Papers
Unsupervised Learning by Predicting Noise
Piotr Bojanowski, Armand Joulin
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
Ilija Bogunovic, Slobodan Mitrović, Jonathan Scarlett et al.
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Andrew An Bian, Joachim M. Buhmann, Andreas Krause et al.
Efficient Online Bandit Multiclass Learning with Õ(√T) Regret
Alina Beygelzimer, Francesco Orabona, Chicheng Zhang
Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models
Garrett Bernstein, Ryan McKenna, Tao Sun et al.
Learning Texture Manifolds with the Periodic Spatial GAN
Urs Bergmann, Nikolay Jetchev, Roland Vollgraf
Neural Optimizer Search with Reinforcement Learning
Irwan Bello, Barret Zoph, Vijay Vasudevan et al.
A Distributional Perspective on Reinforcement Learning
Marc G. Bellemare, Will Dabney, Rémi Munos
Learning to Discover Sparse Graphical Models
Eugene Belilovsky, Kyle Kastner, Gael Varoquaux et al.
End-to-End Learning for Structured Prediction Energy Networks
David Belanger, Bishan Yang, Andrew McCallum
Globally Induced Forest: A Prepruning Compression Scheme
Jean-Michel Begon, Arnaud Joly, Pierre Geurts
Unimodal Probability Distributions for Deep Ordinal Classification
Christopher Beckham, Christopher Pal
Emulating the Expert: Inverse Optimization through Online Learning
Andreas Bärmann, Sebastian Pokutta, Oskar Schneider
End-to-End Differentiable Adversarial Imitation Learning
Nir Baram, Oron Anschel, Itai Caspi et al.
Dynamic Word Embeddings
Robert Bamler, Stephan Mandt
Lost Relatives of the Gumbel Trick
Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani et al.
Spectral Learning from a Single Trajectory under Finite-State Policies
Borja Balle, Odalric-Ambrym Maillard
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks
David Balduzzi, Brian McWilliams, Tony Butler-Yeoman
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
David Balduzzi, Marcus Frean, Lennox Leary et al.
Strongly-Typed Agents are Guaranteed to Interact Safely
David Balduzzi
Differentially Private Clustering in High-Dimensional Euclidean Spaces
Maria-Florina Balcan, Travis Dick, Yingyu Liang et al.
Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms
Arturs Backurs, Christos Tzamos
Learning Algorithms for Active Learning
Philip Bachman, Alessandro Sordoni, Adam Trischler
Distributed and Provably Good Seedings for k-Means in Constant Rounds
Olivier Bachem, Mario Lucic, Andreas Krause
Uniform Deviation Bounds for k-Means Clustering
Olivier Bachem, Mario Lucic, S. Hamed Hassani et al.