Papers
Prediction With Expert Advice For The Brier Game
Vladimir Vovk, Fedor Zhdanov
Reinforcement Learning in Finite MDPs: PAC Analysis
Alexander L. Strehl, Lihong Li, Michael L. Littman
Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions
Lisa Hellerstein, Bernard Rosell, Eric Bach et al.
Estimating Labels from Label Proportions
Novi Quadrianto, Alex J. Smola, Tibério S. Caetano et al.
Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors
Mathias Drton, Michael Eichler, Thomas S. Richardson
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs
Han Liu, John Lafferty, Larry Wasserman
Learning Nondeterministic Classifiers
Juan José del Coz, Jorge Díez, Antonio Bahamonde
Margin-based Ranking and an Equivalence between AdaBoost and RankBoost
Cynthia Rudin, Robert E. Schapire
Discriminative Learning Under Covariate Shift
Steffen Bickel, Michael Brückner, Tobias Scheffer
RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments
Brian Tanner, Adam White
Deterministic Error Analysis of Support Vector Regression and Related Regularized Kernel Methods
Christian Rieger, Barbara Zwicknagl
An Anticorrelation Kernel for Subsystem Training in Multiple Classifier Systems
Luciana Ferrer, Kemal Sönmez, Elizabeth Shriberg
Evolutionary Model Type Selection for Global Surrogate Modeling
Dirk Gorissen, Tom Dhaene, Filip De Turck
Ultrahigh Dimensional Feature Selection: Beyond The Linear Model
Jianqing Fan, Richard Samworth, Yichao Wu
Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection
Jie Chen, Haw-ren Fang, Yousef Saad
Provably Efficient Learning with Typed Parametric Models
Emma Brunskill, Bethany R. Leffler, Lihong Li et al.
Hybrid MPI/OpenMP Parallel Linear Support Vector Machine Training
Kristian Woodsend, Jacek Gondzio
Learning Approximate Sequential Patterns for Classification
Zeeshan Syed, Piotr Indyk, John Guttag
Learning Acyclic Probabilistic Circuits Using Test Paths
Dana Angluin, James Aspnes, Jiang Chen et al.
CarpeDiem: Optimizing the Viterbi Algorithm and Applications to Supervised Sequential Learning
Roberto Esposito, Daniele P. Radicioni
Nonlinear Models Using Dirichlet Process Mixtures
Babak Shahbaba, Radford Neal
Distributed Algorithms for Topic Models
David Newman, Arthur Asuncion, Padhraic Smyth et al.
Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning
Halbert White, Karim Chalak