-Agent Inverse Reinforcement Learning: Suboptimal Demonstrations and Alternative Solution Concepts
• [cs.AI]Situated Conditional Reasoning
• [cs.AI]Symbol Emergence and The Solutions to Any Task
• [cs.AR]On the Accuracy of Analog Neural Network Inference Accelerators
• [cs.CL]A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act Detection
• [cs.CL]A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis
• [cs.CL]An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction
• [cs.CL]An Exploratory Study on Utilising the Web of Linked Data for Product Data Mining
• [cs.CL]An Open-Source Dataset and A Multi-Task Model for Malay Named Entity Recognition
• [cs.CL]CREAK: A Dataset for Commonsense Reasoning over Entity Knowledge
• [cs.CL]Challenges in Generalization in Open Domain Question Answering
• [cs.CL]Contextualized Embeddings based Convolutional Neural Networks for Duplicate Question Identification
• [cs.CL]Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation
• [cs.CL]Cross-Lingual Training with Dense Retrieval for Document Retrieval
• [cs.CL]Detecting Speaker Personas from Conversational Texts
• [cs.CL]Do Prompt-Based Models Really Understand the Meaning of their Prompts?
• [cs.CL]Empirical Study of Named Entity Recognition Performance Using Distribution-aware Word Embedding
• [cs.CL]Entity Linking and Discovery via Arborescence-based Supervised Clustering
• [cs.CL]Establishing Interlingua in Multilingual Language Models
• [cs.CL]Finetuned Language Models Are Zero-Shot Learners
• [cs.CL]Indexing Context-Sensitive Reachability
• [cs.CL]Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT
• [cs.CL]Learning Neural Models for Natural Language Processing in the Face of Distributional Shift
• [cs.CL]Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding
• [cs.CL]Multimodal Conditionality for Natural Language Generation
• [cs.CL]Quantifying Reproducibility in NLP and ML
• [cs.CL]Ranking Scientific Papers Using Preference Learning
• [cs.CL]So Cloze yet so Far: N400 Amplitude is Better Predicted by Distributional Information than Human Predictability Judgements
• [cs.CR]A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples
• [cs.CR]Ontology-driven Knowledge Graph for Android Malware
• [cs.CV]3D Human Shape Style Transfer
• [cs.CV]Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models
• [cs.CV]CAP-Net: Correspondence-Aware Point-view Fusion Network for 3D Shape Analysis
• [cs.CV]Deep Learning for Fitness
• [cs.CV]Deep Metric Learning for Ground Images
• [cs.CV]Dual-Camera Super-Resolution with Aligned Attention Modules
• [cs.CV]Ghost Loss to Question the Reliability of Training Data
• [cs.CV]Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning
• [cs.CV]MitoVis: A Visually-guided Interactive Intelligent System for Neuronal Mitochondria Analysis
• [cs.CV]Model-Based Parameter Optimization for Ground Texture Based Localization Methods
• [cs.CV]Neural Human Deformation Transfer
• [cs.CV]Occlusion-Invariant Rotation-Equivariant Semi-Supervised Depth Based Cross-View Gait Pose Estimation
• [cs.CV]Optimal Target Shape for LiDAR Pose Estimation
• [cs.CV]Ordinal Pooling
• [cs.CV]Representing Shape Collections with Alignment-Aware Linear Models
• [cs.CV]Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
• [cs.CV]Segmentation of turbulent computational fluid dynamics simulations with unsupervised ensemble learning
• [cs.CV]Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decomposition
• [cs.CV]Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models
• [cs.CV]Spatially varying white balancing for mixed and non-uniform illuminants
• [cs.CV]Towards Learning Spatially Discriminative Feature Representations
• [cs.CV]UnDeepLIO: Unsupervised Deep Lidar-Inertial Odometry
• [cs.CV]Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks
• [cs.CV]Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition
• [cs.CV]Wildfire smoke plume segmentation using geostationary satellite imagery
• [cs.CY]Hide and seek in Slovakia: utilizing tracking code data to uncover untrustworthy website networks
• [cs.CY]Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning
• [cs.DC]A Reliable, Self-Adaptive Face Identification Framework via Lyapunov Optimization
• [cs.DC]A Study of Mixed Precision Strategies for GMRES on GPUs
• [cs.DC]Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability
• [cs.DC]Byzantine Consensus in Directed Hypergraphs
• [cs.DC]Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters
• [cs.DC]Continuous Tasks and the Chromatic Simplicial Approximation Theorem
• [cs.DC]ECO: Edge-Cloud Optimization of 5G applications
• [cs.DC]Enabling Reproducible Analysis of Complex Workflows on the Edge-to-Cloud Continuum
• [cs.DC]Fast Abstracts and Student Forum Proceedings, 17th European Dependable Computing Conference — EDCC 2021
• [cs.DC]FedApp: a Research Sandbox for Application Orchestration in Federated Clouds using OpenStack
• [cs.HC]A Multi-Sensor Interface to Improve the Teaching and Learning Experience in Arc Welding Training Tasks
• [cs.HC]The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
• [cs.IR]UserBERT: Contrastive User Model Pre-training
• [cs.IT]A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access
• [cs.IT]Low-Latency and Secure Computation Offloading Assisted by Hybrid Relay-Reflecting Intelligent Surface
• [cs.IT]Optimizing the Energy Efficiency of Unreliable Memories for Quantized Kalman Filtering
• [cs.IT]Scalar Gaussian Wiretap Channel: Properties of the Support Size of the Secrecy-Capacity-Achieving Distribution
• [cs.IT]Secrecy Performance of α-κ-μ Shadowed Fading Channel
• [cs.IT]Secure Source Coding with Side-information at Decoder and Shared Key at Encoder and Decoder
• [cs.LG]A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithms
• [cs.LG]A New Approach to Multilabel Stratified Cross Validation with Application to Large and Sparse Gene Ontology Datasets
• [cs.LG]Biomedical Data-to-Text Generation via Fine-Tuning Transformers
• [cs.LG]Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms
• [cs.LG]Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry
• [cs.LG]Edge-featured Graph Neural Architecture Search
• [cs.LG]Estimating Demand Flexibility Using Siamese LSTM Neural Networks
• [cs.LG]How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
• [cs.LG]Impact of GPU uncertainty on the training of predictive deep neural networks
• [cs.LG]Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation
• [cs.LG]Investigate the Correlation of Breast Cancer Dataset using Different Clustering Technique
• [cs.LG]J-Score: A Robust Measure of Clustering Accuracy
• [cs.LG]LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
• [cs.LG]Large-Scale Learning with Fourier Features and Tensor Decompositions
• [cs.LG]LightAutoML: AutoML Solution for a Large Financial Services Ecosystem
• [cs.LG]Multi-agent Natural Actor-critic Reinforcement Learning Algorithms
• [cs.LG]Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems
• [cs.LG]Provably Safe Model-Based Meta Reinforcement Learning: An Abstraction-Based Approach
• [cs.LG]Stochastic Physics-Informed Neural Networks (SPINN): A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equations
• [cs.LG]Topographic VAEs learn Equivariant Capsules
• [cs.NI]Is Machine Learning Ready for Traffic Engineering Optimization?
• [cs.RO]A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight
• [cs.RO]Invariant Filtering for Bipedal Walking on Dynamic Rigid Surfaces with Orientation-based Measurement Model
• [cs.RO]Iterative Imitation Policy Improvement for Interactive Autonomous Driving
• [cs.RO]Mechanical Chameleons: Evaluating the effects of a social robot’s non-verbal behavior on social influence
• [cs.RO]On the similarities between Control Barrier Functions (CBFs) and Behavior Control Lyapunov Functions (BCLFs)
• [cs.RO]Real-Time Volumetric-Semantic Exploration and Mapping: An Uncertainty-Aware Approach
• [cs.RO]Theory of Mind Based Assistive Communication in Complex Human Robot Cooperation
• [cs.SI]Neural PathSim for Inductive Similarity Search in Heterogeneous Information Networks
• [eess.IV]Automatic Foot Ulcer segmentation Using an Ensemble of Convolutional Neural Networks
• [eess.IV]Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction
• [eess.IV]Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation
• [eess.IV]Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imaging
• [eess.SP]Ground-Assisted Federated Learning in LEO Satellite Constellations
• [eess.SY]Continuous-Time Behavior Trees as Discontinuous Dynamical Systems
• [math.NA]Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations
• [math.ST]Is the mode elicitable relative to unimodal distributions?
