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.DL - 数字图书馆 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 math.PR - 概率 math.ST - 统计理论 q-bio.TO - 组织和器官 q-fin.ST - 统计金融学 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]Few-Shot Bayesian Imitation Learning with Logic over Programs
• [cs.CL]A Crowdsourced Frame Disambiguation Corpus with Ambiguity
• [cs.CL]Adapting Sequence to Sequence models for Text Normalization in Social Media
• [cs.CL]Building a mixed-lingual neural TTS system with only monolingual data
• [cs.CL]CITE: A Corpus of Image—Text Discourse Relations
• [cs.CL]Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation
• [cs.CL]Direct speech-to-speech translation with a sequence-to-sequence model
• [cs.CL]Evaluating the Representational Hub of Language and Vision Models
• [cs.CL]FrameRank: A Text Processing Approach to Video Summarization
• [cs.CL]IIT (BHU) Varanasi at MSR-SRST 2018: A Language Model Based Approach for Natural Language Generation
• [cs.CL]Modeling Interpersonal Linguistic Coordination in Conversations using Word Mover’s Distance
• [cs.CL]Political Text Scaling Meets Computational Semantics
• [cs.CL]Strong Baselines for Complex Word Identification across Multiple Languages
• [cs.CR]Generating Minimal Adversarial Perturbations with Integrated Adaptive Gradients
• [cs.CV]A Light Dual-Task Neural Network for Haze Removal
• [cs.CV]A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids
• [cs.CV]ACE: Adapting to Changing Environments for Semantic Segmentation
• [cs.CV]Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology
• [cs.CV]An Empirical Evaluation Study on the Training of SDC Features for Dense Pixel Matching
• [cs.CV]An Introduction to Person Re-identification with Generative Adversarial Networks
• [cs.CV]Big but Imperceptible Adversarial Perturbations via Semantic Manipulation
• [cs.CV]Cramnet: Layer-wise Deep Neural Network Compression with Knowledge Transfer from a Teacher Network
• [cs.CV]Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense
• [cs.CV]Digging Deeper into Egocentric Gaze Prediction
• [cs.CV]EvalNorm: Estimating Batch Normalization Statistics for Evaluation
• [cs.CV]Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks
• [cs.CV]Face De-occlusion using 3D Morphable Model and Generative Adversarial Network
• [cs.CV]Generalized Presentation Attack Detection: a face anti-spoofing evaluation proposal
• [cs.CV]Generative Hybrid Representations for Activity Forecasting with No-Regret Learning
• [cs.CV]GeoCapsNet: Aerial to Ground view Image Geo-localization using Capsule Network
• [cs.CV]Incremental multi-domain learning with network latent tensor factorization
• [cs.CV]MAANet: Multi-view Aware Attention Networks for Image Super-Resolution
• [cs.CV]Multi-View Region Adaptive Multi-temporal DMM and RGB Action Recognition
• [cs.CV]Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data
• [cs.CV]PWOC-3D: Deep Occlusion-Aware End-to-End Scene Flow Estimation
• [cs.CV]Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation
• [cs.CV]Real-Time Dense Stereo Embedded in A UAV for Road Inspection
• [cs.CV]TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning
• [cs.CV]The Sound of Motions
• [cs.CV]The iWildCam 2018 Challenge Dataset
• [cs.CV]Unifying Heterogeneous Classifiers with Distillation
• [cs.CV]Unsupervised Method to Localize Masses in Mammograms
• [cs.CY]Towards Formalizing the GDPR’s Notion of Singling Out
• [cs.DC]FECBench: A Holistic Interference-aware Approach for Application Performance Modeling
• [cs.DC]Fast and Resource Competitive Broadcast in Multi-channel Radio Networks
• [cs.DC]On Byzantine Fault Tolerance in Multi-Master Kubernertes Clusters
• [cs.DC]Parallel parametric linear programming solving, and application to polyhedral computations
• [cs.DC]Survey of Major Load Balancing Algorithms in Distributed System
• [cs.DC]ezBFT: Decentralizing Byzantine Fault-Tolerant State Machine Replication
• [cs.DL]Female scholars need to achieve more for equal public recognition
• [cs.IT]An Explicit Rate-Optimal Streaming Code for Channels with Burst and Arbitrary Erasures
• [cs.IT]On the Asymptotic Capacity of $X$-Secure $T$-Private Information Retrieval with Graph Based Replicated Storage
• [cs.IT]Optimal Caching Designs for Perfect, Imperfect and Unknown File Popularity Distributions in Large-Scale Multi-Tier Wireless Networks
• [cs.IT]Parity-Based Concurrent Error Detection Schemes for the ChaCha Stream Cipher
• [cs.IT]When does OMP achieves support recovery with continuous dictionaries?
