cs.AI - 人工智能

    cs.CC - 计算复杂度 cs.CL - 计算与语言 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.DS - 数据结构与算法 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.PF - 计算性能 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 eess.SP - 信号处理 eess.SY - 系统和控制 math.CO - 组合数学 math.NA - 数值分析 math.ST - 统计理论 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Procedural Generation of Initial States of Sokoban
    • [cs.CC]Vector Colorings of Random, Ramanujan, and Large-Girth Irregular Graphs
    • [cs.CL]Application of Transfer Learning for Automatic Triage of Social Media Posts
    • [cs.CL]Head-Driven Phrase Structure Grammar Parsing on Penn Treebank
    • [cs.CL]Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings
    • [cs.CL]Interactive-Predictive Neural Machine Translation through Reinforcement and Imitation
    • [cs.CL]Multi-lingual Intent Detection and Slot Filling in a Joint BERT-based Model
    • [cs.CV]A Novel Deep Learning Pipeline for Retinal Vessel Detection in Fluorescein Angiography
    • [cs.CV]A Performance Evaluation of Correspondence Grouping Methods for 3D Rigid Data Matching
    • [cs.CV]A Spectral Approach to Unsupervised Object Segmentation in Video
    • [cs.CV]A Survey of Pruning Methods for Efficient Person Re-identification Across Domains
    • [cs.CV]AI-based evaluation of the SDGs: The case of crop detection with earth observation data
    • [cs.CV]Attentive Context Normalization for Robust Permutation-Equivariant Learning
    • [cs.CV]C^3 Framework: An Open-source PyTorch Code for Crowd Counting
    • [cs.CV]Depth Restoration: A fast low-rank matrix completion via dual-graph regularization
    • [cs.CV]Distilling with Residual Network for Single Image Super Resolution
    • [cs.CV]Large Scale Adversarial Representation Learning
    • [cs.CV]Prior Activation Distribution (PAD): A Versatile Representation to Utilize DNN Hidden Units
    • [cs.CV]Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
    • [cs.CV]Visual Appearance Analysis of Forest Scenes for Monocular SLAM
    • [cs.CY]The FACTS of Technology-Assisted Sensitivity Review
    • [cs.DC]Automatic Differentiation for Adjoint Stencil Loops
    • [cs.DC]Data Encoding for Byzantine-Resilient Distributed Optimization
    • [cs.DC]Energy of Computing on Multicore CPUs: Predictive Models and Energy Conservation Law
    • [cs.DC]On the Cost of Concurrency in Hybrid Transactional Memory
    • [cs.DS]HashGraph — Scalable Hash Tables Using A Sparse Graph Data Structure
    • [cs.DS]Improved local search for graph edit distance
    • [cs.IR]A Road-map Towards Explainable Question Answering A Solution for Information Pollution
    • [cs.IR]Deep Personalized Re-targeting
    • [cs.IT]Early Detection for Optimal-Latency Communications in Multi-Hop Links
    • [cs.IT]Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges
    • [cs.IT]Low-power and Reliable Solid-state Drive with Inverted Limited Weight Coding
    • [cs.IT]Wireless Federated Distillation for Distributed Edge Learning with Heterogeneous Data
    • [cs.LG]A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks
    • [cs.LG]Attentive Multi-Task Deep Reinforcement Learning
    • [cs.LG]Deep Reinforcement Learning For Modeling Chit-Chat Dialog With Discrete Attributes
    • [cs.LG]Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
    • [cs.LG]Evaluating the distribution learning capabilities of GANs
    • [cs.LG]Explaining Predictions from Tree-based Boosting Ensembles
    • [cs.LG]Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation
    • [cs.LG]Incremental Concept Learning via Online Generative Memory Recall
    • [cs.LG]On Inductive Biases in Deep Reinforcement Learning
    • [cs.LG]Sequence to Sequence with Attention for Influenza Prevalence Prediction using Google Trends
    • [cs.LG]Twin Auxiliary Classifiers GAN
    • [cs.LG]Visualizing Uncertainty and Saliency Maps of Deep Convolutional Neural Networks for Medical Imaging Applications
    • [cs.LG]Visus: An Interactive System for Automatic Machine Learning Model Building and Curation
