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