• [cs.LG]A streaming feature-based compression method for data from instrumented infrastructure
• [cs.LG]AMS-SFE: Towards an Alignment of Manifold Structures via Semantic Feature Expansion for Zero-shot Learning
• [cs.LG]Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks
• [cs.LG]Compressing deep neural networks by matrix product operators
• [cs.LG]Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch
• [cs.LG]Distributed Bandit Learning: How Much Communication is Needed to Achieve (Near) Optimal Regret
• [cs.LG]Distributed Layer-Partitioned Training for Privacy-Preserved Deep Learning
• [cs.LG]Effective Scheduling Function Design in SDN through Deep Reinforcement Learning
• [cs.LG]Interaction-aware Decision Making with Adaptive Strategies under Merging Scenarios
• [cs.LG]Learning Optimal Decision Trees from Large Datasets
• [cs.LG]Let’s Play Again: Variability of Deep Reinforcement Learning Agents in Atari Environments
• [cs.LG]Multi-Armed Bandit for Energy-Efficient and Delay-Sensitive Edge Computing in Dynamic Networks with Uncertainty
• [cs.LG]Multimodal Speech Emotion Recognition and Ambiguity Resolution
• [cs.LG]Position-Aware Convolutional Networks for Traffic Prediction
• [cs.LG]Ranking-Based Autoencoder for Extreme Multi-label Classification
• [cs.LG]Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout
• [cs.LG]Revisit Lmser and its further development based on convolutional layers
• [cs.LG]Robust Coreset Construction for Distributed Machine Learning
• [cs.LG]Similarities between policy gradient methods (PGM) in Reinforcement learning (RL) and supervised learning (SL)
• [cs.LG]Spatio-Temporal Deep Graph Infomax
• [cs.LG]The coupling effect of Lipschitz regularization in deep neural networks
• [cs.LG]Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders
• [cs.LG]Variational AutoEncoder For Regression: Application to Brain Aging Analysis
• [cs.LG]Variational Inference for Computational Imaging Inverse Problems
• [cs.NE]A Reference Vector based Many-Objective Evolutionary Algorithm with Feasibility-aware Adaptation
• [cs.NE]Evolved Art with Transparent, Overlapping, and Geometric Shapes
• [cs.NE]Evolving Indoor Navigational Strategies Using Gated Recurrent Units In NEAT
• [cs.NE]Locally Connected Spiking Neural Networks for Unsupervised Feature Learning
• [cs.NE]On the Impact of the Cutoff Time on the Performance of Algorithm Configurators
• [cs.RO]AI-IMU Dead-Reckoning
• [cs.RO]On the Calibration of Force/Torque Sensors in Robotics
• [cs.SD]Assisted Sound Sample Generation with Musical Conditioning in Adversarial Auto-Encoders
• [cs.SD]STC Speaker Recognition Systems for the VOiCES From a Distance Challenge
• [cs.SI]STAND: A Spatio-Temporal Algorithm for Network Diffusion Simulation
• [eess.AS]Examining the Mapping Functions of Denoising Autoencoders in Music Source Separation
• [eess.AS]Unsupervised Speech Domain Adaptation Based on Disentangled Representation Learning for Robust Speech Recognition
• [eess.IV]Boundary-Preserved Deep Denoising of the Stochastic Resonance Enhanced Multiphoton Images
• [math.PR]Community Detection in the Sparse Hypergraph Stochastic Block Model
• [math.ST]Outlier-robust estimation of a sparse linear model using $\ell_1$-penalized Huber’s $M$-estimator
• [q-bio.TO]Interpretable Classification from Skin Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study
• [q-fin.ST]A Weight-based Information Filtration Algorithm for Stock-Correlation Networks
