Papers
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Alon Brutzkus, Amir Globerson
Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning
Noam Brown, Tuomas Sandholm
On the Sampling Problem for Kernel Quadrature
François-Xavier Briol, Chris J. Oates, Jon Cockayne et al.
Clustering High Dimensional Dynamic Data Streams
Vladimir Braverman, Gereon Frahling, Harry Lang et al.
Lazifying Conditional Gradient Algorithms
Gábor Braun, Sebastian Pokutta, Daniel Zink
Practical Gauss-Newton Optimisation for Deep Learning
Aleksandar Botev, Hippolyt Ritter, David Barber
Programming with a Differentiable Forth Interpreter
Matko Bošnjak, Tim Rocktäschel, Jason Naradowsky et al.
Compressed Sensing using Generative Models
Ashish Bora, Ajil Jalal, Eric Price et al.
Adaptive Neural Networks for Efficient Inference
Tolga Bolukbasi, Joseph Wang, Ofer Dekel et al.
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.