人工智能顶会UAI 2019大会论文接受列表

【导读】UAI大会全称为Conference on Uncertainty in Artificial Intelligence，立足于不确定性人工智能领域，主要侧重于不确定性人工智能的知识表达、获取以及推理等问题。本文整理了2019年大会的接受论文列表，方便读者查阅。

ID: 1	Personalized Peer Truth Serum  for Eliciting Multi-Attribute Personal Data
	Naman Goel, Boi Faltings
ID: 6	Conditional  Expectation Propagation
	Zheng Wang, Shandian Zhe
ID: 7	A Sparse Representation-Based  Approach to Linear Regression with Partially Shuffled Labels
	Martin Slawski, Mostafa Rahmani,  Ping Li
ID: 13	On Fast Convergence of Proximal  Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss  Function
	Xingguo Li, Haoming Jiang,  Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
ID: 14	Correlated Learning for  Aggregation Systems
	Tanvi Verma, Pradeep  Varakantham
ID: 15	Causal Calculus in the Presence  of Cycles, Latent Confounders and Selection Bias
	Patrick Forré, Joris M.  Mooij
ID: 16	Variational Regret Bounds for  Reinforcement Learning
	Ronald Ortner, Pratik Gajane,  Peter Auer
ID: 17	Recommendation  from Raw Data with Adaptive Compound Poisson Factorization
	Olivier Gouvert, Thomas Oberlin,  Cédric Févotte
ID: 19	One-Shot Inference in Markov  Random Fields
	Hao Xiong, Yuanzhen Guo, Yibo  Yang, Nicholas Ruozzi
ID: 21	Truly  Proximal Policy Optimization
	Yuhui Wang, Hao He, Xiaoyang  Tan
ID: 24	Learning Factored Markov  Decision Processes with Unawareness
	Craig Innes, Alex  Lascarides
ID: 25	Expressive  Priors in Bayesian Neural Networks: Kernel Combinations and Periodic  Functions
	Tim Pearce, Russell Tsuchida,  Mohamed Zaki, Alexandra Brintrup, Andy Neely
ID: 28	Countdown  Regression: Sharp and Calibrated Survival Predictions
	Anand Avati, Tony Duan, Sharon  Zhou, Ken Jung, Nigam H. Shah, Andrew Ng
ID: 32	Reducing  Exploration of Dying Arms in Mortal Bandits
	Stefano Tracà, Weiyu Yan,  Cynthia Rudin
ID: 33	Comparing  EM with GD in Mixture Models of Two Components
	Guojun Zhang, Pascal Poupart,  George Trimponias
ID: 35	Efficient Search-Based Weighted  Model Integration
	Zhe Zeng, Guy Van den  Broeck
ID: 45	Causal Discovery with General  Non-Linear Relationships using Non-Linear ICA
	Ricardo Pio Monti, Kun Zhang,  Aapo Hyvarinen
ID: 47	BubbleRank: Safe Online Learning  to Re-Rank via Implicit Click Feedback
	Chang Li, Branislav Kveton, Tor  Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvari, Masrour  Zoghi
ID: 49	Coordinating Users of Shared  Facilities via Data-driven Predictive Assistants and Game Theory
	Philipp Geiger, Michel Besserve,  Justus Winkelmann, Claudius Proissl, Bernhard Schoelkopf
ID: 53	The Incomplete Rosetta Stone  problem: Identifiability results for Multi-view Nonlinear ICA
	Luigi Gresele, Paul Rubenstein,  Arash Mehrjou, Francesco Locatello, Bernhard Schoelkopf
ID: 55	Random  Clique Covers for Graphs with Local Density and Global Sparsity
	Sinead A. Williamson, Mauricio  Tec
ID: 64	Randomized  Iterative Algorithms for Fisher Discriminant Analysis
	Agniva Chowdhury, Jiasen Yang,  Petros Drineas
ID: 78	Dynamic Trip-Vehicle Dispatch  with Scheduled and On-Demand Requests
	Taoan Huang, Bohui Fang, Xiaohui  Bei, Fei Fang
ID: 83	Fall of Empires: Breaking  Byzantine-tolerant SGD by Inner Product Manipulation