• [quant-ph]Experimental neural network enhanced quantum tomography
• [quant-ph]Inferring the quantum density matrix with machine learning
• [stat.AP]A robust approach to model-based classification based on trimming and constraints
• [stat.AP]New statistic for detecting laboratory effects in ORDANOVA
• [stat.ME]A Composite Likelihood-based Approach for Change-point Detection in Spatio-temporal Process
• [stat.ME]Conformal Prediction Under Covariate Shift
• [stat.ME]On the estimation of parameter and stress-strength reliability for unit-Lindley distribution
• [stat.ML]Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension
• [stat.ML]Reference Product Search
• [stat.ML]Supervised Anomaly Detection based on Deep Autoregressive Density Estimators
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• [cs.AI]Few-Shot Bayesian Imitation Learning with Logic over Programs
Tom Silver, Kelsey R. Allen, Alex K. Lew, Leslie Pack Kaelbling, Josh Tenenbaum
http://arxiv.org/abs/1904.06317v1
• [cs.CL]A Crowdsourced Frame Disambiguation Corpus with Ambiguity
Anca Dumitrache, Lora Aroyo, Chris Welty
http://arxiv.org/abs/1904.06101v1
• [cs.CL]Adapting Sequence to Sequence models for Text Normalization in Social Media
Ismini Lourentzou, Kabir Manghnani, ChengXiang Zhai
http://arxiv.org/abs/1904.06100v1
• [cs.CL]Building a mixed-lingual neural TTS system with only monolingual data
Liumeng Xue, Wei Song, Guanghui Xu, Lei Xie, Zhizheng Wu
http://arxiv.org/abs/1904.06063v1
• [cs.CL]CITE: A Corpus of Image—Text Discourse Relations
Malihe Alikhani, Sreyasi Nag Chowdhury, Gerard de Melo, Matthew Stone
http://arxiv.org/abs/1904.06286v1
• [cs.CL]Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation
Ori Shapira, David Gabay, Yang Gao, Hadar Ronen, Ramakanth Pasunuru, Mohit Bansal, Yael Amsterdamer, Ido Dagan
http://arxiv.org/abs/1904.05929v1
• [cs.CL]Direct speech-to-speech translation with a sequence-to-sequence model
Ye Jia, Ron J. Weiss, Fadi Biadsy, Wolfgang Macherey, Melvin Johnson, Zhifeng Chen, Yonghui Wu
http://arxiv.org/abs/1904.06037v1
• [cs.CL]Evaluating the Representational Hub of Language and Vision Models
Ravi Shekhar, Ece Takmaz, Raquel Fernández, Raffaella Bernardi
http://arxiv.org/abs/1904.06038v1
• [cs.CL]FrameRank: A Text Processing Approach to Video Summarization
Zhuo Lei, Chao Zhang, Qian Zhang, Guoping Qiu
http://arxiv.org/abs/1904.05544v2
• [cs.CL]IIT (BHU) Varanasi at MSR-SRST 2018: A Language Model Based Approach for Natural Language Generation
Shreyansh Singh, Avi Chawla, Ayush Sharma, Anil Kumar Singh
http://arxiv.org/abs/1904.06234v1
• [cs.CL]Modeling Interpersonal Linguistic Coordination in Conversations using Word Mover’s Distance
Md Nasir, Sandeep Nallan Chakravarthula, Brian Baucom, David C. Atkins, Panayiotis Georgiou, Shrikanth Narayanan
http://arxiv.org/abs/1904.06002v1
• [cs.CL]Political Text Scaling Meets Computational Semantics
Federico Nanni, Goran Glavas, Simone Paolo Ponzetto, Heiner Stuckenschmidt
http://arxiv.org/abs/1904.06217v1
• [cs.CL]Strong Baselines for Complex Word Identification across Multiple Languages
Pierre Finnimore, Elisabeth Fritzsch, Daniel King, Alison Sneyd, Aneeq Ur Rehman, Fernando Alva-Manchego, Andreas Vlachos
http://arxiv.org/abs/1904.05953v1
• [cs.CR]Generating Minimal Adversarial Perturbations with Integrated Adaptive Gradients
Yatie Xiao, Chi-Man Pun
http://arxiv.org/abs/1904.06186v1