    • [cs.LG]Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape
    • [cs.LG]Zero-shot Learning for Audio-based Music Classification and Tagging
    • [cs.NE]Genetic Network Architecture Search
    • [cs.NI]Distributed User Clustering and Resource Allocation for Imperfect NOMA in Heterogeneous Networks
    • [cs.NI]Networkmetrics unraveled: MBDA in Action
    • [cs.PF]RegDem: Increasing GPU Performance via Shared Memory Register Spilling
    • [cs.RO]Object Placement Planning and Optimization for Robot Manipulators
    • [cs.RO]Spine-Inspired Continuum Soft Exoskeleton for Stoop Lifting Assistance
    • [cs.SD]A Bi-directional Transformer for Musical Chord Recognition
    • [cs.SD]Deep Neural Baselines for Computational Paralinguistics
    • [cs.SI]Extraction and Analysis of Fictional Character Networks: A Survey
    • [cs.SI]Intelligent social bots uncover the link between user preference and diversity of news consumption
    • [cs.SI]Network Embedding: on Compression and Learning
    • [eess.AS]A Methodology for Controlling the Emotional Expressiveness in Synthetic Speech — a Deep Learning approach
    • [eess.AS]The DKU Replay Detection System for the ASVspoof 2019 Challenge: On Data Augmentation, Feature Representation, Classification, and Fusion
    • [eess.IV]A new method for determining the filled point of the tooth by Bit-Plane Algorithm
    • [eess.IV]Adversarial Learning with Multiscale Features and Kernel Factorization for Retinal Blood Vessel Segmentation
    • [eess.IV]Automated Non-Destructive Inspection of Fused Filament Fabrication Components Using Thermographic Signal Reconstruction
    • [eess.IV]Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
    • [eess.IV]Cardiac MRI Segmentation with Strong Anatomical Guarantees
    • [eess.IV]Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation
    • [eess.IV]DeepAAA: clinically applicable and generalizable detection of abdominal aortic aneurysm using deep learning
    • [eess.IV]Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression
    • [eess.IV]High-throughput Onboard Hyperspectral Image Compression with Ground-based CNN Reconstruction
    • [eess.SP]Analysis and Optimisation of Distribution Matching for the Nonlinear Fibre Channel
    • [eess.SP]Optimal Blocklength Allocation towards Reduced Age of Information in Wireless Sensor Networks
    • [eess.SP]Spherical Large Intelligent Surfaces
    • [eess.SP]Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG
    • [eess.SY]Warm-Started Optimized Trajectory Planning for ASVs
    • [math.CO]Subspaces intersecting in at most a point
    • [math.NA]A stable discontinuous Galerkin method for linear elastodynamics in geometrically complex media using physics based numerical fluxes
    • [math.ST]A quantitative Mc Diarmid’s inequality for geometrically ergodic Markov chains
    • [math.ST]Algorithms of Robust Stochastic Optimization Based on Mirror Descent Method
    • [math.ST]On Finite Exchangeability and Conditional Independence
    • [math.ST]The adaptive Wynn-algorithm in generalized linear models with univariate response
    • [q-fin.ST]Forecasting security’s volatility using low-frequency historical data, high-frequency historical data and option-implied volatility
    • [stat.AP]Risk models for breast cancer and their validation
    • [stat.AP]Spatio-Temporal Reconstructions of Global CO2-Fluxes using Gaussian Markov Random Fields
    • [stat.ME]Analyses of ‘change scores’ do not estimate causal effects in observational data
    • [stat.ME]Cross-classified multilevel models
    • [stat.ME]Particularities and commonalities of singular spectrum analysis as a method of time series analysis and signal processing
    • [stat.ML]Adversarial Robustness through Local Linearization
    • [stat.ML]An Approximate Bayesian Approach to Surprise-Based Learning
    • [stat.ML]Geodesic Learning via Unsupervised Decision Forests
    • [stat.ML]Hybridized Threshold Clustering for Massive Data
    • [stat.ML]Invariant Risk Minimization