• [physics.flu-dyn]Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows
• [physics.soc-ph]COVID-19 Vaccine Hesitancy and Information Diffusion: An Agent-based Modeling Approach
• [physics.soc-ph]Universality, criticality and complexity of information propagation in social media
• [stat.AP]Epidemic Models for COVID-19 during the First Wave from February to May 2020: a Methodological Review
• [stat.AP]Evaluating the Use of Generalized Dynamic Weighted Ordinary Least Squares for Individualized HIV Treatment Strategies
• [stat.AP]Frequency-Severity Experience Rating based on Latent Markovian Risk Profiles
• [stat.AP]Simultaneous quantification and changepoint detection of point source gas emissions using recursive Bayesian inference
• [stat.AP]Teacher Mental Health During the COVID-19 Pandemic: Informing Policies to Support Teacher Well-being and Effective Teaching Practices
• [stat.AP]Two Shifts for Crop Mapping: Leveraging Aggregate Crop Statistics to Improve Satellite-based Maps in New Regions
• [stat.ME]Regularized tapered sample covariance matrix
• [stat.ME]Robust confidence distributions from proper scoring rules
• [stat.ME]Variational Bayes algorithm and posterior consistency of Ising model parameter estimation
• [stat.ML]Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process
• [stat.ML]Sample Noise Impact on Active Learning
• [stat.ML]Statistical Estimation and Inference via Local SGD in Federated Learning
·····································
• [cond-mat.stat-mech]The typical set and entropy in stochastic systems with arbitrary phase space growth
Rudolf Hanel, Bernat Corominas-Murtra
http://arxiv.org/abs/2109.01475v1
• [cs.AI]A brief history of AI: how to prevent another winter (a critical review)
Amirhosein Toosi, Andrea Bottino, Babak Saboury, Eliot Siegel, Arman Rahmim
http://arxiv.org/abs/2109.01517v1
• [cs.AI]An Oracle and Observations for the OpenAI Gym / ALE Freeway Environment
James S. Plank, Catherine D. Schuman, Robert M. Patton
http://arxiv.org/abs/2109.01220v1
• [cs.AI]CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models
Arjun R. Akula, Keze Wang, Changsong Liu, Sari Saba-Sadiya, Hongjing Lu, Sinisa Todorovic, Joyce Chai, Song-Chun Zhu
http://arxiv.org/abs/2109.01401v1
• [cs.AI]Efficient Communication in Multi-Agent Distributed Reinforcement Learning
Daniel Jarne Ornia, Manuel Mazo Jr
http://arxiv.org/abs/2109.01417v1
• [cs.AI]Integration of Data and Theory for Accelerated Derivable Symbolic Discovery
Cristina Cornelio, Sanjeeb Dash, Vernon Austel, Tyler Josephson, Joao Goncalves, Kenneth Clarkson, Nimrod Megiddo, Bachir El Khadir, Lior Horesh
http://arxiv.org/abs/2109.01634v1
• [cs.AI]Multi-Agent Inverse Reinforcement Learning: Suboptimal Demonstrations and Alternative Solution Concepts
Sage Bergerson
http://arxiv.org/abs/2109.01178v1
• [cs.AI]Situated Conditional Reasoning
Giovanni Casini, Thomas Meyer, Ivan Varzinczak
http://arxiv.org/abs/2109.0
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1552v1
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• [cs.AI]Symbol Emergence and The Solutions to Any Task
Michael Timothy Bennett
http://arxiv.org/abs/2109.01281v1
• [cs.AR]On the Accuracy of Analog Neural Network Inference Accelerators
T. Patrick Xiao, Ben Feinberg, Christopher H. Bennett, Venkatraman Prabhakar, Prashant Saxena, Vineet Agrawal, Sapan Agarwal, Matthew J. Marinella
http://arxiv.org/abs/2109.01262v1
• [cs.CL]A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act Detection
Ting-Wei Wu, Ruolin Su, Biing-Hwang Juang
http://arxiv.org/abs/2109.01267v1
• [cs.CL]A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis
Dimitris Gkoumas, Bo Wang, Adam Tsakalidis, Maria Wolters, Arkaitz Zubiaga, Matthew Purver, Maria Liakata
http://arxiv.org/abs/2109.01537v1
• [cs.CL]An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction
Samuel Mensah, Kai Sun, Nikolaos Aletras
http://arxiv.org/abs/2109.01238v1
• [cs.CL]An Exploratory Study on Utilising the Web of Linked Data for Product Data Mining
Ziqi Zhang, Xingyi Song
http://arxiv.org/abs/2109.01411v1
• [cs.CL]An Open-Source Dataset and A Multi-Task Model for Malay Named Entity Recognition
Yingwen Fu, Nankai Lin, Zhihe Yang, Shengyi Jiang
http://arxiv.org/abs/2109.01293v1
• [cs.CL]CREAK: A Dataset for Commonsense Reasoning over Entity Knowledge