• [cs.CV]A Light Dual-Task Neural Network for Haze Removal
Yu Zhang, Xinchao Wang, Xiaojun Bi, Dacheng Tao
http://arxiv.org/abs/1904.06024v1
• [cs.CV]A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids
Qiuyu Zhu, Pengju Zhang, Xin Ye
http://arxiv.org/abs/1904.06008v1
• [cs.CV]ACE: Adapting to Changing Environments for Semantic Segmentation
Zuxuan Wu, Xin Wang, Joseph E. Gonzalez, Tom Goldstein, Larry S. Davis
http://arxiv.org/abs/1904.06268v1
• [cs.CV]Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology
Hiroki Tokunaga, Yuki Teramoto, Akihiko Yoshizawa, Ryoma Bise
http://arxiv.org/abs/1904.06040v1
• [cs.CV]An Empirical Evaluation Study on the Training of SDC Features for Dense Pixel Matching
René Schuster, Oliver Wasenmüller, Christian Unger, Didier Stricker
http://arxiv.org/abs/1904.06167v1
• [cs.CV]An Introduction to Person Re-identification with Generative Adversarial Networks
Hamed Alqahtani, Manolya Kavakli-Thorne, Charles Z. Liu
http://arxiv.org/abs/1904.05992v1
• [cs.CV]Big but Imperceptible Adversarial Perturbations via Semantic Manipulation
Anand Bhattad, Min Jin Chong, Kaizhao Liang, Bo Li, David A. Forsyth
http://arxiv.org/abs/1904.06347v1
• [cs.CV]Cramnet: Layer-wise Deep Neural Network Compression with Knowledge Transfer from a Teacher Network
Jon Hoffman
http://arxiv.org/abs/1904.05982v1
• [cs.CV]Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense
Lingyun Jiang, Kai Qiao, Ruoxi Qin, Linyuan Wang, Jian Chen, Haibing Bu, Bin Yan
http://arxiv.org/abs/1904.06026v1
• [cs.CV]Digging Deeper into Egocentric Gaze Prediction
Hamed R. Tavakoli, Esa Rahtu, Juho Kannala, Ali Borji
http://arxiv.org/abs/1904.06090v1
• [cs.CV]EvalNorm: Estimating Batch Normalization Statistics for Evaluation
Saurabh Singh, Abhinav Shrivastava
http://arxiv.org/abs/1904.06031v1
• [cs.CV]Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks
Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee
http://arxiv.org/abs/1904.06097v1
• [cs.CV]Face De-occlusion using 3D Morphable Model and Generative Adversarial Network
Xiaowei Yuan, In Kyu Park
http://arxiv.org/abs/1904.06109v1
• [cs.CV]Generalized Presentation Attack Detection: a face anti-spoofing evaluation proposal
Artur Costa-Pazo, David Jimenez-Cabello, Esteban Vazquez-Fernandez, Jose L. Alba-Castro, Roberto J. López-Sastre
http://arxiv.org/abs/1904.06213v1
• [cs.CV]Generative Hybrid Representations for Activity Forecasting with No-Regret Learning
Jiaqi Guan, Ye Yuan, Kris M. Kitani, Nicholas Rhinehart
http://arxiv.org/abs/1904.06250v1
• [cs.CV]GeoCapsNet: Aerial to Ground view Image Geo-localization using Capsule Network
Bin Sun, Chen Chen, Yingying Zhu, Jianmin Jiang
http://arxiv.org/abs/1904.06281v1
• [cs.CV]Incremental multi-domain learning with network latent tensor factorization
Adrian Bulat, Jean Kossaifi, Georgios Tzimiropoulos, Maja Pantic
http://arxiv.org/abs/1904.06345v1
• [cs.CV]MAANet: Multi-view Aware Attention Networks for Image Super-Resolution
Jingcai Guo, Shiheng Ma, Song Guo
http://arxiv.org/abs/1904.06252v1
• [cs.CV]Multi-View Region Adaptive Multi-temporal DMM and RGB Action Recognition
Mahmoud Al-Faris, John P. Chiverton, Yanyan Yang, David L. Ndzi
http://arxiv.org/abs/1904.06074v1
• [cs.CV]Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data
Aleksei Tiulpin, Stefan Klein, Sita M. A. Bierma-Zeinstra, Jérôme Thevenot, Esa Rahtu, Joyce van Meurs, Edwin H. G. Oei, Simo Saarakkala
