UAI 2020
140 papers
Active Model Estimation in Markov Decision Processes
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric Amortized Bayesian Optimization over Discrete Spaces
Kevin Swersky, Yulia Rubanova, David Dohan, Kevin Murphy An Interpretable and Sample Efficient Deep Kernel for Gaussian Process
Yijue Dai, Tianjian Zhang, Zhidi Lin, Feng Yin, Sergios Theodoridis, Shuguang Cui Automated Dependence Plots
David Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar Bayesian Online Prediction of Change Points
Diego Agudelo-España, Sebastian Gomez-Gonzalez, Stefan Bauer, Bernhard Schölkopf, Jan Peters C-MI-GAN : Estimation of Conditional Mutual Information Using MinMax Formulation
Arnab Mondal, Arnab Bhattacharjee, Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan, A P Prathosh Complete Dictionary Learning via $\ell_p$-Norm Maximization
Yifei Shen, Ye Xue, Jun Zhang, Khaled Letaief, Vincent Lau Compositional Uncertainty in Deep Gaussian Processes
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill Campbell, Carl Henrik Ek Deep Sigma Point Processes
Martin Jankowiak, Geoff Pleiss, Jacob Gardner Efficient Rollout Strategies for Bayesian Optimization
Eric Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt Election Control by Manipulating Issue Significance
Andrew Estornell, Sanmay Das, Edith Elkind, Yevgeniy Vorobeychik Fair Contextual Multi-Armed Bandits: Theory and Experiments
Yifang Chen, Alex Cuellar, Haipeng Luo, Jignesh Modi, Heramb Nemlekar, Stefanos Nikolaidis Graphical Continuous Lyapunov Models
Gherardo Varando, Niels Richard Hansen Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation
Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Molchanov, Dmitry Vetrov How Private Are Commonly-Used Voting Rules?
Ao Liu, Yun Lu, Lirong Xia, Vassilis Zikas Lagrangian Decomposition for Neural Network Verification
Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip Torr, M. Pawan Kumar MaskAAE: Latent Space Optimization for Adversarial Auto-Encoders
Arnab Mondal, Sankalan Pal Chowdhury, Aravind Jayendran, Himanshu Asnani, Parag Singla, A P Prathosh Multitask Soft Option Learning
Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N Siddharth, Wendelin Boehmer, Shimon Whiteson Non Parametric Graph Learning for Bayesian Graph Neural Networks
Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates On the Design of Consequential Ranking Algorithms
Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez Ordering Variables for Weighted Model Integration
Vincent Derkinderen, Evert Heylen, Pedro Zuidberg Dos Martires, Samuel Kolb, Luc Raedt Popularity Agnostic Evaluation of Knowledge Graph Embeddings
Aisha Mohamed, Shameem Parambath, Zoi Kaoudi, Ashraf Aboulnaga PoRB-Nets: Poisson Process Radial Basis Function Networks
Beau Coker, Melanie Fernandez Pradier, Finale Doshi-Velez Probabilistic Safety for Bayesian Neural Networks
Matthew Wicker, Luca Laurenti, Andrea Patane, Marta Kwiatkowska Robust $k$-Means++
Amit Deshpande, Praneeth Kacham, Rameshwar Pratap Robust Spatial-Temporal Incident Prediction
Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik Semi-Bandit Optimization in the Dispersed Setting
Maria-Florina Balcan, Travis Dick, Wesley Pegden Semi-Supervised Sequential Generative Models
Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood Sensor Placement for Spatial Gaussian Processes with Integral Observations
Krista Longi, Chang Rajani, Tom Sillanpää, Joni Mäkinen, Timo Rauhala, Ari Salmi, Edward Haeggström, Arto Klami Skewness Ranking Optimization for Personalized Recommendation
Chuan-Ju Wang, Yu-Neng Chuang, Chih-Ming Chen, Ming-Feng Tsai Slice Sampling for General Completely Random Measures
Peiyuan Zhu, Alexandre Bouchard-Cote, Trevor Campbell Stochastic Variational Inference for Dynamic Correlated Topic Models
Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai Structure Learning for Cyclic Linear Causal Models
Carlos Amendola, Philipp Dettling, Mathias Drton, Federica Onori, Jun Wu Submodular Bandit Problem Under Multiple Constraints
Sho Takemori, Masahiro Sato, Takashi Sonoda, Janmajay Singh, Tomoko Ohkuma The Indian Chefs Process
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Marcel Gerven, François Laviolette Verifying Individual Fairness in Machine Learning Models
Philips George John, Deepak Vijaykeerthy, Diptikalyan Saha