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    • [cs.AI]Procedural Generation of Initial States of Sokoban
    Dâmaris S. Bento, André G. Pereira, Levi H. S. Lelis
    http://arxiv.org/abs/1907.02548v1

    • [cs.CC]Vector Colorings of Random, Ramanujan, and Large-Girth Irregular Graphs
    Jess Banks, Luca Trevisan
    http://arxiv.org/abs/1907.02539v1

    • [cs.CL]Application of Transfer Learning for Automatic Triage of Social Media Posts
    Derek Howard, Marta Maslej, Justin Lee, Jacob Ritchie, Geoffrey Woollard, Leon French
    http://arxiv.org/abs/1907.02581v1

    • [cs.CL]Head-Driven Phrase Structure Grammar Parsing on Penn Treebank
    Junru Zhou, Hai Zhao
    http://arxiv.org/abs/1907.02684v1

    • [cs.CL]Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings
    Zenan Zhai, Dat Quoc Nguyen, Saber A. Akhondi, Camilo Thorne, Christian Druckenbrodt, Trevor Cohn, Michelle Gregory, Karin Verspoor
    http://arxiv.org/abs/1907.02679v1

    • [cs.CL]Interactive-Predictive Neural Machine Translation through Reinforcement and Imitation
    Tsz Kin Lam, Shigehiko Schamoni, Stefan Riezler
    http://arxiv.org/abs/1907.02326v2

    • [cs.CL]Multi-lingual Intent Detection and Slot Filling in a Joint BERT-based Model
    Giuseppe Castellucci, Valentina Bellomaria, Andrea Favalli, Raniero Romagnoli
    http://arxiv.org/abs/1907.02884v1

    • [cs.CV]A Novel Deep Learning Pipeline for Retinal Vessel Detection in Fluorescein Angiography
    Li Ding, Mohammad H. Bawany, Ajay E. Kuriyan, Rajeev S. Ramchandran, Charles C. Wykoff, Gaurav Sharma
    http://arxiv.org/abs/1907.02946v1

    • [cs.CV]A Performance Evaluation of Correspondence Grouping Methods for 3D Rigid Data Matching
    Jiaqi Yang, Ke Xian, Peng Wang, Yanning Zhang
    http://arxiv.org/abs/1907.02890v1

    • [cs.CV]A Spectral Approach to Unsupervised Object Segmentation in Video
    Elena Burceanu, Marius Leordeanu
    http://arxiv.org/abs/1907.02731v1

    • [cs.CV]A Survey of Pruning Methods for Efficient Person Re-identification Across Domains
    Hugo Masson, Amran Bhuiyan, Le Thanh Nguyen-Meidine, Mehrsan Javan, Parthipan Siva, Ismail Ben Ayed, Eric Granger
    http://arxiv.org/abs/1907.02547v1

    • [cs.CV]AI-based evaluation of the SDGs: The case of crop detection with earth observation data
    Natalia Efremova, Dennis West, Dmitry Zausaev
    http://arxiv.org/abs/1907.02813v1

    • [cs.CV]Attentive Context Normalization for Robust Permutation-Equivariant Learning
    Weiwei Sun, Wei Jiang, Eduard Trulls, Andrea Tagliasacchi, Kwang Moo Yi
    http://arxiv.org/abs/1907.02545v1

    • [cs.CV]C^3 Framework: An Open-source PyTorch Code for Crowd Counting
    Junyu Gao, Wei Lin, Bin Zhao, Dong Wang, Chenyu Gao, Jun Wen
    http://arxiv.org/abs/1907.02724v1

    • [cs.CV]Depth Restoration: A fast low-rank matrix completion via dual-graph regularization
    Wenxiang Zuo, Qiang Li, Xianming Liu
    http://arxiv.org/abs/1907.02841v1

    • [cs.CV]Distilling with Residual Network for Single Image Super Resolution
    Xiaopeng Sun, Wen Lu, Rui Wang, Furui Bai
    http://arxiv.org/abs/1907.02843v1

    • [cs.CV]Large Scale Adversarial Representation Learning
    Jeff Donahue, Karen Simonyan
    http://arxiv.org/abs/1907.02544v1

    • [cs.CV]Prior Activation Distribution (PAD): A Versatile Representation to Utilize DNN Hidden Units
    Lakmal Meegahapola, Vengateswaran Subramaniam, Lance Kaplan, Archan Misra
    http://arxiv.org/abs/1907.02711v1