http://arxiv.org/abs/1904.06236v1
• [cs.CV]PWOC-3D: Deep Occlusion-Aware End-to-End Scene Flow Estimation
Rohan Saxena, René Schuster, Oliver Wasenmüller, Didier Stricker
http://arxiv.org/abs/1904.06116v1
• [cs.CV]Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation
Yuyin Zhou, Zhe Li, Song Bai, Chong Wang, Xinlei Chen, Mei Han, Elliot Fishman, Alan Yuille
http://arxiv.org/abs/1904.06346v1
• [cs.CV]Real-Time Dense Stereo Embedded in A UAV for Road Inspection
Rui Fan, Jianhao Jiao, Jie Pan, Huaiyang Huang, Shaojie Shen, Ming Liu
http://arxiv.org/abs/1904.06017v1
• [cs.CV]TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning
Xin Wang, Fisher Yu, Ruth Wang, Trevor Darrell, Joseph E. Gonzalez
http://arxiv.org/abs/1904.05967v1
• [cs.CV]The Sound of Motions
Hang Zhao, Chuang Gan, Wei-Chiu Ma, Antonio Torralba
http://arxiv.org/abs/1904.05979v1
• [cs.CV]The iWildCam 2018 Challenge Dataset
Sara Beery, Grant van Horn, Oisin MacAodha, Pietro Perona
http://arxiv.org/abs/1904.05986v1
• [cs.CV]Unifying Heterogeneous Classifiers with Distillation
Jayakorn Vongkulbhisal, Phongtharin Vinayavekhin, Marco Visentini-Scarzanella
http://arxiv.org/abs/1904.06062v1
• [cs.CV]Unsupervised Method to Localize Masses in Mammograms
Bilal Ahmed Lodhi
http://arxiv.org/abs/1904.06044v1
• [cs.CY]Towards Formalizing the GDPR’s Notion of Singling Out
Aloni Cohen, Kobbi Nissim
http://arxiv.org/abs/1904.06009v1
• [cs.DC]FECBench: A Holistic Interference-aware Approach for Application Performance Modeling
Yogesh D. Barve, Shashank Shekhar, Ajay Dev Chhokra, Shweta Khare, Anirban Bhattacharjee, Zhuangwei Kang, Hongyang Sun, Aniruddha Gokhale
http://arxiv.org/abs/1904.05833v2
• [cs.DC]Fast and Resource Competitive Broadcast in Multi-channel Radio Networks
Haimin Chen, Chaodong Zheng
http://arxiv.org/abs/1904.06328v1
• [cs.DC]On Byzantine Fault Tolerance in Multi-Master Kubernertes Clusters
Gor Mack Diouf, Halima Elbiaze, Wael Jaafar
http://arxiv.org/abs/1904.06206v1
• [cs.DC]Parallel parametric linear programming solving, and application to polyhedral computations
Camille Coti, David Monniaux, Hang Yu
http://arxiv.org/abs/1904.06079v1
• [cs.DC]Survey of Major Load Balancing Algorithms in Distributed System
Igor Ivanisenko, Tamara Radivilova
http://arxiv.org/abs/1904.05923v1
• [cs.DC]ezBFT: Decentralizing Byzantine Fault-Tolerant State Machine Replication
Balaji Arun, Sebastiano Peluso, Binoy Ravindran
http://arxiv.org/abs/1904.06023v1
• [cs.DL]Female scholars need to achieve more for equal public recognition
Menno H. Schellekensa, Floris Holstegeb, Taha Yasseri
http://arxiv.org/abs/1904.06310v1
• [cs.IT]An Explicit Rate-Optimal Streaming Code for Channels with Burst and Arbitrary Erasures
Elad Domanovitz, Silas L. Fong, Ashish Khisti
http://arxiv.org/abs/1904.06212v1
• [cs.IT]On the Asymptotic Capacity of $X$-Secure $T$-Private Information Retrieval with Graph Based Replicated Storage
Zhuqing Jia, Syed A. Jafar
http://arxiv.org/abs/1904.05906v1
• [cs.IT]Optimal Caching Designs for Perfect, Imperfect and Unknown File Popularity Distributions in Large-Scale Multi-Tier Wireless Networks
Chencheng Ye, Ying Cui, Yang Yang, Rui Wang
http://arxiv.org/abs/1904.06029v1
• [cs.IT]Parity-Based Concurrent Error Detection Schemes for the ChaCha Stream Cipher
Viola Rieger, Alexander Zeh
http://arxiv.org/abs/1904.06073v1
• [cs.IT]When does OMP achieves support recovery with continuous dictionaries?