Yasumasa Onoe, Michael J. Q. Zhang, Eunsol Choi, Greg Durrett
http://arxiv.org/abs/2109.01653v1
• [cs.CL]Challenges in Generalization in Open Domain Question Answering
Linqing Liu, Patrick Lewis, Sebastian Riedel, Pontus Stenetorp
http://arxiv.org/abs/2109.01156v1
• [cs.CL]Contextualized Embeddings based Convolutional Neural Networks for Duplicate Question Identification
Harsh Sakhrani, Saloni Parekh, Pratik Ratadiya
http://arxiv.org/abs/2109.01560v1
• [cs.CL]Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation
Haoran Yang, Wai Lam, Piji Li
http://arxiv.org/abs/2109.01484v1
• [cs.CL]Cross-Lingual Training with Dense Retrieval for Document Retrieval
Peng Shi, Rui Zhang, He Bai, Jimmy Lin
http://arxiv.org/abs/2109.01628v1
• [cs.CL]Detecting Speaker Personas from Conversational Texts
Jia-Chen Gu, Zhen-Hua Ling, Yu Wu, Quan Liu, Zhigang Chen, Xiaodan Zhu
http://arxiv.org/abs/2109.01330v1
• [cs.CL]Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Albert Webson, Ellie Pavlick
http://arxiv.org/abs/2109.01247v1
• [cs.CL]Empirical Study of Named Entity Recognition Performance Using Distribution-aware Word Embedding
Xin Chen, Qi Zhao, Xinyang Liu
http://arxiv.org/abs/2109.01636v1
• [cs.CL]Entity Linking and Discovery via Arborescence-based Supervised Clustering
Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum
http://arxiv.org/abs/2109.01242v1
• [cs.CL]Establishing Interlingua in Multilingual Language Models
Maksym Del, Mark Fishel
http://arxiv.org/abs/2109.01207v1
• [cs.CL]Finetuned Language Models Are Zero-Shot Learners
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le
http://arxiv.org/abs/2109.01652v1
• [cs.CL]Indexing Context-Sensitive Reachability
Qingkai Shi, Yongchao Wang, Charles Zhang
http://arxiv.org/abs/2109.01321v1
• [cs.CL]Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT
Elena Voita, Rico Sennrich, Ivan Titov
http://arxiv.org/abs/2109.01396v1
• [cs.CL]Learning Neural Models for Natural Language Processing in the Face of Distributional Shift
Paul Michel
http://arxiv.org/abs/2109.01558v1
• [cs.CL]Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding
Yingmei Guo, Linjun Shou, Jian Pei, Ming Gong, Mingxing Xu, Zhiyong Wu, Daxin Jiang
http://arxiv.org/abs/2109.01583v1
• [cs.CL]Multimodal Conditionality for Natural Language Generation
Michael Sollami, Aashish Jain
http://arxiv.org/abs/2109.01229v1
• [cs.CL]Quantifying Reproducibility in NLP and ML
Anya Belz
http://arxiv.org/abs/2109.01211v1
• [cs.CL]Ranking Scientific Papers Using Preference Learning
Nils Dycke, Edwin Simpson, Ilia Kuznetsov, Iryna Gurevych
http://arxiv.org/abs/2109.01190v1
• [cs.CL]So Cloze yet so Far: N400 Amplitude is Better Predicted by Distributional Information than Human Predictability Judgements
James A. Michaelov, Seana Coulson, Benjamin K. Bergen
http://arxiv.org/abs/2109.01226v1
• [cs.CR]A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples
Guanxiong Liu, Issa Khalil, Abdallah Khreishah, NhatHai Phan
http://arxiv.org/abs/2109.01275v1
• [cs.CR]Ontology-driven Knowledge Graph for Android Malware
Ryan Christian, Sharmishtha Dutta, Youngja Park, Nidhi Rastogi
http://arxiv.org/abs/2109.01544v1
• [cs.CV]3D Human Shape Style Transfer
Joao Regateiro, Edmond Boyer
http://arxiv.org/abs/2109.01587v1
• [cs.CV]Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models
Hiroki Ito, MaungMaung AprilPyone, Hitoshi Kiya
http://arxiv.org/abs/2109.01332v1
• [cs.CV]CAP-Net: Correspondence-Aware Point-view Fusion Network for 3D Shape Analysis
Xinwei He, Silin Cheng, Song Bai, Xiang Bai
http://arxiv.org/abs/2109.01291v1
• [cs.CV]Deep Learning for Fitness
Mahendran N
http://arxiv.org/abs/2109.01376v1
• [cs.CV]Deep Metric Learning for Ground Images
Raaghav Radhakrishnan, Jan Fabian Schmid, Randolf Scholz, Lars Schmidt-Thieme
http://arxiv.org/abs/2109.01569v1
• [cs.CV]Dual-Camera Super-Resolution with Aligned Attention Modules
Tengfei Wang, Jiaxin Xie, Wenxiu Sun, Qiong Yan, Qifeng Chen
http://arxiv.org/abs/2109.01349v1
• [cs.CV]Ghost Loss to Question the Reliability of Training Data
Adrien Deliège, Anthony Cioppa, Marc Van Droogenbroeck
http://arxiv.org/abs/2109.01504v1
• [cs.CV]Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning
Zhong Ji, Zhishen Hou, Xiyao Liu, Yanwei Pang, Jungong Han
http://arxiv.org/abs/2109.01295v1
• [cs.CV]MitoVis: A Visually-guided Interactive Intelligent System for Neuronal Mitochondria Analysis