    • [cs.CV]Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
    Wenjia Bai, Chen Chen, Giacomo Tarroni, Jinming Duan, Florian Guitton, Steffen E. Petersen, Yike Guo, Paul M. Matthews, Daniel Rueckert
    http://arxiv.org/abs/1907.02757v1

    • [cs.CV]Visual Appearance Analysis of Forest Scenes for Monocular SLAM
    James Garforth, Barbara Webb
    http://arxiv.org/abs/1907.02824v1

    • [cs.CY]The FACTS of Technology-Assisted Sensitivity Review
    Graham McDonald, Craig Macdonald, Iadh Ounis
    http://arxiv.org/abs/1907.02956v1

    • [cs.DC]Automatic Differentiation for Adjoint Stencil Loops
    Jan Hückelheim, Navjot Kukreja, Sri Hari Krishna Narayanan, Fabio Luporini, Gerard Gorman, Paul Hovland
    http://arxiv.org/abs/1907.02818v1

    • [cs.DC]Data Encoding for Byzantine-Resilient Distributed Optimization
    Deepesh Data, Linqi Song, Suhas Diggavi
    http://arxiv.org/abs/1907.02664v1

    • [cs.DC]Energy of Computing on Multicore CPUs: Predictive Models and Energy Conservation Law
    Arsalan Shahid, Muhammad Fahad, Ravi Reddy Manumachu, Alexey Lastovetsky
    http://arxiv.org/abs/1907.02805v1

    • [cs.DC]On the Cost of Concurrency in Hybrid Transactional Memory
    Trevor Brown, Srivatsan Ravi
    http://arxiv.org/abs/1907.02669v1

    • [cs.DS]HashGraph — Scalable Hash Tables Using A Sparse Graph Data Structure
    Oded Green
    http://arxiv.org/abs/1907.02900v1

    • [cs.DS]Improved local search for graph edit distance
    Nicolas Boria, David B. Blumenthal, Sébastien Bougleux, Luc Brun
    http://arxiv.org/abs/1907.02929v1

    • [cs.IR]A Road-map Towards Explainable Question Answering A Solution for Information Pollution
    Saeedeh Shekarpour, Faisal Alshargi
    http://arxiv.org/abs/1907.02606v1

    • [cs.IR]Deep Personalized Re-targeting
    Meisam Hejazinia, Pavlos Mitsoulis-Ntompos, Serena Zhang
    http://arxiv.org/abs/1907.02822v1

    • [cs.IT]Early Detection for Optimal-Latency Communications in Multi-Hop Links
    Diego Barragán Guerrero, Minh Au, Ghyslain Gagnon, François Gagnon, Pascal Giard
    http://arxiv.org/abs/1907.02576v1

    • [cs.IT]Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges
    Rui She, Shanyun Liu, Shuo Wan, Ke Xiong, Pingyi Fan
    http://arxiv.org/abs/1907.02652v1

    • [cs.IT]Low-power and Reliable Solid-state Drive with Inverted Limited Weight Coding
    Armin Ahmadzadeh, Omid Hajihassani, Pooria Taheri, Seyed Hossein Khasteh
    http://arxiv.org/abs/1907.02622v1

    • [cs.IT]Wireless Federated Distillation for Distributed Edge Learning with Heterogeneous Data
    Jin-Hyun Ahn, Osvaldo Simeone, Joonhyuk Kang
    http://arxiv.org/abs/1907.02745v1

    • [cs.LG]A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks
    Owen Marschall, Kyunghyun Cho, Cristina Savin
    http://arxiv.org/abs/1907.02649v1

    • [cs.LG]Attentive Multi-Task Deep Reinforcement Learning
    Timo Bram, Gino Brunner, Oliver Richter, Roger Wattenhofer
    http://arxiv.org/abs/1907.02874v1

    • [cs.LG]Deep Reinforcement Learning For Modeling Chit-Chat Dialog With Discrete Attributes
    Chinnadhurai Sankar, Sujith Ravi
    http://arxiv.org/abs/1907.02848v1

    • [cs.LG]Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
    Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison Cottrell, Geoffrey Hinton
    http://arxiv.org/abs/1907.02957v1

    • [cs.LG]Evaluating the distribution learning capabilities of GANs
    Amit Rege, Claire Monteleoni
    http://arxiv.org/abs/1907.02662v1

