Papers
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation
Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir
Deep Mixture of Experts via Shallow Embedding
Xin Wang, Fisher Yu, Lisa Dunlap et al.
An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient
Pan Xu, Felicia Gao, Quanquan Gu
Perturbed-History Exploration in Stochastic Linear Bandits
Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh et al.
A Tighter Analysis of Randomised Policy Iteration
Meet Taraviya, Shivaram Kalyanakrishnan
Augmenting and Tuning Knowledge Graph Embeddings
Robert Bamler, Farnood Salehi, Stephan Mandt
Efficient Neural Network Verification with Exactness Characterization
Krishnamurthy (Dj) Dvijotham, Robert Stanforth, Sven Gowal et al.
Periodic Kernel Approximation by Index Set Fourier Series Features
Anthony Tompkins, Fabio Ramos
Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning
Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee
Fisher-Bures Adversary Graph Convolutional Networks
Ke Sun, Piotr Koniusz, Zhen Wang
A Fast Proximal Point Method for Computing Exact Wasserstein Distance
Yujia Xie, Xiangfeng Wang, Ruijia Wang et al.
Randomized Value Functions via Multiplicative Normalizing Flows
Ahmed Touati, Harsh Satija, Joshua Romoff et al.
Approximate Inference in Structured Instances with Noisy Categorical Observations
Alireza Heidari, Ihab F. Ilyas, Theodoros Rekatsinas
Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem
Karen Ullrich, Rianne van den Berg, Marcus Brubaker et al.
General Identifiability with Arbitrary Surrogate Experiments
Sanghack Lee, Juan D. Correa, Elias Bareinboim
Joint Nonparametric Precision Matrix Estimation with Confounding
Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo
Random Search and Reproducibility for Neural Architecture Search
Liam Li, Ameet Talwalkar
The Role of Memory in Stochastic Optimization
Antonio Orvieto, Jonas Kohler, Aurelien Lucchi
Towards Robust Relational Causal Discovery
Sanghack Lee, Vasant Honavar
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
Robert Peharz, Antonio Vergari, Karl Stelzner et al.
Stability of Linear Structural Equation Models of Causal Inference
Karthik Abhinav Sankararaman, Anand Louis, Navin Goyal
Cubic Regularization with Momentum for Nonconvex Optimization
Zhe Wang, Yi Zhou, Yingbin Liang et al.
Efficient Planning Under Uncertainty with Incremental Refinement
Juan Carlos Saborío, Joachim Hertzberg
Domain Generalization via Multidomain Discriminant Analysis
Shoubo Hu, Kun Zhang, Zhitang Chen et al.