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.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.SD - 声音处理
cs.SI - 社交网络与信息网络
eess.SP - 信号处理
math.ST - 统计理论
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
• [cs.AI]ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero
• [cs.AI]NAIL: A General Interactive Fiction Agent
• [cs.AI]VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems
• [cs.CL]BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model
• [cs.CL]Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops
• [cs.CL]Table2answer: Read the database and answer without SQL
• [cs.CR]Adversarial Samples on Android Malware Detection Systems for IoT Systems
• [cs.CR]Asymptotic Performance Analysis of Blockchain Protocols
• [cs.CR]Examining Adversarial Learning against Graph-based IoT Malware Detection Systems
• [cs.CR]Mind the Mining
• [cs.CR]TensorSCONE: A Secure TensorFlow Framework using Intel SGX
• [cs.CR]Verification Code Recognition Based on Active and Deep Learning
• [cs.CV]A system for generating complex physically accurate sensor images for automotive applications
• [cs.CV]Bag of Freebies for Training Object Detection Neural Networks
• [cs.CV]Brain MRI Segmentation using Rule-Based Hybrid Approach
• [cs.CV]Center of circle after perspective transformation
• [cs.CV]De-identification without losing faces
• [cs.CV]Enhancement Mask for Hippocampus Detection and Segmentation
• [cs.CV]Extended 2D Volumetric Consensus Hippocampus Segmentation
• [cs.CV]Fast-SCNN: Fast Semantic Segmentation Network
• [cs.CV]GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation
• [cs.CV]Learning to Authenticate with Deep Multibiometric Hashing and Neural Network Decoding
• [cs.CV]MASC: Multi-scale Affinity with Sparse Convolution for 3D Instance Segmentation
• [cs.CV]Manifestation of Image Contrast in Deep Networks
• [cs.CV]Max-C and Min-D Projection Autoassociative Fuzzy Morphological Memories: Theory and Applications for Face Recognition
• [cs.CV]Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation
• [cs.CV]ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing
• [cs.CV]Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold
• [cs.CV]Synthesizing New Retinal Symptom Images by Multiple Generative Models
• [cs.CV]The effect of scene context on weakly supervised semantic segmentation
• [cs.CV]Using Deep Cross Modal Hashing and Error Correcting Codes for Improving the Efficiency of Attribute Guided Facial Image Retrieval
• [cs.CV]You Only Look & Listen Once: Towards Fast and Accurate Visual Grounding
• [cs.CY]Coloring in the Links: Capturing Social Ties as They are Perceived
• [cs.DC]Distributed and Application-aware Task Scheduling in Edge-clouds
• [cs.DC]Performance of All-Pairs Shortest-Paths Solvers with Apache Spark
• [cs.IR]A Domain Generalization Perspective on Listwise Context Modeling
• [cs.IR]Cross-Modal Music Retrieval and Applications: An Overview of Key Methodologies
• [cs.IR]Reading Protocol: Understanding what has been Read in Interactive Information Retrieval Tasks
• [cs.IT]A Class of Narrow-Sense BCH Codes
• [cs.IT]An Enhanced SDR based Global Algorithm for Nonconvex Complex Quadratic Programs with Signal Processing Applications
• [cs.IT]Beamwidth Control for NOMA in Hybrid mmWave Communication Systems
• [cs.IT]Can Massive MIMO Support Uplink Intensive Applications?
