Papers
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.
On Kernelized Multi-armed Bandits
Sayak Ray Chowdhury, Aditya Gopalan
Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution
Po-Wei Chou, Daniel Maturana, Sebastian Scherer
On Relaxing Determinism in Arithmetic Circuits
Arthur Choi, Adnan Darwiche
MEC: Memory-efficient Convolution for Deep Neural Network
Minsik Cho, Daniel Brand
Algorithms for ℓ_p Low-Rank Approximation
Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar et al.
Nearly Optimal Robust Matrix Completion
Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain
Learning to Aggregate Ordinal Labels by Maximizing Separating Width
Guangyong Chen, Shengyu Zhang, Di Lin et al.
Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability
Zhehui Chen, Lin F. Yang, Chris Junchi Li et al.
Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data
Xixian Chen, Michael R. Lyu, Irwin King