Clément Elvira, Rémi Gribonval, Charles Soussen, Cédric Herzet
http://arxiv.org/abs/1904.06311v1
• [cs.LG]A streaming feature-based compression method for data from instrumented infrastructure
Alastair Gregory, Din-Houn Lau, Alex Tessier, Pan Zhang
http://arxiv.org/abs/1904.06127v1
• [cs.LG]AMS-SFE: Towards an Alignment of Manifold Structures via Semantic Feature Expansion for Zero-shot Learning
Jingcai Guo, Song Guo
http://arxiv.org/abs/1904.06254v1
• [cs.LG]Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks
David J. Miller, Zhen Xiang, George Kesidis
http://arxiv.org/abs/1904.06292v1
• [cs.LG]Compressing deep neural networks by matrix product operators
Ze-Feng Gao, Song Cheng, Rong-Qiang He, Z. Y. Xie, Hui-Hai Zhao, Zhong-Yi Lu, Tao Xiang
http://arxiv.org/abs/1904.06194v1
• [cs.LG]Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch
Huy Phan, Oliver Y. Chén, Philipp Koch, Alfred Mertins, Maarten De Vos
http://arxiv.org/abs/1904.05945v1
• [cs.LG]Distributed Bandit Learning: How Much Communication is Needed to Achieve (Near) Optimal Regret
Yuanhao Wang, Jiachen Hu, Xiaoyu Chen, Liwei Wang
http://arxiv.org/abs/1904.06309v1
• [cs.LG]Distributed Layer-Partitioned Training for Privacy-Preserved Deep Learning
Chun-Hsien Yu, Chun-Nan Chou, Emily Chang
http://arxiv.org/abs/1904.06049v1
• [cs.LG]Effective Scheduling Function Design in SDN through Deep Reinforcement Learning
Huang Victoria, Chen Gang, Fu Qiang
http://arxiv.org/abs/1904.06039v1
• [cs.LG]Interaction-aware Decision Making with Adaptive Strategies under Merging Scenarios
Yeping Hu, Alireza Nakhaei, Masayoshi Tomizuka, Kikuo Fujimura
http://arxiv.org/abs/1904.06025v1
• [cs.LG]Learning Optimal Decision Trees from Large Datasets
Florent Avellaneda
http://arxiv.org/abs/1904.06314v1
• [cs.LG]Let’s Play Again: Variability of Deep Reinforcement Learning Agents in Atari Environments
Kaleigh Clary, Emma Tosch, John Foley, David Jensen
http://arxiv.org/abs/1904.06312v1
• [cs.LG]Multi-Armed Bandit for Energy-Efficient and Delay-Sensitive Edge Computing in Dynamic Networks with Uncertainty
Saeed Ghoorchian, Setareh Maghsudi
http://arxiv.org/abs/1904.06258v1
• [cs.LG]Multimodal Speech Emotion Recognition and Ambiguity Resolution
Gaurav Sahu
http://arxiv.org/abs/1904.06022v1
• [cs.LG]Position-Aware Convolutional Networks for Traffic Prediction
Shiheng Ma, Jingcai Guo, Song Guo, Minyi Guo
http://arxiv.org/abs/1904.06187v1
• [cs.LG]Ranking-Based Autoencoder for Extreme Multi-label Classification
Bingyu Wang, Li Chen, Wei Sun, Kechen Qin, Kefeng Li, Hui Zhou
http://arxiv.org/abs/1904.05937v1
• [cs.LG]Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout
Isidro Cortes-Ciriano, Andreas Bender
http://arxiv.org/abs/1904.06330v1
• [cs.LG]Revisit Lmser and its further development based on convolutional layers
Wenjing Huang, Shikui Tu, Lei Xu
http://arxiv.org/abs/1904.06307v1
• [cs.LG]Robust Coreset Construction for Distributed Machine Learning
