Papers
8,340 papers found
PAC-inspired Option Discovery in Lifelong Reinforcement Learning
Emma Brunskill, Lihong Li
Pitfalls in the use of Parallel Inference for the Dirichlet Process
Yarin Gal, Zoubin Ghahramani
Prediction with Limited Advice and Multiarmed Bandits with Paid Observations
Yevgeny Seldin, Peter Bartlett, Koby Crammer et al.
Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows
Robert Busa-Fekete, Eyke Huellermeier, Balázs Szörényi
Preserving Modes and Messages via Diverse Particle Selection
Jason Pacheco, Silvia Zuffi, Michael Black et al.
Probabilistic Matrix Factorization with Non-random Missing Data
Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani
Probabilistic Partial Canonical Correlation Analysis
Yusuke Mukuta, Harada
Programming by Feedback
Marc Schoenauer, Riad Akrour, Michele Sebag et al.
Provable Bounds for Learning Some Deep Representations
Sanjeev Arora, Aditya Bhaskara, Rong Ge et al.
Pursuit-Evasion Without Regret, with an Application to Trading
Lili Dworkin, Michael Kearns, Yuriy Nevmyvaka
Putting MRFs on a Tensor Train
Alexander Novikov, Anton Rodomanov, Anton Osokin et al.
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Jiyan Yang, Vikas Sindhwani, Haim Avron et al.
Randomized Nonlinear Component Analysis
David Lopez-Paz, Suvrit Sra, Alex Smola et al.
Rank-One Matrix Pursuit for Matrix Completion
Zheng Wang, Ming-Jun Lai, Zhaosong Lu et al.
Rectangular Tiling Process
Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura et al.
Recurrent Convolutional Neural Networks for Scene Labeling
Pedro Pinheiro, Ronan Collobert
Reducing Dueling Bandits to Cardinal Bandits
Nir Ailon, Zohar Karnin, Thorsten Joachims
Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem
Masrour Zoghi, Shimon Whiteson, Remi Munos et al.
Riemannian Pursuit for Big Matrix Recovery
Mingkui Tan, Ivor W. Tsang, Li Wang et al.
Robust and Efficient Kernel Hyperparameter Paths with Guarantees
Joachim Giesen, Soeren Laue, Patrick Wieschollek
Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization
Hua Wang, Feiping Nie, Heng Huang
Robust Inverse Covariance Estimation under Noisy Measurements
Jun-Kun Wang, Shou-de Lin
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification
Junfeng Wen, Chun-Nam Yu, Russell Greiner
Robust Principal Component Analysis with Complex Noise
Qian Zhao, Deyu Meng, Zongben Xu et al.
Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models
Shike Mei, Jun Zhu, Jerry Zhu