Papers
Tree Decomposition for Large-Scale SVM Problems
Fu Chang, Chien-Yang Guo, Xiao-Rong Lin et al.
Linear Algorithms for Online Multitask Classification
Giovanni Cavallanti, Nicoló Cesa-Bianchi, Claudio Gentile
Expectation Truncation and the Benefits of Preselection In Training Generative Models
Jörg Lücke, Julian Eggert
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
Nguyen Xuan Vinh, Julien Epps, James Bailey
Regret Bounds and Minimax Policies under Partial Monitoring
Jean-Yves Audibert, Sébastien Bubeck
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Ido Cohn, Tal El-Hay, Nir Friedman et al.
Using Contextual Representations to Efficiently Learn Context-Free Languages
Alexander Clark, Rémi Eyraud, Amaury Habrard
Topology Selection in Graphical Models of Autoregressive Processes
Jitkomut Songsiri, Lieven Vandenberghe
Learnability, Stability and Uniform Convergence
Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro et al.
Stochastic Composite Likelihood
Joshua V. Dillon, Guy Lebanon
WEKA−Experiences with a Java Open-Source Project
Remco R. Bouckaert, Eibe Frank, Mark A. Hall et al.
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
Miloš Radovanović
Rademacher Complexities and Bounding the Excess Risk in Active Learning
Vladimir Koltchinskii
Sparse Semi-supervised Learning Using Conjugate Functions
Shiliang Sun, John Shawe-Taylor
Composite Binary Losses
Mark D. Reid, Robert C. Williamson
High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency
Dapo Omidiran, Martin J. Wainwright
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers
Franz Pernkopf, Jeff A. Bilmes
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
Restricted Eigenvalue Properties for Correlated Gaussian Designs
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
Erratum: SGDQN is Less Careful than Expected
Antoine Bordes, Léon Bottou, Patrick Gallinari et al.
Regularized Discriminant Analysis, Ridge Regression and Beyond
Zhihua Zhang, Guang Dai, Congfu Xu et al.
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
Qiang Wu, Justin Guinney, Mauro Maggioni et al.