Papers
Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms
Ping Ma, Xinlian Zhang, Xin Xing et al.
Asynchronous Gibbs Sampling
Alexander Terenin, Daniel Simpson, David Draper
A Theoretical and Practical Framework for Regression and Classification from Truncated Samples
Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis
A Theoretical Case Study of Structured Variational Inference for Community Detection
Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar
A Three Sample Hypothesis Test for Evaluating Generative Models
Casey Meehan, Kamalika Chaudhuri, Sanjoy Dasgupta
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games
Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien et al.
A Topology Layer for Machine Learning
Rickard Brüel Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath et al.
Auditing ML Models for Individual Bias and Unfairness
Songkai Xue, Mikhail Yurochkin, Yuekai Sun
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach
Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil
A Unified Statistically Efficient Estimation Framework for Unnormalized Models
Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi et al.
A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments
Adam Foster, Martin Jankowiak, Matthew O’Meara et al.
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent
Eduard Gorbunov, Filip Hanzely, Peter Richtarik
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models
Theo Galy-Fajou, Florian Wenzel, Manfred Opper
Automatic Differentiation of Sketched Regression
Hang Liao, Barak A. Pearlmutter, Vamsi K. Potluru et al.
Automatic Differentiation of Some First-Order Methods in Parametric Optimization
Sheheryar Mehmood, Peter Ochs
A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models
Ziyu Wang, Shuyu Cheng, Li Yueru et al.
Balanced Off-Policy Evaluation in General Action Spaces
Arjun Sondhi, David Arbour, Drew Dimmery
Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration
Matteo Papini, Andrea Battistello, Marcello Restelli
Bandit Convex Optimization in Non-stationary Environments
Peng Zhao, Guanghui Wang, Lijun Zhang et al.
Bandit optimisation of functions in the Matérn kernel RKHS
David Janz, David Burt, Javier Gonzalez
BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders
Kaspar Märtens, Christopher Yau
Bayesian experimental design using regularized determinantal point processes
Michal Derezinski, Feynman Liang, Michael Mahoney
Bayesian Image Classification with Deep Convolutional Gaussian Processes
Vincent Dutordoir, Mark Wilk, Artem Artemev et al.
Bayesian Reinforcement Learning via Deep, Sparse Sampling
Divya Grover, Debabrota Basu, Christos Dimitrakakis