    • [cs.LG]Explaining Predictions from Tree-based Boosting Ensembles
    Ana Lucic, Hinda Haned, Maarten de Rijke
    http://arxiv.org/abs/1907.02582v1

    • [cs.LG]Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation
    Micha Pfeiffer, Isabel Funke, Maria R. Robu, Sebastian Bodenstedt, Leon Strenger, Sandy Engelhardt, Tobias Roß, Matthew J. Clarkson, Kurinchi Gurusamy, Brian R. Davidson, Lena Maier-Hein, Carina Riediger, Thilo Welsch, Jürgen Weitz, Stefanie Speidel
    http://arxiv.org/abs/1907.02882v1

    • [cs.LG]Incremental Concept Learning via Online Generative Memory Recall
    Huaiyu Li, Weiming Dong, Bao-Gang Hu
    http://arxiv.org/abs/1907.02788v1

    • [cs.LG]On Inductive Biases in Deep Reinforcement Learning
    Matteo Hessel, Hado van Hasselt, Joseph Modayil, David Silver
    http://arxiv.org/abs/1907.02908v1

    • [cs.LG]Sequence to Sequence with Attention for Influenza Prevalence Prediction using Google Trends
    Kenjiro Kondo, Akihiko Ishikawa, Masashi Kimura
    http://arxiv.org/abs/1907.02786v1

    • [cs.LG]Twin Auxiliary Classifiers GAN
    Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich
    http://arxiv.org/abs/1907.02690v1

    • [cs.LG]Visualizing Uncertainty and Saliency Maps of Deep Convolutional Neural Networks for Medical Imaging Applications
    Jae Duk Seo
    http://arxiv.org/abs/1907.02940v1

    • [cs.LG]Visus: An Interactive System for Automatic Machine Learning Model Building and Curation
    Aécio Santos, Sonia Castelo, Cristian Felix, Jorge Piazentin Ono, Bowen Yu, Sungsoo Hong, Cláudio T. Silva, Enrico Bertini, Juliana Freire
    http://arxiv.org/abs/1907.02889v1

    • [cs.LG]Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape
    Johanni Brea, Berfin Simsek, Bernd Illing, Wulfram Gerstner
    http://arxiv.org/abs/1907.02911v1

    • [cs.LG]Zero-shot Learning for Audio-based Music Classification and Tagging
    Jeong Choi, Jongpil Lee, Jiyoung Park, Juhan Nam
    http://arxiv.org/abs/1907.02670v1

    • [cs.NE]Genetic Network Architecture Search
    Hai Victor Habi, Gil Rafalovich
    http://arxiv.org/abs/1907.02871v1

    • [cs.NI]Distributed User Clustering and Resource Allocation for Imperfect NOMA in Heterogeneous Networks
    Abdulkadir Celik, Ming-Cheng Tsai, Redha M. Radaydeh, Fawaz S. Al-Qahtani, Mohamed-Slim Alouini
    http://arxiv.org/abs/1907.02761v1

    • [cs.NI]Networkmetrics unraveled: MBDA in Action
    José Camacho, Rasmus Bro, David Kotz
    http://arxiv.org/abs/1907.02677v1

    • [cs.PF]RegDem: Increasing GPU Performance via Shared Memory Register Spilling
    Putt Sakdhnagool, Amit Sabne, Rudolf Eigenmann
    http://arxiv.org/abs/1907.02894v1

    • [cs.RO]Object Placement Planning and Optimization for Robot Manipulators
    Joshua A. Haustein, Kaiyu Hang, Johannes Stork, Danica Kragic
    http://arxiv.org/abs/1907.02555v1

    • [cs.RO]Spine-Inspired Continuum Soft Exoskeleton for Stoop Lifting Assistance
    Xiaolong Yang, Tzu-Hao Huang, Hang Hu, Shuangyue Yu, Sainan Zhang, Xianlian Zhou, Alessandra Carriero, Guang Yue, Hao Su
    http://arxiv.org/abs/1907.02562v1

    • [cs.SD]A Bi-directional Transformer for Musical Chord Recognition
    Jonggwon Park, Kyoyun Choi, Sungwook Jeon, Dokyun Kim, Jonghun Park
    http://arxiv.org/abs/1907.02698v1