	Cong Xie, Oluwasanmi Koyejo,  Indranil Gupta
ID: 86	Adaptive  Hashing for Model Counting
	Jonathan Kuck, Tri Dao, Shenjia  Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon
ID: 91	Towards a  Better Understanding and Regularization of GAN Training Dynamics
	Weili Nie, Ankit Patel
ID: 101	Domain  Generalization via Multidomain Discriminant Analysis
	Shoubo Hu, Kun Zhang, Zhitang  Chen, Laiwan Chan
ID: 112	Efficient Planning Under  Uncertainty with Incremental Refinement
	Juan Carlos Saborío, Joachim  Hertzberg
ID: 118	Cubic Regularization with  Momentum for Nonconvex Optimization
	Zhe Wang, Yi Zhou, Yingbin  Liang, Guanghui Lan
ID: 122	Stability of Linear Structural  Equation Models of Causal Inference
	Karthik Abinav Sankararaman,  Anand Louis, Navin Goyal
ID: 124	Random  Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep  Learning
	Robert Peharz, Antonio Vergari,  Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian  Kersting, Zoubin Ghahramani
ID: 127	Towards  Robust Relational Causal Discovery
	Sanghack Lee, Vasant  Honavar
ID: 128	The Role of Memory in Stochastic  Optimization
	Antonio Orvieto, Jonas Kohler,  Aurelien Lucchi
ID: 129	Random  Search and Reproducibility for Neural Architecture Search
	Liam Li, Ameet Talwalkar
ID: 138	Joint Nonparametric Precision  Matrix Estimation with Confounding
	Sinong Geng, Mladen Kolar,  Oluwasanmi Koyejo
ID: 144	General Identifiability with  Arbitrary Surrogate Experiments
	Sanghack Lee, Juan D. Correa,  Elias Bareinboim
ID: 148	Differentiable  Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem
	Karen Ullrich, Rianne van den  Berg, Marcus A. Brubaker, David Fleet, Max Welling
ID: 152	Approximate Inference in  Structured Instances with Noisy Categorical Observations
	Alireza Heidari, Ihab F. Ilyas,  Theodoros Rekatsinas
ID: 156	Randomized  Value Functions via Multiplicative Normalizing Flows
	Ahmed Touati, Harsh Satija,  Joshua Romoff, Joelle Pineau, Pascal Vincent
ID: 158	A Fast Proximal Point Method for  Computing Exact Wasserstein Distance
	Yujia Xie, Xiangfeng Wang,  Ruijia Wang, Hongyuan Zha
ID: 159	Neural  Dynamics Discovery via Gaussian Process Recurrent Neural Networks
	Qi She, Anqi Wu
ID: 161	Fisher-Bures  Adversary Graph Convolutional Networks
	Ke Sun, Piotr Koniusz, Zhen  Wang
ID: 162	Epsilon-BMC: A Bayesian Ensemble  Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning
	Michael Gimelfarb, Scott Sanner,  Chi-Guhn Lee
ID: 163	Periodic  Kernel Approximation by Index Set Fourier Series Features
	Anthony Tompkins, Fabio  Ramos
ID: 164	Efficient Neural Network  Verification with Exactness Characterization
	Krishnamurthy (Dj) Dvijotham,  Robert Stanforth, Sven Gowal, Sven Gowal, Chongli Qin, Soham De, Pushmeet  Kohli
ID: 172	Augmenting  and Tuning Knowledge Graph Embeddings
	Robert Bamler, Farnood Salehi,  Stephan Mandt
ID: 174	A Tighter Analysis of Randomised  Policy Iteration
	Meet Taraviya, Shivaram  Kalyanakrishnan
ID: 176	Perturbed-History Exploration in  Stochastic Linear Bandits
	Branislav Kveton, Csaba  Szepesvari, Mohammad Ghavamzadeh, Craig Boutilier
ID: 191	An Improved Convergence Analysis  of Stochastic Variance-Reduced Policy Gradient
