Papers
Optimal Regularized Dual Averaging Methods for Stochastic Optimization
Xi Chen, Qihang Lin, Javier Pena
Parametric Local Metric Learning for Nearest Neighbor Classification
Jun Wang, Alexandros Kalousis, Adam Woznica
Patient Risk Stratification for Hospital-Associated C. diff as a Time-Series Classification Task
Jenna Wiens, Eric Horvitz, John V. Guttag
Perceptron Learning of SAT
Alex Flint, Matthew Blaschko
Perfect Dimensionality Recovery by Variational Bayesian PCA
Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama et al.
Persistent Homology for Learning Densities with Bounded Support
Florian T. Pokorny, Hedvig Kjellström, Danica Kragic et al.
Phoneme Classification using Constrained Variational Gaussian Process Dynamical System
Hyunsin Park, Sungrack Yun, Sanghyuk Park et al.
Pointwise Tracking the Optimal Regression Function
Yair Wiener, Ran El-Yaniv
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek, Hugo Larochelle, Ryan P. Adams
Predicting Action Content On-Line and in Real Time before Action Onset – an Intracranial Human Study
Uri Maoz, Shengxuan Ye, Ian Ross et al.
Priors for Diversity in Generative Latent Variable Models
James T. Kwok, Ryan P. Adams
Privacy Aware Learning
Martin J. Wainwright, Michael I. Jordan, John C. Duchi
Probabilistic Event Cascades for Alzheimer's disease
Jonathan Huang, Daniel Alexander
Probabilistic Low-Rank Subspace Clustering
S. D. Babacan, Shinichi Nakajima, Minh Do
Probabilistic n-Choose-k Models for Classification and Ranking
Kevin Swersky, Brendan J. Frey, Daniel Tarlow et al.
Projection Retrieval for Classification
Madalina Fiterau, Artur Dubrawski
Proper losses for learning from partial labels
Jesús Cid-sueiro
Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders
Sanjeev Arora, Rong Ge, Ankur Moitra et al.
Proximal Newton-type methods for convex optimization
Jason Lee, Yuekai Sun, Michael Saunders
Putting Bayes to sleep
Dmitry Adamskiy, Manfred K. Warmuth, Wouter M. Koolen
Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging
Chris Hinrichs, Vikas Singh, Jiming Peng et al.
Query Complexity of Derivative-Free Optimization
Kevin G. Jamieson, Robert Nowak, Ben Recht
Random function priors for exchangeable arrays with applications to graphs and relational data
James Lloyd, Peter Orbanz, Zoubin Ghahramani et al.
Random Utility Theory for Social Choice
Hossein Azari, David Parks, Lirong Xia
Rational inference of relative preferences
Nisheeth Srivastava, Paul R. Schrater