Papers
Maximum Selection and Ranking under Noisy Comparisons
Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati et al.
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
Jesse Engel, Cinjon Resnick, Adam Roberts et al.
Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement
Jonathan Eckstein, Noam Goldberg, Ai Kagawa
Stochastic Variance Reduction Methods for Policy Evaluation
Simon S. Du, Jianshu Chen, Lihong Li et al.
Dance Dance Convolution
Chris Donahue, Zachary C. Lipton, Julian McAuley
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh, Razvan Pascanu, Samy Bengio et al.
Probabilistic Path Hamiltonian Monte Carlo
Vu Dinh, Arman Bilge, Cheng Zhang et al.
Being Robust (in High Dimensions) Can Be Practical
Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane et al.
RobustFill: Neural Program Learning under Noisy I/O
Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju et al.
Image-to-Markup Generation with Coarse-to-Fine Attention
Yuntian Deng, Anssi Kanervisto, Jeffrey Ling et al.
iSurvive: An Interpretable, Event-time Prediction Model for mHealth
Walter H. Dempsey, Alexander Moreno, Christy K. Scott et al.
Consistency Analysis for Binary Classification Revisited
Krzysztof Dembczyński, Wojciech Kotłowski, Oluwasanmi Koyejo et al.
Distributed Batch Gaussian Process Optimization
Erik A. Daxberger, Bryan Kian Hsiang Low
An Infinite Hidden Markov Model With Similarity-Biased Transitions
Colin Reimer Dawson, Chaofan Huang, Clayton T. Morrison
Language Modeling with Gated Convolutional Networks
Yann N. Dauphin, Angela Fan, Michael Auli et al.
Logarithmic Time One-Against-Some
Hal Daumé III, Nikos Karampatziakis, John Langford et al.
Stochastic Generative Hashing
Bo Dai, Ruiqi Guo, Sanjiv Kumar et al.
Understanding Synthetic Gradients and Decoupled Neural Interfaces
Wojciech Marian Czarnecki, Grzegorz Świrszcz, Max Jaderberg et al.
Soft-DTW: a Differentiable Loss Function for Time-Series
Marco Cuturi, Mathieu Blondel
Random Feature Expansions for Deep Gaussian Processes
Kurt Cutajar, Edwin V. Bonilla, Pietro Michiardi et al.
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Corinna Cortes, Xavier Gonzalvo, Vitaly Kuznetsov et al.
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
Yulai Cong, Bo Chen, Hongwei Liu et al.
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cisse, Piotr Bojanowski, Edouard Grave et al.