	Pan Xu, Felicia Gao, Quanquan  Gu
ID: 192	Deep Mixture of Experts via  Shallow Embedding
	Xin Wang, Fisher Yu, Lisa  Dunlap, Yi-An Ma, Ruth Wang, Azalia Mirhoseini, Trevor Darrell, Joseph E.  Gonzalez
ID: 193	Sampling-Free  Variational Inference of Bayesian Neural Networks by Variance Backpropagation
	Manuel Haußmann, Fred A.  Hamprecht, Melih Kandemir
ID: 204	Sliced  Score Matching: A Scalable Approach to Density and Score Estimation
	Yang Song, Sahaj Garg, Jiaxin  Shi, Stefano Ermon
ID: 205	Beyond Structural Causal Models:  Causal Constraints Models
	Tineke Blom, Stephan Bongers,  Joris M. Mooij
ID: 206	Be Greedy: How Chromatic Number  meets Regret Minimization in Graph Bandits
	Aadirupa Saha, Shreyas  Sheshadri, Chiranjib Bhattacharyya
ID: 210	Approximate Causal Abstractions
	Sander Beckers, Frederick  Eberhardt, Joseph Y. Halpern
ID: 213	The  Sensitivity of Counterfactual Fairness to Unmeasured Confounding
	Niki Kilbertus, Philip J. Ball,  Matt J. Kusner, Adrian Weller, Ricardo Silva
ID: 221	Belief Propagation: Accurate  Marginals or Accurate Partition Function -- Where is the Difference?
	Christian Knoll, Franz  Pernkopf
ID: 222	Finding Minimal d-separators in  Linear Time and Applications
	Benito van der Zander, Maciej  Liśkiewicz
ID: 228	A Bayesian Approach to Robust  Reinforcement Learning
	Esther Derman, Daniel J.  Mankowitz, Timothy A. Mann, Shie Mannor
ID: 232	Adaptivity and Optimality: A  Universal Algorithm for Online Convex Optimization
	Guanghui Wang, Shiyin Lu, Lijun  Zhang
ID: 234	Evacuate or Not? A POMDP Model  of the Decision Making of Individuals in Hurricane Evacuation Zones
	Adithya Raam Sankar, Prashant  Doshi, Adam Goodie
ID: 235	Probabilistic  Programming for Birth-Death Models of Evolution Using an Alive Particle  Filter with Delayed Sampling
	Jan Kudlicka, Lawrence M.  Murray, Fredrik Ronquist, Thomas B. Schön
ID: 239	Variational  Sparse Coding
	Francesco Tonolini, Bjørn Sand  Jensen, Roderick Murray-Smith
ID: 244	Learning with Non-Convex  Truncated Losses by SGD
	Yi Xu, Shenghuo Zhu, Sen Yang,  Chi Zhang, Rong Jin, Tianbao Yang
ID: 245	Active Multi-Information Source  Bayesian Quadrature
	Alexandra Gessner, Javier  Gonzalez, Maren Mahsereci
ID: 248	Cascading Linear Submodular  Bandits: Accounting for Position Bias and Diversity in Online Learning to  Rank
	Gaurush Hiranandani, Harvineet  Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav  Kveton
ID: 253	Sinkhorn AutoEncoders
	Giorgio Patrini, Rianne van den  Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim  Genewein, Frank Nielsen
ID: 262	How to Exploit Structure while  Solving Weighted Model Integration Problems
	Samuel Kolb, Pedro Zuidberg Dos  Martires, Luc De Raedt
ID: 264	Multi-Class Gaussian Process  Classification Made Conjugate: Efficient Inference via Data Augmentation
	Théo Galy-Fajou, Florian Wenzel,  Christian Donner, Manfred Opper
ID: 267	A Flexible Framework for  Multi-Objective Bayesian Optimization using Random Scalarizations
	Biswajit Paria, Kirthevasan  Kandasamy, Barnabás Póczos
ID: 275	Efficient Multitask Feature and  Relationship Learning
	Han Zhao, Otilia Stretcu,  Alexander J. Smola, Geoffrey J. Gordon