Hanlin Lu, Ming-Ju Li, Ting He, Shiqiang Wang, Vijay Narayanan, Kevin S Chan
http://arxiv.org/abs/1904.05961v1
• [cs.LG]Similarities between policy gradient methods (PGM) in Reinforcement learning (RL) and supervised learning (SL)
Eric Benhamou
http://arxiv.org/abs/1904.06260v1
• [cs.LG]Spatio-Temporal Deep Graph Infomax
Felix L. Opolka, Aaron Solomon, Cătălina Cangea, Petar Veličković, Pietro Liò, R Devon Hjelm
http://arxiv.org/abs/1904.06316v1
• [cs.LG]The coupling effect of Lipschitz regularization in deep neural networks
Nicolas Couellan
http://arxiv.org/abs/1904.06253v1
• [cs.LG]Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders
Ari Heljakka, Arno Solin, Juho Kannala
http://arxiv.org/abs/1904.06145v1
• [cs.LG]Variational AutoEncoder For Regression: Application to Brain Aging Analysis
Qingyu Zhao, Ehsan Adeli, Nicolas Honnorat, Tuo Leng, Kilian M. Pohl
http://arxiv.org/abs/1904.05948v1
• [cs.LG]Variational Inference for Computational Imaging Inverse Problems
Francesco Tonolini, Ashley Lyons, Piergiorgio Caramazza, Daniele Faccio, Roderick Murray-Smith
http://arxiv.org/abs/1904.06264v1
• [cs.NE]A Reference Vector based Many-Objective Evolutionary Algorithm with Feasibility-aware Adaptation
Mingde Zhao, Hongwei Ge, Kai Zhang, Yaqing Hou
http://arxiv.org/abs/1904.06302v1
• [cs.NE]Evolved Art with Transparent, Overlapping, and Geometric Shapes
Joachim Berg, Nils Gustav Andreas Berggren, Sivert Allergodt Borgeteien, Christian Ruben Alexander Jahren, Arqam Sajid, Stefano Nichele
http://arxiv.org/abs/1904.06110v1
• [cs.NE]Evolving Indoor Navigational Strategies Using Gated Recurrent Units In NEAT
James Butterworth, Rahul Savani, Karl Tuyls
http://arxiv.org/abs/1904.06239v1
• [cs.NE]Locally Connected Spiking Neural Networks for Unsupervised Feature Learning
Daniel J. Saunders, Devdhar Patel, Hananel Hazan, Hava T. Siegelmann, Robert Kozma
http://arxiv.org/abs/1904.06269v1
• [cs.NE]On the Impact of the Cutoff Time on the Performance of Algorithm Configurators
George T. Hall, Pietro S. Oliveto, Dirk Sudholt
http://arxiv.org/abs/1904.06230v1
• [cs.RO]AI-IMU Dead-Reckoning
Martin Brossard, Axel Barrau, Silvère Bonnabel
http://arxiv.org/abs/1904.06064v1
• [cs.RO]On the Calibration of Force/Torque Sensors in Robotics
Fredrik Bagge Carlson
http://arxiv.org/abs/1904.06158v1
• [cs.SD]Assisted Sound Sample Generation with Musical Conditioning in Adversarial Auto-Encoders
Adrien Bitton, Philippe Esling, Antoine Caillon, Martin Fouilleul
http://arxiv.org/abs/1904.06215v1
• [cs.SD]STC Speaker Recognition Systems for the VOiCES From a Distance Challenge
Sergey Novoselov, Aleksei Gusev, Artem Ivanov, Timur Pekhovsky, Andrey Shulipa, Galina Lavrentyeva, Vladimir Volokhov, Alexandr Kozlov
http://arxiv.org/abs/1904.06093v1
• [cs.SI]STAND: A Spatio-Temporal Algorithm for Network Diffusion Simulation
Fangcao Xu, Bruce Desmarais, Donna Peuquet
http://arxiv.org/abs/1904.05998v1
• [eess.AS]Examining the Mapping Functions of Denoising Autoencoders in Music Source Separation