JunYoung Choi, Hakjun Lee, Suyeon Kim, Seok-Kyu Kwon, Won-Ki Jeong
http://arxiv.org/abs/2109.01351v1
• [cs.CV]Model-Based Parameter Optimization for Ground Texture Based Localization Methods
Jan Fabian Schmid, Stephan F. Simon, Rudolf Mester
http://arxiv.org/abs/2109.01559v1
• [cs.CV]Neural Human Deformation Transfer
Jean Basset, Adnane Boukhayma, Stefanie Wuhrer, Franck Multon, Edmond Boyer
http://arxiv.org/abs/2109.01588v1
• [cs.CV]Occlusion-Invariant Rotation-Equivariant Semi-Supervised Depth Based Cross-View Gait Pose Estimation
Xiao Gu, Jianxin Yang, Hanxiao Zhang, Jianing Qiu, Frank Po Wen Lo, Yao Guo, Guang-Zhong Yang, Benny Lo
http://arxiv.org/abs/2109.01397v1
• [cs.CV]Optimal Target Shape for LiDAR Pose Estimation
Jiunn-Kai Huang, William Clark, Jessy W. Grizzle
http://arxiv.org/abs/2109.01181v1
• [cs.CV]Ordinal Pooling
Adrien Deliège, Maxime Istasse, Ashwani Kumar, Christophe De Vleeschouwer, Marc Van Droogenbroeck
http://arxiv.org/abs/2109.01561v1
• [cs.CV]Representing Shape Collections with Alignment-Aware Linear Models
Romain Loiseau, Tom Monnier, Loïc Landrieu, Mathieu Aubry
http://arxiv.org/abs/2109.01605v1
• [cs.CV]Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
Xuanchi Ren, Tao Yang, Li Erran Li, Alexandre Alahi, Qifeng Chen
http://arxiv.org/abs/2109.01510v1
• [cs.CV]Segmentation of turbulent computational fluid dynamics simulations with unsupervised ensemble learning
Maarja Bussov, Joonas Nättilä
http://arxiv.org/abs/2109.01381v1
• [cs.CV]Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decomposition
Xiyao Liu, Zhong Ji, Yanwei Pang, Zhongfei Zhang
http://arxiv.org/abs/2109.01302v1
• [cs.CV]Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models
Zixuan Chen, Junhong Zou, Xiaotao Wang
http://arxiv.org/abs/2109.01316v1
• [cs.CV]Spatially varying white balancing for mixed and non-uniform illuminants
Teruaki Akazawa, Yuma Kinoshita, Hitoshi Kiya
http://arxiv.org/abs/2109.01350v1
• [cs.CV]Towards Learning Spatially Discriminative Feature Representations
Chaofei Wang, Jiayu Xiao, Yizeng Han, Qisen Yang, Shiji Song, Gao Huang
http://arxiv.org/abs/2109.01359v1
• [cs.CV]UnDeepLIO: Unsupervised Deep Lidar-Inertial Odometry
Yiming Tu, Jin Xie
http://arxiv.org/abs/2109.01533v1
• [cs.CV]Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks
Yogesh Kochar, Sunil Kumar Vengalil, Neelam Sinha
http://arxiv.org/abs/2109.01572v1
• [cs.CV]Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition
James Hong, Matthew Fisher, Michaël Gharbi, Kayvon Fatahalian
http://arxiv.org/abs/2109.01305v1
• [cs.CV]Wildfire smoke plume segmentation using geostationary satellite imagery
Jeff Wen, Marshall Burke
http://arxiv.org/abs/2109.01637v1
• [cs.CY]Hide and seek in Slovakia: utilizing tracking code data to uncover untrustworthy website networks
Jozef Michal Mintal, Michal Kalman, Karol Fabián
http://arxiv.org/abs/2109.01527v1
• [cs.CY]Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning
Snehalkumar, S. Gaikwad, Shankar Iyer, Dalton Lunga, Elizabeth Bondi
http://arxiv.org/abs/2109.00100v3
• [cs.DC]A Reliable, Self-Adaptive Face Identification Framework via Lyapunov Optimization
Dohyeon Kim, Joongheon Kim, Jae young Bang
http://arxiv.org/abs/2109.01212v1
• [cs.DC]A Study of Mixed Precision Strategies for GMRES on GPUs
Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam
http://arxiv.org/abs/2109.01232v1
• [cs.DC]Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability
Vincent R. Pascuzzi, Mehdi Goli
http://arxiv.org/abs/2109.01329v1
• [cs.DC]Byzantine Consensus in Directed Hypergraphs
Muhammad Samir Khan, Nitin H. Vaidya
http://arxiv.org/abs/2109.01205v1
• [cs.DC]Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters
Hu, Qinghao, Sun, Peng, Yan, Shengen, Wen, Yonggang, Zhang, Tianwei
http://arxiv.org/abs/2109.01313v1
• [cs.DC]Continuous Tasks and the Chromatic Simplicial Approximation Theorem
Hugo Rincon Galeana, Sergio Rajsbaum, Ulrich Schmid
http://arxiv.org/abs/2109.01439v1
• [cs.DC]ECO: Edge-Cloud Optimization of 5G applications
Kunal Rao, Giuseppe Coviello, Wang-Pin Hsiung, Srimat Chakradhar
http://arxiv.org/abs/2109.01201v1
• [cs.DC]Enabling Reproducible Analysis of Complex Workflows on the Edge-to-Cloud Continuum
Daniel Rosendo, Alexandru Costan, Gabriel Antoniu, Patrick Valduriez
http://arxiv.org/abs/2109.01379v1
