Papers
Efficient Second-Order Online Kernel Learning with Adaptive Embedding
Daniele Calandriello, Alessandro Lazaric, Michal Valko
Optimistic posterior sampling for reinforcement learning: worst-case regret bounds
Shipra Agrawal, Randy Jia
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
Yuhuai Wu, Elman Mansimov, Roger B Grosse et al.
A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks
Qinliang Su, xuejun Liao, Lawrence Carin
Variational Inference via χ Upper Bound Minimization
Adji Bousso Dieng, Dustin Tran, Rajesh Ranganath et al.
Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting
Yue Wang, Wei Chen, Yuting Liu et al.
Hypothesis Transfer Learning via Transformation Functions
Simon S Du, Jayanth Koushik, Aarti Singh et al.
On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning
Xingguo Li, Lin Yang, Jason Ge et al.
Successor Features for Transfer in Reinforcement Learning
Andre Barreto, Will Dabney, Remi Munos et al.
Pose Guided Person Image Generation
Liqian Ma, Xu Jia, Qianru Sun et al.
Affine-Invariant Online Optimization and the Low-rank Experts Problem
Tomer Koren, Roi Livni
Spectral Mixture Kernels for Multi-Output Gaussian Processes
Gabriel Parra, Felipe Tobar
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
Marc Lanctot, Vinicius Zambaldi, Audrunas Gruslys et al.
The power of absolute discounting: all-dimensional distribution estimation
Moein Falahatgar, Mesrob I Ohannessian, Alon Orlitsky et al.
Inverse Reward Design
Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel et al.
The Expressive Power of Neural Networks: A View from the Width
Zhou Lu, Hongming Pu, Feicheng Wang et al.
Dilated Recurrent Neural Networks
Shiyu Chang, Yang Zhang, Wei Han et al.
Statistical Cost Sharing
Eric Balkanski, Umar Syed, Sergei Vassilvitskii
Min-Max Propagation
Christopher Srinivasa, Inmar Givoni, Siamak Ravanbakhsh et al.
Reducing Reparameterization Gradient Variance
Andrew Miller, Nicholas Foti, Alexander D'Amour et al.
Sparse Embedded k-Means Clustering
Weiwei Liu, Xiaobo Shen, Ivor Tsang
Alternating minimization for dictionary learning with random initialization
Niladri Chatterji, Peter L Bartlett
Bayesian GAN
Yunus Saatci, Andrew G Wilson
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models
Alex M Lamb, Devon Hjelm, Yaroslav Ganin et al.
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
Kristof Schütt, Pieter-Jan Kindermans, Huziel Enoc Sauceda Felix et al.