• [cs.IT]IEEE 802.11be Extremely High Throughput: The Next Generation of Wi-Fi Technology Beyond 802.11ax
• [cs.IT]On Conflict Free DNA Codes
• [cs.IT]SLNR Based Precoding for One-Bit Quantized Massive MIMO in mmWave Communications
• [cs.LG]A Probabilistic Framework to Node-level Anomaly Detection in Communication Networks
• [cs.LG]A Theory of Selective Prediction
• [cs.LG]A simple and efficient architecture for trainable activation functions
• [cs.LG]ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning
• [cs.LG]An In-Vehicle KWS System with Multi-Source Fusion for Vehicle Applications
• [cs.LG]Bayesian Online Detection and Prediction of Change Points
• [cs.LG]Binary Stochastic Filtering: a Solution for Supervised Feature Selection and Neural Network Shape Optimization
• [cs.LG]Capacity allocation analysis of neural networks: A tool for principled architecture design
• [cs.LG]Deep Reinforcement Learning from Policy-Dependent Human Feedback
• [cs.LG]Density Estimation and Incremental Learning of Latent Vector for Generative Autoencoders
• [cs.LG]Divergence-Based Motivation for Online EM and Combining Hidden Variable Models
• [cs.LG]Domain Constraint Approximation based Semi Supervision
• [cs.LG]Effective Network Compression Using Simulation-Guided Iterative Pruning
• [cs.LG]Gaussian Mean Field Regularizes by Limiting Learned Information
• [cs.LG]Hyperbolic Disk Embeddings for Directed Acyclic Graphs
• [cs.LG]Improving learnability of neural networks: adding supplementary axes to disentangle data representation
• [cs.LG]Infinite Mixture Prototypes for Few-Shot Learning
• [cs.LG]LS-Tree: Model Interpretation When the Data Are Linguistic
• [cs.LG]MaCow: Masked Convolutional Generative Flow
• [cs.LG]Multi-objective Bayesian optimisation with preferences over objectives
• [cs.LG]Nearest Neighbor Median Shift Clustering for Binary Data
• [cs.LG]Net2Vis: Transforming Deep Convolutional Networks into Publication-Ready Visualizations
• [cs.LG]PAC-Bayes Analysis of Sentence Representation
• [cs.LG]Performance Dynamics and Termination Errors in Reinforcement Learning: A Unifying Perspective
• [cs.LG]Post-Data Augmentation to Improve Deep Pose Estimation of Extreme and Wild Motions
• [cs.LG]Preferences Implicit in the State of the World
• [cs.LG]Stochastic Reinforcement Learning
• [cs.LG]Thompson Sampling with Information Relaxation Penalties
• [cs.LG]Towards Self-Supervised High Level Sensor Fusion
• [cs.LG]VC Classes are Adversarially Robustly Learnable, but Only Improperly
• [cs.LG]WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving
• [cs.NE]Guiding Neuroevolution with Structural Objectives
• [cs.NE]On Residual Networks Learning a Perturbation from Identity
• [cs.NI]A Novel Communication Cost Aware Load Balancing in Content Delivery Networks using Honeybee Algorithm
• [cs.RO]Evolving Robots on Easy Mode: Towards a Variable Complexity Controller for Quadrupeds
• [cs.RO]VIZARD: Reliable Visual Localization for Autonomous Vehicles in Urban Outdoor Environments
• [cs.SD]Adversarial Generation of Time-Frequency Features with application in audio synthesis
• [cs.SI]An Analysis of United States Online Political Advertising Transparency
• [cs.SI]Asymptotic resolution bounds of generalized modularity and statistically significant community detection
• [cs.SI]Meta Diagram based Active Social Networks Alignment
• [cs.SI]RTbust: Exploiting Temporal Patterns for Botnet Detection on Twitter
• [cs.SI]WikiLinkGraphs: A complete, longitudinal and multi-language dataset of the Wikipedia link networks
• [eess.SP]Helping Blind People in Their Meeting Locations to Find Each Other Using RFID Technology
• [eess.SP]Inter-Node Distance Estimation from Multipath Delay Differences of Channels to Observer Nodes
• [eess.SP]RespNet: A deep learning model for extraction of respiration from photoplethysmogram
• [math.ST]Elicitability of Range Value at Risk
• [math.ST]Maximum Likelihood Estimation for Learning Populations of Parameters
• [math.ST]Optimal BIBD-extended designs
• [math.ST]Quickest Change Detection in the Presence of a Nuisance Change
• [math.ST]Statistical inference with F-statistics when fitting simple models to high-dimensional data
• [physics.soc-ph]Wikipedia and Digital Currencies: Interplay Between Collective Attention and Market Performance
• [stat.AP]Achieving GWAS with Homomorphic Encryption
• [stat.AP]Bayesian Inference of a Finite Population Mean Under Length-Biased Sampling
• [stat.AP]Non-Linear Non-Stationary Heteroscedasticity Volatility for Tracking of Jump Processes
• [stat.AP]Winning the Big Data Technologies Horizon Prize: Fast and reliable forecasting of electricity grid traffic by identification of recurrent fluctuations
• [stat.ME]A quantile-based g-computation approach to addressing the effects of exposure mixtures
• [stat.ME]Bayesian cumulative shrinkage for infinite factorizations
• [stat.ML]A Problem-Adaptive Algorithm for Resource Allocation
• [stat.ML]Joint Training of Neural Network Ensembles
• [stat.ML]Learning interpretable continuous-time models of latent stochastic dynamical systems
• [stat.ML]Sparse Feature Selection in Kernel Discriminant Analysis via Optimal Scoring
• [stat.ML]The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy
• [stat.ML]Using Embeddings to Correct for Unobserved Confounding
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