• [cs.DC]Fast Abstracts and Student Forum Proceedings, 17th European Dependable Computing Conference — EDCC 2021
Marcello Cinque, Barbara Gallina
http://arxiv.org/abs/2109.00465v2
• [cs.DC]FedApp: a Research Sandbox for Application Orchestration in Federated Clouds using OpenStack
Johan Ruuskanen, Haorui Peng, Alfred Åkesson, Lars Larsson, Maria Kihl
http://arxiv.org/abs/2109.01480v1
• [cs.HC]A Multi-Sensor Interface to Improve the Teaching and Learning Experience in Arc Welding Training Tasks
Hoi-Yin Lee, Peng Zhou, Victor Wu, David Navarro-Alarcon
http://arxiv.org/abs/2109.01383v1
• [cs.HC]The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
Riccardo Fogliato, Alexandra Chouldechova, Zachary Lipton
http://arxiv.org/abs/2109.01443v1
• [cs.IR]UserBERT: Contrastive User Model Pre-training
Chuhan Wu, Fangzhao Wu, Yang Yu, Tao Qi, Yongfeng Huang, Xing Xie
http://arxiv.org/abs/2109.01274v1
• [cs.IT]A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access
Vaibhav Kumar, Muhammad Fainan Hanif, Markku Juntti, Le-Nam Tran
http://arxiv.org/abs/2109.01239v1
• [cs.IT]Low-Latency and Secure Computation Offloading Assisted by Hybrid Relay-Reflecting Intelligent Surface
Khac-Hoang Ngo, Nhan Thanh Nguyen, Thinh Quang Dinh, Trong-Minh Hoang, Markku Juntti
http://arxiv.org/abs/2109.01335v1
• [cs.IT]Optimizing the Energy Efficiency of Unreliable Memories for Quantized Kalman Filtering
Jonathan Kern, Elsa Dupraz, Abdeldjalil Aïssa-El-Bey, Lav R. Varshney, François Leduc-Primeau
http://arxiv.org/abs/2109.01520v1
• [cs.IT]Scalar Gaussian Wiretap Channel: Properties of the Support Size of the Secrecy-Capacity-Achieving Distribution
Luca Barletta, Alex Dytso
http://arxiv.org/abs/2109.01566v1
• [cs.IT]Secrecy Performance of α-κ-μ Shadowed Fading Channel
A. S. M. Badrudduza, S. H. Islam, M. K. Kundu, I. S. Ansari
http://arxiv.org/abs/2109.01407v1
• [cs.IT]Secure Source Coding with Side-information at Decoder and Shared Key at Encoder and Decoder
Hamid Ghourchian, Photios A. Stavrou, Tobias J. Oechtering, Mikael Skoglund
http://arxiv.org/abs/2109.01613v1
• [cs.LG]A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithms
Xuetong Wu, Jonathan H. Manton, Uwe Aickelin, Jingge Zhu
http://arxiv.org/abs/2109.01377v1
• [cs.LG]A New Approach to Multilabel Stratified Cross Validation with Application to Large and Sparse Gene Ontology Datasets
Henri Tiittanen, Liisa Holm, Petri Törönen
http://arxiv.org/abs/2109.01425v1
• [cs.LG]Biomedical Data-to-Text Generation via Fine-Tuning Transformers
Ruslan Yermakov, Nicholas Drago, Angelo Ziletti
http://arxiv.org/abs/2109.01518v1
• [cs.LG]Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms
Bemali Wickramanayake, Zhipeng He, Chun Ouyang, Catarina Moreira, Yue Xu, Renuka Sindhgatta
http://arxiv.org/abs/2109.01419v1
• [cs.LG]Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry
Ji Yang, Lu Sang, Daniel Cremers
http://arxiv.org/abs/2109.01461v1
• [cs.LG]Edge-featured Graph Neural Architecture Search
Shaofei Cai, Liang Li, Xinzhe Han, Zheng-jun Zha, Qingming Huang
http://arxiv.org/abs/2109.01356v1
• [cs.LG]Estimating Demand Flexibility Using Siamese LSTM Neural Networks
Guangchun Ruan, Daniel S. Kirschen, Haiwang Zhong, Qing Xia, Chongqing Kang
http://arxiv.org/abs/2109.01258v1
• [cs.LG]How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
Zhiyuan Zhang, Lingjuan Lyu, Weiqiang Wang, Lichao Sun, Xu Sun
http://arxiv.org/abs/2109.01300v1
• [cs.LG]Impact of GPU uncertainty on the training of predictive deep neural networks
Maciej Pietrowski, Andrzej Gajda, Takuto Yamamoto, Taisuke Kobayashi, Lana Sinapayen, Eiji Watanabe
http://arxiv.org/abs/2109.01451v1
• [cs.LG]Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation
Jiahui Li, Kun Kuang, Lin Li, Long Chen, Songyang Zhang, Jian Shao, Jun Xiao
http://arxiv.org/abs/2109.01369v1
• [cs.LG]Investigate the Correlation of Breast Cancer Dataset using Different Clustering Technique
Somenath Chakraborty, Beddhu Murali
http://arxiv.org/abs/2109.01538v1
• [cs.LG]J-Score: A Robust Measure of Clustering Accuracy
Navid Ahmadinejad, Li Liu
http://arxiv.org/abs/2109.01306v1
• [cs.LG]LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
Maximilian Stubbemann, Gerd Stumme
http://arxiv.org/abs/2109.01479v1
• [cs.LG]Large-Scale Learning with Fourier Features and Tensor Decompositions
