← Optimization & Theory
Machine Learning › Optimization & Theory ›

Theory

4950 directly classified papers

Papers per year

Papers

(weak) Calibration is Computationally Hard COLT 2012
Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions NIPS 2012
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation NIPS 2012
The Bethe Partition Function of Log-supermodular Graphical Models NIPS 2012
Mixability in Statistical Learning NIPS 2012
Submodular-Bregman and the Lovász-Bregman Divergences with Applications NIPS 2012
Testing for Membership to the IFRA and the NBU Classes of Distributions AISTATS 2012
Active Learning of Multi-Index Function Models NIPS 2012
Spectral Learning of General Weighted Automata via Constrained Matrix Completion NIPS 2012
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NIPS 2012
Structured Sparsity and Generalization JMLR 2012
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data NIPS 2012
Regression for sets of polynomial equations AISTATS 2012
Convergence Rate Analysis of MAP Coordinate Minimization Algorithms NIPS 2012
Minimax hypothesis testing for curve registration AISTATS 2012
Learning Manifolds with K-Means and K-Flats NIPS 2012
Locally Defined Principal Curves and Surfaces JMLR 2011
The Fast Convergence of Boosting NIPS 2011
Selecting the State-Representation in Reinforcement Learning NIPS 2011
A Convergence Analysis of Log-Linear Training NIPS 2011
Online Learning in Case of Unbounded Losses Using Follow the Perturbed Leader Algorithm JMLR 2011
Discussion of “Learning Equivalence Classes of Acyclic Models with Latent and Selection Variables from Multiple Datasets with Overlapping Variables” AISTATS 2011
Union Support Recovery in Multi-task Learning JMLR 2011
Uniqueness of Belief Propagation on Signed Graphs NIPS 2011
Discussion of “A conditional game for comparing approximations” AISTATS 2011