ID: 284	Practical Multi-fidelity  Bayesian Optimization for Hyperparameter Tuning
	Jian Wu, Saul Toscano-Palmerin,  Peter I. Frazier, Andrew Gordon Wilson
ID: 290	Adaptively  Truncating Backpropagation Through Time to Control Gradient Bias
	Christopher Aicher, Nicholas J.  Foti, Emily B. Fox
ID: 296	Sampling-free  Uncertainty Estimation in Gated Recurrent Units with Applications to  Normative Modeling in Neuroimaging
	Seong Jae Hwang, Ronak R. Mehta,  Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh
ID: 299	Online Factorization and  Partition of Complex Networks by Random Walk
	Lin F. Yang, Zheng Yu, Vladimir  Braverman, Tuo Zhao, Mengdi Wang
ID: 302	On Densification for Minwise  Hashing
	Tung Mai, Anup Rao, Matt  Kapilevich, Ryan Rossi, Yasin Abbsi Yadkori, Ritwik Sinha
ID: 310	N-GCN: Multi-scale Graph  Convolution for Semi-supervised Node Classification
	Sami Abu-El-Haija, Amol Kapoor,  Bryan Perozzi, Joonseok Lee
ID: 312	Problem-dependent Regret Bounds  for Online Learning with Feedback Graphs
	Bingshan Hu, Nishant A. Mehta,  Jianping Pan
ID: 315	Wasserstein Fair Classification
	Ray Jiang, Aldo Pacchiano, Tom  Stepleton, Heinrich Jiang, Silvia Chiappa
ID: 317	Variational Training for  Large-Scale Noisy-OR Bayesian Networks
	Geng Ji, Dehua Cheng, Huazhong  Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik Sudderth
ID: 319	Guaranteed Scalable Learning of  Latent Tree Models
	Furong Huang, Niranjan UN,  Ioakeim Perros, Robert Chen, Jimeng Sun, Anima Anandkumar
ID: 324	On First-Order Bounds, Variance  and Gap-Dependent Bounds for Adversarial Bandits
	Roman Pogodin, Tor  Lattimore
ID: 332	Noise  Contrastive Priors for Functional Uncertainty
	Danijar Hafner, Dustin Tran,  Timothy Lillicrap, Alex Irpan, James Davidson
ID: 334	Fake It  Till You Make It: Learning-Compatible Performance ort
	Jonathan Bragg, Emma  Brunskill
ID: 335	Literal or Pedagogic Human?  Analyzing Human Model Misspecification in Objective Learning
	Smitha Milli, Anca D.  Dragan
ID: 339	Convergence Analysis of  Gradient-Based Learning in Continuous Games
	Benjamin Chasnov, Lillian J.  Ratliff, Eric Mazumdar, Sam Burden
ID: 340	End-to-end  Training of Deep Probabilistic CCA on Paired Biomedical Observations
	Gregory Gundersen, Bianca  Dumitrascu, Jordan T. Ash, Barbara E. Engelhardt
ID: 341	Approximate Relative Value  Learning for Average-reward Continuous State MDPs
	Hiteshi Sharma, Mehdi  Jafarnia-Jahromi, Rahul Jain
ID: 345	Exact  Sampling of Directed Acyclic Graphs from Modular Distributions
	Topi Talvitie, Aleksis  Vuoksenmaa, Mikko Koivisto
ID: 352	Intervening on Network Ties
	Eli Sherman, Ilya Shpitser
ID: 356	Generating and Sampling Orbits  for Lifted Probabilistic Inference
	Steven Holtzen, Todd Millstein,  Guy Van den Broeck
ID: 368	Real-Time Robotic Search using  Structural Spatial Point Processes
	Olov Andersson, Per Sidén, Johan  Dahlin, Patrick Doherty, Mattias Villani
ID: 370	Social Reinforcement Learning to  Combat Fake News Spread
	Mahak Goindani, Jennifer  Neville
ID: 371	P3O: Policy-on Policy-off Policy  Optimization
	Rasool Fakoor, Pratik Chaudhari,  Alexander J. Smola
ID: 372	Causal Inference Under  Interference And Network Uncertainty
