Papers
8,340 papers found
Predictive Entropy Search for Bayesian Optimization with Unknown Constraints
Jose Miguel Hernandez-Lobato, Michael Gelbart, Matthew Hoffman et al.
Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons
Dohyung Park, Joe Neeman, Jin Zhang et al.
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo
Yu-Xiang Wang, Stephen Fienberg, Alex Smola
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks
Jose Miguel Hernandez-Lobato, Ryan Adams
Proteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach
Jason Pacheco, Erik Sudderth
PU Learning for Matrix Completion
Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit Dhillon
Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCA
Bo Xin, David Wipf
Qualitative Multi-Armed Bandits: A Quantile-Based Approach
Balazs Szorenyi, Robert Busa-Fekete, Paul Weng et al.
Rademacher Observations, Private Data, and Boosting
Richard Nock, Giorgio Patrini, Arik Friedman
Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions
Alina Ene, Huy Nguyen
Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top
Arun Rajkumar, Suprovat Ghoshal, Lek-Heng Lim et al.
Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood
Kohei Hayashi, Shin-ichi Maeda, Ryohei Fujimaki
Reified Context Models
Jacob Steinhardt, Percy Liang
Removing systematic errors for exoplanet search via latent causes
Bernhard Schölkopf, David Hogg, Dun Wang et al.
Risk and Regret of Hierarchical Bayesian Learners
Jonathan Huggins, Josh Tenenbaum
Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes
Huitong Qiu, Sheng Xu, Fang Han et al.
Robust partially observable Markov decision process
Takayuki Osogami
Safe Exploration for Optimization with Gaussian Processes
Yanan Sui, Alkis Gotovos, Joel Burdick et al.
Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret
Haitham Bou Ammar, Rasul Tutunov, Eric Eaton
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices
Jie Wang, Jieping Ye
Safe Subspace Screening for Nuclear Norm Regularized Least Squares Problems
Qiang Zhou, Qi Zhao
Scalable Bayesian Optimization Using Deep Neural Networks
Jasper Snoek, Oren Rippel, Kevin Swersky et al.
Scalable Deep Poisson Factor Analysis for Topic Modeling
Zhe Gan, Changyou Chen, Ricardo Henao et al.
Scalable Model Selection for Large-Scale Factorial Relational Models
Chunchen Liu, Lu Feng, Ryohei Fujimaki et al.
Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes
Yves-Laurent Kom Samo, Stephen Roberts