    • [cs.SD]Deep Neural Baselines for Computational Paralinguistics
    Daniel Elsner, Stefan Langer, Fabian Ritz, Robert Müller, Steffen Illium
    http://arxiv.org/abs/1907.02864v1

    • [cs.SI]Extraction and Analysis of Fictional Character Networks: A Survey
    Vincent Labatut, Xavier Bost
    http://arxiv.org/abs/1907.02704v1

    • [cs.SI]Intelligent social bots uncover the link between user preference and diversity of news consumption
    Yong Min, Tingjun Jiang, Cheng Jin, Qu Li, Xiaogang Jin
    http://arxiv.org/abs/1907.02703v1

    • [cs.SI]Network Embedding: on Compression and Learning
    Esra Akbas, Mehmet Aktas
    http://arxiv.org/abs/1907.02811v1

    • [eess.AS]A Methodology for Controlling the Emotional Expressiveness in Synthetic Speech — a Deep Learning approach
    Noé Tits
    http://arxiv.org/abs/1907.02784v1

    • [eess.AS]The DKU Replay Detection System for the ASVspoof 2019 Challenge: On Data Augmentation, Feature Representation, Classification, and Fusion
    Weicheng Cai, Haiwei Wu, Danwei Cai, Ming Li
    http://arxiv.org/abs/1907.02663v1

    • [eess.IV]A new method for determining the filled point of the tooth by Bit-Plane Algorithm
    Zahra Alidousti, Maryam Taghizadeh Dehkordi
    http://arxiv.org/abs/1907.02873v1

    • [eess.IV]Adversarial Learning with Multiscale Features and Kernel Factorization for Retinal Blood Vessel Segmentation
    Farhan Akram, Vivek Kumar Singh, Hatem A. Rashwan, Mohamed Abdel-Nasser, Md. Mostafa Kamal Sarker, Nidhi Pandey, Domenec Puig
    http://arxiv.org/abs/1907.02742v1

    • [eess.IV]Automated Non-Destructive Inspection of Fused Filament Fabrication Components Using Thermographic Signal Reconstruction
    Joshua E. Siegel, Maria F. Beemer, Steven M. Shepard
    http://arxiv.org/abs/1907.02634v1

    • [eess.IV]Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
    Weixia Zhang, Kede Ma, Jia Yan, Dexiang Deng, Zhou Wang
    http://arxiv.org/abs/1907.02665v1

    • [eess.IV]Cardiac MRI Segmentation with Strong Anatomical Guarantees
    Nathan Painchaud, Youssef Skandarani, Thierry Judge, Olivier Bernard, Alain Lalande, Pierre-Marc Jodoin
    http://arxiv.org/abs/1907.02865v1

    • [eess.IV]Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation
    Cheng Ouyang, Konstantinos Kamnitsas, Carlo Biffi, Jinming Duan, Daniel Rueckert
    http://arxiv.org/abs/1907.02766v1

    • [eess.IV]DeepAAA: clinically applicable and generalizable detection of abdominal aortic aneurysm using deep learning
    Jen-Tang Lu, Rupert Brooks, Stefan Hahn, Jin Chen, Varun Buch, Gopal Kotecha, Katherine P. Andriole, Brian Ghoshhajra, Joel Pinto, Paul Vozila, Mark Michalski, Neil A. Tenenholtz
    http://arxiv.org/abs/1907.02567v1

    • [eess.IV]Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression
    Daniele Ravi, Daniel C. Alexander, Neil P. Oxtoby
    http://arxiv.org/abs/1907.02787v1

    • [eess.IV]High-throughput Onboard Hyperspectral Image Compression with Ground-based CNN Reconstruction
    Diego Valsesia, Enrico Magli
    http://arxiv.org/abs/1907.02959v1

    • [eess.SP]Analysis and Optimisation of Distribution Matching for the Nonlinear Fibre Channel
    Tobias Fehenberger, Alex Alvarado
    http://arxiv.org/abs/1907.02846v1

    • [eess.SP]Optimal Blocklength Allocation towards Reduced Age of Information in Wireless Sensor Networks
    Bin Han, Yao Zhu, Zhiyuan Jiang, Yulin hu, Hans D. Schotten
    http://arxiv.org/abs/1907.02779v1

    • [eess.SP]Spherical Large Intelligent Surfaces
    Sha Hu
    http://arxiv.org/abs/1907.02699v1