Stylianos Ioannis Mimilakis, Konstantinos Drossos, Estefanía Cano, Gerald Schuller
http://arxiv.org/abs/1904.06157v1
• [eess.AS]Unsupervised Speech Domain Adaptation Based on Disentangled Representation Learning for Robust Speech Recognition
Jong-Hyeon Park, Myungwoo Oh, Hyung-Min Park
http://arxiv.org/abs/1904.06086v1
• [eess.IV]Boundary-Preserved Deep Denoising of the Stochastic Resonance Enhanced Multiphoton Images
Sheng-Yong Niu, Lun-Zhang Guo, Yue Li, Tzung-Dau Wang, Yu Tsao, Tzu-Ming Liu
http://arxiv.org/abs/1904.06329v1
• [math.PR]Community Detection in the Sparse Hypergraph Stochastic Block Model
Soumik Pal, Yizhe Zhu
http://arxiv.org/abs/1904.05981v1
• [math.ST]Outlier-robust estimation of a sparse linear model using $\ell_1$-penalized Huber’s $M$-estimator
Arnak S. Dalalyan, Philip Thompson
http://arxiv.org/abs/1904.06288v1
• [q-bio.TO]Interpretable Classification from Skin Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study
Peizhen Xie, Ke Zuo, Yu Zhang, Fangfang Li, Mingzhu Yin, Kai Lu
http://arxiv.org/abs/1904.06156v1
• [q-fin.ST]A Weight-based Information Filtration Algorithm for Stock-Correlation Networks
Seyed Soheil Hosseini, Nick Wormald, Tianhai Tian
http://arxiv.org/abs/1904.06007v1
• [quant-ph]Experimental neural network enhanced quantum tomography
Adriano Macarone-Palmier, Egor Kovlakov, Federico Bianchi, Dmitry Yudin, Stanislav Straupe, Jacob Biamonte, Sergei Kulik
http://arxiv.org/abs/1904.05902v1
• [quant-ph]Inferring the quantum density matrix with machine learning
Kyle Cranmer, Siavash Golkar, Duccio Pappadopulo
http://arxiv.org/abs/1904.05903v1
• [stat.AP]A robust approach to model-based classification based on trimming and constraints
Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy
http://arxiv.org/abs/1904.06136v1
• [stat.AP]New statistic for detecting laboratory effects in ORDANOVA
Jun-ichi Takeshita, Yuto Arai, Mayu Ogawa, Xiao-Nan Lu, Tomomichi Suzuki
http://arxiv.org/abs/1904.06048v1
• [stat.ME]A Composite Likelihood-based Approach for Change-point Detection in Spatio-temporal Process
Zifeng Zhao, Ting Fung Ma, Wai Leong Ng, Chun Yip Yau
http://arxiv.org/abs/1904.06340v1
• [stat.ME]Conformal Prediction Under Covariate Shift
Rina Foygel Barber, Emmanuel J. Candes, Aaditya Ramdas, Ryan J. Tibshirani
http://arxiv.org/abs/1904.06019v1
• [stat.ME]On the estimation of parameter and stress-strength reliability for unit-Lindley distribution
Aniket Biswas, Subrata Chakraborty
http://arxiv.org/abs/1904.06181v1
• [stat.ML]Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension
Marina Gomtsyan, Nikita Mokrov, Maxim Panov, Yury Yanovich
http://arxiv.org/abs/1904.06151v1
• [stat.ML]Reference Product Search
Chu Wang, Lei Tang, Shujun Bian, Da Zhang, Zuohua Zhang, Yongning Wu
http://arxiv.org/abs/1904.05985v1
• [stat.ML]Supervised Anomaly Detection based on Deep Autoregressive Density Estimators
Tomoharu Iwata, Yuki Yamanaka
http://arxiv.org/abs/1904.06034v1