Papers
Estimating Mutual Information for Discrete-Continuous Mixtures
Weihao Gao, Sreeram Kannan, Sewoong Oh et al.
On the Model Shrinkage Effect of Gamma Process Edge Partition Models
Iku Ohama, Issei Sato, Takuya Kida et al.
Tensor Biclustering
Soheil Feizi, Hamid Javadi, David Tse
Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues
Noga Alon, Moshe Babaioff, Yannai A. Gonczarowski et al.
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J Maddison et al.
Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting
Rebecca Morrison, Ricardo Baptista, Youssef Marzouk
Adaptive Batch Size for Safe Policy Gradients
Matteo Papini, Matteo Pirotta, Marcello Restelli
Trimmed Density Ratio Estimation
Song Liu, Akiko Takeda, Taiji Suzuki et al.
Simple strategies for recovering inner products from coarsely quantized random projections
Ping Li, Martin Slawski
A Learning Error Analysis for Structured Prediction with Approximate Inference
Yuanbin Wu, Man Lan, Shiliang Sun et al.
ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization
Yi Xu, Mingrui Liu, Qihang Lin et al.
Approximation Algorithms for ℓ_0-Low Rank Approximation
Karl Bringmann, Pavel Kolev, David Woodruff
Deep Supervised Discrete Hashing
Qi Li, Zhenan Sun, Ran He et al.
QMDP-Net: Deep Learning for Planning under Partial Observability
Peter Karkus, David Hsu, Wee Sun Lee
Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos
Gerasimos Palaiopanos, Ioannis Panageas, Georgios Piliouras
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference
Geoffrey Roeder, Yuhuai Wu, David K. Duvenaud
Hierarchical Clustering Beyond the Worst-Case
Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn
Incorporating Side Information by Adaptive Convolution
Di Kang, Debarun Dhar, Antoni Chan
Learning multiple visual domains with residual adapters
Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi
Scalable Variational Inference for Dynamical Systems
Nico S Gorbach, Stefan Bauer, Joachim M Buhmann
Consistent Robust Regression
Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban et al.
Compatible Reward Inverse Reinforcement Learning
Alberto Maria Metelli, Matteo Pirotta, Marcello Restelli
From Bayesian Sparsity to Gated Recurrent Nets
Hao He, Bo Xin, Satoshi Ikehata et al.
Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication
Qian Yu, Mohammad Maddah-Ali, Salman Avestimehr
Stochastic Mirror Descent in Variationally Coherent Optimization Problems
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos et al.