    • [eess.SP]Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG
    Sumit A. Raurale, Saif Nalband, Geraldine B. Boylan, Gordon Lightbody, John M. O’Toole
    http://arxiv.org/abs/1907.02877v1

    • [eess.SY]Warm-Started Optimized Trajectory Planning for ASVs
    Glenn Bitar, Vegard N. Vestad, Anastasios M. Lekkas, Morten Breivik
    http://arxiv.org/abs/1907.02696v1

    • [math.CO]Subspaces intersecting in at most a point
    Sascha Kurz
    http://arxiv.org/abs/1907.02728v1

    • [math.NA]A stable discontinuous Galerkin method for linear elastodynamics in geometrically complex media using physics based numerical fluxes
    Kenneth Duru, Leonhard Rannabauer, On Ki Angel Ling, Alice-Agnes Gabriel, Heiner Igel, Michael Bader
    http://arxiv.org/abs/1907.02658v1

    • [math.ST]A quantitative Mc Diarmid’s inequality for geometrically ergodic Markov chains
    Antoine Havet, Matthieu Lerasle, Eric Moulines, Elodie Vernet
    http://arxiv.org/abs/1907.02809v1

    • [math.ST]Algorithms of Robust Stochastic Optimization Based on Mirror Descent Method
    Anatoli Juditsky, Alexander Nazin, Arkadi Nemirovsky, Alexandre Tsybakov
    http://arxiv.org/abs/1907.02707v1

    • [math.ST]On Finite Exchangeability and Conditional Independence
    Kayvan Sadeghi
    http://arxiv.org/abs/1907.02912v1

    • [math.ST]The adaptive Wynn-algorithm in generalized linear models with univariate response
    Fritjof Freise, Norbert Gaffke, Rainer Schwabe
    http://arxiv.org/abs/1907.02708v1

    • [q-fin.ST]Forecasting security’s volatility using low-frequency historical data, high-frequency historical data and option-implied volatility
    Huiling Yuan, Yong Zhou, Zhiyuan Zhang, Xiangyu Cui
    http://arxiv.org/abs/1907.02666v1

    • [stat.AP]Risk models for breast cancer and their validation
    Adam R Brentnall, Jack Cuzick
    http://arxiv.org/abs/1907.02829v1

    • [stat.AP]Spatio-Temporal Reconstructions of Global CO2-Fluxes using Gaussian Markov Random Fields
    Unn Dahlen, Johan Linström, Marko Scholze
    http://arxiv.org/abs/1907.02706v1

    • [stat.ME]Analyses of ‘change scores’ do not estimate causal effects in observational data
    Peter W. G. Tennant, Kellyn F. Arnold, George T. H. Ellison, Mark S. Gilthorpe
    http://arxiv.org/abs/1907.02764v1

    • [stat.ME]Cross-classified multilevel models
    George Leckie
    http://arxiv.org/abs/1907.02569v1

    • [stat.ME]Particularities and commonalities of singular spectrum analysis as a method of time series analysis and signal processing
    Nina Golyandina
    http://arxiv.org/abs/1907.02579v1

    • [stat.ML]Adversarial Robustness through Local Linearization
    Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy, Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli
    http://arxiv.org/abs/1907.02610v1

    • [stat.ML]An Approximate Bayesian Approach to Surprise-Based Learning
    Vasiliki Liakoni, Alireza Modirshanechi, Wulfram Gerstner, Johanni Brea
    http://arxiv.org/abs/1907.02936v1

    • [stat.ML]Geodesic Learning via Unsupervised Decision Forests
    Meghana Madhyastha, Percy Li, James Browne, Veronika Strnadova-Neeley, Carey E. Priebe, Randal Burns, Joshua T. Vogelstein
    http://arxiv.org/abs/1907.02844v1

    • [stat.ML]Hybridized Threshold Clustering for Massive Data
    Jianmei Luo, ChandraVyas Annakula, Aruna Sai Kannamareddy, Jasjeet S. Sekhon, William Henry Hsu, Michael Higgins
    http://arxiv.org/abs/1907.02907v1

    • [stat.ML]Invariant Risk Minimization
    Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, David Lopez-Paz
    http://arxiv.org/abs/1907.02893v1