Papers
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Samuel Ritter, David G. T. Barrett, Adam Santoro et al.
Active Learning for Accurate Estimation of Linear Models
Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric
Real-Time Adaptive Image Compression
Oren Rippel, Lubomir Bourdev
Parallel Multiscale Autoregressive Density Estimation
Scott Reed, Aäron Oord, Nal Kalchbrenner et al.
Large-Scale Evolution of Image Classifiers
Esteban Real, Sherry Moore, Andrew Selle et al.
Equivariance Through Parameter-Sharing
Siamak Ravanbakhsh, Jeff Schneider, Barnabás Póczos
High Dimensional Bayesian Optimization with Elastic Gaussian Process
Santu Rana, Cheng Li, Sunil Gupta et al.
Innovation Pursuit: A New Approach to the Subspace Clustering Problem
Mostafa Rahmani, George Atia
Coherence Pursuit: Fast, Simple, and Robust Subspace Recovery
Mostafa Rahmani, George Atia
Estimating the unseen from multiple populations
Aditi Raghunathan, Gregory Valiant, James Zou
On the Expressive Power of Deep Neural Networks
Maithra Raghu, Ben Poole, Jon Kleinberg et al.
Online and Linear-Time Attention by Enforcing Monotonic Alignments
Colin Raffel, Minh-Thang Luong, Peter J. Liu et al.
Neural Episodic Control
Alexander Pritzel, Benigno Uria, Sriram Srinivasan et al.
Robust Adversarial Reinforcement Learning
Lerrel Pinto, James Davidson, Rahul Sukthankar et al.
Multi-task Learning with Labeled and Unlabeled Tasks
Anastasia Pentina, Christoph H. Lampert
Geometry of Neural Network Loss Surfaces via Random Matrix Theory
Jeffrey Pennington, Yasaman Bahri
Asynchronous Distributed Variational Gaussian Process for Regression
Hao Peng, Shandian Zhe, Xiao Zhang et al.
Curiosity-driven Exploration by Self-supervised Prediction
Deepak Pathak, Pulkit Agrawal, Alexei A. Efros et al.
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery
Ashkan Panahi, Devdatt Dubhashi, Fredrik D. Johansson et al.
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control
Yunpeng Pan, Xinyan Yan, Evangelos A. Theodorou et al.
A Birth-Death Process for Feature Allocation
Konstantina Palla, David Knowles, Zoubin Ghahramani
Stochastic Bouncy Particle Sampler
Ari Pakman, Dar Gilboa, David Carlson et al.
Dictionary Learning Based on Sparse Distribution Tomography
Pedram Pad, Farnood Salehi, Elisa Celis et al.
Count-Based Exploration with Neural Density Models
Georg Ostrovski, Marc G. Bellemare, Aäron Oord et al.
Bidirectional Learning for Time-series Models with Hidden Units
Takayuki Osogami, Hiroshi Kajino, Taro Sekiyama