Frederiek Wesel, Kim Batselier
http://arxiv.org/abs/2109.01545v1
• [cs.LG]LightAutoML: AutoML Solution for a Large Financial Services Ecosystem
Anton Vakhrushev, Alexander Ryzhkov, Maxim Savchenko, Dmitry Simakov, Rinchin Damdinov, Alexander Tuzhilin
http://arxiv.org/abs/2109.01528v1
• [cs.LG]Multi-agent Natural Actor-critic Reinforcement Learning Algorithms
Prashant Trivedi, Nandyala Hemachandra
http://arxiv.org/abs/2109.01654v1
• [cs.LG]Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems
Bo Sun, Russell Lee, Mohammad Hajiesmaili, Adam Wierman, Danny H. K. Tsang
http://arxiv.org/abs/2109.01556v1
• [cs.LG]Provably Safe Model-Based Meta Reinforcement Learning: An Abstraction-Based Approach
Xiaowu Sun, Wael Fatnassi, Ulices Santa Cruz, Yasser Shoukry
http://arxiv.org/abs/2109.01255v1
• [cs.LG]Stochastic Physics-Informed Neural Networks (SPINN): A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equations
Jared O’Leary, Joel A. Paulson, Ali Mesbah
http://arxiv.org/abs/2109.01621v1
• [cs.LG]Topographic VAEs learn Equivariant Capsules
T. Anderson Keller, Max Welling
http://arxiv.org/abs/2109.01394v1
• [cs.NI]Is Machine Learning Ready for Traffic Engineering Optimization?
Guillermo Bernárdez, José Suárez-Varela, Albert López, Bo Wu, Shihan Xiao, Xiangle Cheng, Pere Barlet-Ros, Albert Cabellos-Aparicio
http://arxiv.org/abs/2109.01445v1
• [cs.RO]A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight
Sihao Sun, Angel Romero, Philipp Foehn, Elia Kaufmann, Davide Scaramuzza
http://arxiv.org/abs/2109.01365v1
• [cs.RO]Invariant Filtering for Bipedal Walking on Dynamic Rigid Surfaces with Orientation-based Measurement Model
Yuan Gao, Yan Gu
http://arxiv.org/abs/2109.01241v1
• [cs.RO]Iterative Imitation Policy Improvement for Interactive Autonomous Driving
Zhao-Heng Yin, Chenran Li, Liting Sun, Masayoshi Tomizuka, Wei Zhan
http://arxiv.org/abs/2109.01288v1
• [cs.RO]Mechanical Chameleons: Evaluating the effects of a social robot’s non-verbal behavior on social influence
Patrik Jonell, Anna Deichler, Ilaria Torre, Iolanda Leite, Jonas Beskow
http://arxiv.org/abs/2109.01206v1
• [cs.RO]On the similarities between Control Barrier Functions (CBFs) and Behavior Control Lyapunov Functions (BCLFs)
Petter Ögren
http://arxiv.org/abs/2109.01343v1
• [cs.RO]Real-Time Volumetric-Semantic Exploration and Mapping: An Uncertainty-Aware Approach
Rui Pimentel de Figueiredo, Jonas le Fevre Sejersen, Jakob Grimm Hansen, Martim Brandão, Erdal Kayacan
http://arxiv.org/abs/2109.01474v1
• [cs.RO]Theory of Mind Based Assistive Communication in Complex Human Robot Cooperation
Moritz C. Buehler, Jürgen Adamy, Thomas H. Weisswange
http://arxiv.org/abs/2109.01355v1
• [cs.SI]Neural PathSim for Inductive Similarity Search in Heterogeneous Information Networks
Wenyi Xiao, Huan Zhao, Vincent W. Zheng, Yangqiu Song
http://arxiv.org/abs/2109.01549v1
• [eess.IV]Automatic Foot Ulcer segmentation Using an Ensemble of Convolutional Neural Networks
Amirreza Mahbod, Rupert Ecker, Isabella Ellinger
http://arxiv.org/abs/2109.01408v1
• [eess.IV]Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction
Peichao Li, Michael Ebner, Philip Noonan, Conor Horgan, Anisha Bahl, Sebastien Ourselin, Jonathan Shapey, Tom Vercauteren
http://arxiv.org/abs/2109.01403v1
• [eess.IV]Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation
Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro
http://arxiv.org/abs/2109.01303v1
• [eess.IV]Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imaging
Roshan P Mathews, Mahesh Raveendranatha Panicker, Abhilash R Hareendranathan, Yale Tung Chen, Jacob L Jaremko, Brian Buchanan, Kiran Vishnu Narayan, Kesavadas C, Greeta Mathews
http://arxiv.org/abs/2109.01309v1
• [eess.SP]Ground-Assisted Federated Learning in LEO Satellite Constellations
Nasrin Razmi, Bho Matthiesen, Armin Dekorsy, Petar Popovski
http://arxiv.org/abs/2109.01348v1
• [eess.SY]Continuous-Time Behavior Trees as Discontinuous Dynamical Systems
Christopher Iliffe Sprague, Petter Ögren
http://arxiv.org/abs/2109.01575v1
• [math.NA]Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations
Suprosanna Shit, Ivan Ezhov, Leon Mächler, Abinav R., Jana Lipkova, Johannes C. Paetzold, Florian Kofler, Marie Piraud, Bjoern H. Menze
http://arxiv.org/abs/2109.01467v1
• [math.ST]Is the mode elicitable relative to unimodal distributions?
