Papers
8,340 papers found
High Confidence Policy Improvement
Philip Thomas, Georgios Theocharous, Mohammad Ghavamzadeh
High Dimensional Bayesian Optimisation and Bandits via Additive Models
Kirthevasan Kandasamy, Jeff Schneider, Barnabas Poczos
How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances?
Senjian An, Farid Boussaid, Mohammed Bennamoun
How Hard is Inference for Structured Prediction?
Amir Globerson, Tim Roughgarden, David Sontag et al.
Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning
K. Lakshmanan, Ronald Ortner, Daniil Ryabko
Inference in a Partially Observed Queuing Model with Applications in Ecology
Kevin Winner, Garrett Bernstein, Dan Sheldon
Inferring Graphs from Cascades: A Sparse Recovery Framework
Jean Pouget-Abadie, Thibaut Horel
Information Geometry and Minimum Description Length Networks
Ke Sun, Jun Wang, Alexandros Kalousis et al.
Intersecting Faces: Non-negative Matrix Factorization With New Guarantees
Rong Ge, James Zou
Is Feature Selection Secure against Training Data Poisoning?
Huang Xiao, Battista Biggio, Gavin Brown et al.
JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes
Jonathan Huggins, Karthik Narasimhan, Ardavan Saeedi et al.
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)
Andrew Wilson, Hannes Nickisch
K-hyperplane Hinge-Minimax Classifier
Margarita Osadchy, Tamir Hazan, Daniel Keren
Landmarking Manifolds with Gaussian Processes
Dawen Liang, John Paisley
Large-scale Distributed Dependent Nonparametric Trees
Zhiting Hu, Ho Qirong, Avinava Dubey et al.
Large-scale log-determinant computation through stochastic Chebyshev expansions
Insu Han, Dmitry Malioutov, Jinwoo Shin
Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing
Yasin Abbasi-Yadkori, Peter Bartlett, Xi Chen et al.
Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data
Yarin Gal, Yutian Chen, Zoubin Ghahramani
Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models
James Foulds, Shachi Kumar, Lise Getoor
Learning Deep Structured Models
Liang-Chieh Chen, Alexander Schwing, Alan Yuille et al.
Learning Fast-Mixing Models for Structured Prediction
Jacob Steinhardt, Percy Liang
Learning from Corrupted Binary Labels via Class-Probability Estimation
Aditya Menon, Brendan Van Rooyen, Cheng Soon Ong et al.
Learning Local Invariant Mahalanobis Distances
Ethan Fetaya, Shimon Ullman
Learning Parametric-Output HMMs with Two Aliased States
Roi Weiss, Boaz Nadler