Papers
New Learning Methods for Supervised and Unsupervised Preference Aggregation
Maksims N. Volkovs, Richard S. Zemel
A Reliable Effective Terascale Linear Learning System
Alekh Agarwal, Oliveier Chapelle, Miroslav Dudík et al.
Gibbs Max-margin Topic Models with Data Augmentation
Jun Zhu, Ning Chen, Hugh Perkins et al.
Improving Prediction from Dirichlet Process Mixtures via Enrichment
Sara Wade, David B. Dunson, Sonia Petrone et al.
Conditional Random Field with High-order Dependencies for Sequence Labeling and Segmentation
Nguyen Viet Cuong, Nan Ye, Wee Sun Lee et al.
Natural Evolution Strategies
Daan Wierstra, Tom Schaul, Tobias Glasmachers et al.
An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation
Henning Sprekeler, Tiziano Zito, Laurenz Wiskott
Active Learning Using Smooth Relative Regret Approximations with Applications
Nir Ailon, Ron Begleiter, Esther Ezra
Policy Evaluation with Temporal Differences: A Survey and Comparison
Christoph Dann, Gerhard Neumann, Jan Peters
A Novel M-Estimator for Robust PCA
Teng Zhang, Gilad Lerman
Clustering Hidden Markov Models with Variational HEM
Emanuele Coviello, Antoni B. Chan, Gert R.G. Lanckriet
Reinforcement Learning for Closed-Loop Propofol Anesthesia: A Study in Human Volunteers
Brett L Moore, Larry D Pyeatt, Vivekanand Kulkarni et al.
Random Intersection Trees
Rajen Dinesh Shah, Nicolai Meinshausen
Link Prediction in Graphs with Autoregressive Features
Emile Richard, Stéphane Gaïffas, Nicolas Vayatis
Ground Metric Learning
Marco Cuturi, David Avis
Improving Markov Network Structure Learning Using Decision Trees
Daniel Lowd, Jesse Davis
LIBOL: A Library for Online Learning Algorithms
Steven C.H. Hoi, Jialei Wang, Peilin Zhao
The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R
Haotian Pang, Han Liu, Robert Vanderbei
Node-Based Learning of Multiple Gaussian Graphical Models
Karthik Mohan, Palma London, Maryam Fazel et al.
Unbiased Generative Semi-Supervised Learning
Patrick Fox-Roberts, Edward Rosten
Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
Off-policy Learning With Eligibility Traces: A Survey
Matthieu Geist, Bruno Scherrer
Information Theoretical Estimators Toolbox
Zoltán Szabó