Claudio Heinrich-Mertsching, Tobias Fissler
http://arxiv.org/abs/2109.00464v2
• [physics.flu-dyn]Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows
Hamidreza Eivazi, Soledad Le Clainche, Sergio Hoyas, Ricardo Vinuesa
http://arxiv.org/abs/2109.01514v1
• [physics.soc-ph]COVID-19 Vaccine Hesitancy and Information Diffusion: An Agent-based Modeling Approach
Pooria Taghizadeh Naderi, Ali Asgary, Jude Kong, Jianhong Wu, Fattaneh Taghiyareh
http://arxiv.org/abs/2109.01182v1
• [physics.soc-ph]Universality, criticality and complexity of information propagation in social media
Daniele Notarmuzi, Claudio Castellano, Alessandro Flammini, Dario Mazzilli, Filippo Radicchi
http://arxiv.org/abs/2109.00116v1
• [stat.AP]Epidemic Models for COVID-19 during the First Wave from February to May 2020: a Methodological Review
Marie Garin, Myrto Limnios, Alice Nicolaï, Ioannis Bargiotas, Olivier Boulant, Stephen Chick, Amir Dib, Theodoros Evgeniou, Mathilde Fekom, Argyris Kalogeratos, Christophe Labourdette, Anton Ovchinnikov, Raphaël Porcher, Camille Pouchol, Nicolas Vayatis
http://arxiv.org/abs/2109.01450v1
• [stat.AP]Evaluating the Use of Generalized Dynamic Weighted Ordinary Least Squares for Individualized HIV Treatment Strategies
Larry Dong, Erica E. M. Moodie, Laura Villain, Rodolphe Thiébaut
http://arxiv.org/abs/2109.01218v1
• [stat.AP]Frequency-Severity Experience Rating based on Latent Markovian Risk Profiles
Robert Matthijs Verschuren
http://arxiv.org/abs/2109.01413v1
• [stat.AP]Simultaneous quantification and changepoint detection of point source gas emissions using recursive Bayesian inference
Amir Montazeri, Xiaochi Zhou, John D. Albertson
http://arxiv.org/abs/2109.01603v1
• [stat.AP]Teacher Mental Health During the COVID-19 Pandemic: Informing Policies to Support Teacher Well-being and Effective Teaching Practices
Joseph M. Kush, Elena Badillo-Goicoechea, Rashelle J. Musci, Elizabeth A. Stuart
http://arxiv.org/abs/2109.01547v1
• [stat.AP]Two Shifts for Crop Mapping: Leveraging Aggregate Crop Statistics to Improve Satellite-based Maps in New Regions
Dan M. Kluger, Sherrie Wang, David B. Lobell
http://arxiv.org/abs/2109.01246v1
• [stat.ME]Regularized tapered sample covariance matrix
Esa Ollila, Arnaud Breloy
http://arxiv.org/abs/2109.01353v1
• [stat.ME]Robust confidence distributions from proper scoring rules
Erlis Ruli, Laura Ventura, Monica Musio
http://arxiv.org/abs/2109.01219v1
• [stat.ME]Variational Bayes algorithm and posterior consistency of Ising model parameter estimation
Minwoo Kim, Shrijita Bhattacharya, Tapabrata Maiti
http://arxiv.org/abs/2109.01548v1
• [stat.ML]Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process
Christoph Molnar, Timo Freiesleben, Gunnar König, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl
http://arxiv.org/abs/2109.01433v1
• [stat.ML]Sample Noise Impact on Active Learning
Alexandre Abraham, Léo Dreyfus-Schmidt
http://arxiv.org/abs/2109.01372v1
• [stat.ML]Statistical Estimation and Inference via Local SGD in Federated Learning
Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang
http://arxiv.org/abs/2109.01326v1