	Rohit Bhattacharya, Daniel  Malinsky, Ilya Shpitser
ID: 373	Revisiting Reweighted Wake-Sleep  for Models with Stochastic Control Flow
	Tuan Anh Le, Adam R. Kosiorek,  N. Siddharth, Yee Whye Teh, Frank Wood
ID: 380	Learnability for the Information  Bottleneck
	Tailin Wu, Ian Fischer, Isaac  Chuang, Max Tegmark
ID: 383	Learning  Belief Representations for Imitation Learning in POMDPs
	Tanmay Gangwani, Joel Lehman,  Qiang Liu, Jian Peng
ID: 393	Object Conditioning for Causal  Inference
	David Jensen, Javier Burroni,  Matthew Rattigan
ID: 403	CCMI :  Classifier based Conditional Mutual Information Estimation
	Sudipto Mukherjee, Himanshu  Asnani, Sreeram Kannan
ID: 406	Empirical  Mechanism Design: Designing Mechanisms from Data
	Enrique Areyan Viqueira, Cyrus  Cousins, Yasser Mohammad, Amy Greenwald
ID: 407	On the  Relationship Between Satisfiability and Markov Decision Processes
	Ricardo Salmon, Pascal  Poupart
ID: 410	Interpretable  Almost Matching Exactly With Instrumental Variables
	M.Usaid Awan, Yameng Liu, Marco  Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
ID: 411	Low  Frequency Adversarial Perturbation
	Chuan Guo, Jared S. Frank,  Kilian Q. Weinberger
ID: 427	Markov Logic Networks for  Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption
	Ondrej Kuzelka, Jesse  Davis
ID: 428	Identification In Missing Data  Models Represented By Directed Acyclic Graphs
	Rohit Bhattacharya, Razieh Nabi,  Ilya Shpitser, James M. Robins
ID: 432	A  Weighted Mini-Bucket Bound for Solving Influence Diagram
	Junkyu Lee, Radu Marinescu,  Alexander Iher, Rina Dechter
ID: 435	Subspace  Inference for Bayesian Deep Learning
	Pavel Izmailov, Wesley J.  Maddox, Polina Kirichenko, Timur Garipov, Dmitry Vetrov, Andrew Gordon  Wilson
ID: 440	Off-Policy Policy Gradient with  Stationary Distribution Correction
	Yao Liu, Adith Swaminathan,  Alekh Agarwal, Emma Brunskill
ID: 441	Co-training for Policy Learning
	Jialin Song, Ravi Lanka, Yisong  Yue, Masahiro Ono
ID: 443	Variational Inference of  Penalized Regression with Submodular Functions
	Koh Takeuchi, Yuichi Yoshida,  Yoshinobu Kawahara
ID: 450	Probability Distillation: A  Caveat and Alternatives
	Chin-Wei Huang, Faruk Ahmed,  Kundan Kumar, Alexandre Lacoste, Aaron Courville
ID: 468	Bayesian  Optimization with Binary Auxiliary Information
	Yehong Zhang, Zhongxiang Dai,  Bryan Kian Hsiang Low
ID: 481	On Open-Universe Causal  Reasoning
	Duligur Ibeling, Thomas  Icard
ID: 496	Embarrassingly Parallel MCMC  using Deep Invertible Transformations
	Diego Mesquita, Paul Blomstedt,  Samuel Kaski
ID: 508	Fast  Proximal Gradient Descent for A Class of Non-convex and Non-smooth Sparse  Learning Problems
	Yingzhen Yang, Jiahui Yu
ID: 511	Block  Neural Autoregressive Flow
	Nicola De Cao, Wilker Aziz, Ivan  Titov
ID: 512	Exclusivity Graph Approach to  Instrumental Inequalities
	Davide Poderini, Rafael Chaves,  Iris Agresti, Gonzalo Carvacho, Fabio Sciarrino

-END-

专 · 知

专知，专业可信的人工智能知识分发，让认知协作更快更好！欢迎登录www.zhuanzhi.ai，注册登录专知，获取更多AI知识资料！

欢迎微信扫一扫加入专知人工智能知识星球群，获取最新AI专业干货知识教程视频资料和与专家交流咨询！

请加专知小助手微信（扫一扫如下二维码添加），加入专知人工智能主题群，咨询技术商务合作~

专知《深度学习:算法到实战》课程全部完成！550+位同学在学习，现在报名，限时优惠！网易云课堂人工智能畅销榜首位！

点击“阅读原文”，了解报名专知《深度学习:算法到实战》课程