← Optimization & Theory
Machine Learning › Optimization & Theory ›

Optimization

14207 directly classified papers

Papers per year

Papers

Quasi-Newton Methods for Markov Chain Monte Carlo NIPS 2011
Greedy Model Averaging NIPS 2011
Learning large-margin halfspaces with more malicious noise NIPS 2011
Higher-Order Correlation Clustering for Image Segmentation NIPS 2011
The Fast Convergence of Boosting NIPS 2011
An Exact Algorithm for F-Measure Maximization NIPS 2011
Adaptive Hedge NIPS 2011
Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression NIPS 2011
Structure Learning for Optimization NIPS 2011
A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm NIPS 2011
Learning with the weighted trace-norm under arbitrary sampling distributions NIPS 2011
Contextual Gaussian Process Bandit Optimization NIPS 2011
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels NIPS 2011
Learning to Search Efficiently in High Dimensions NIPS 2011
Multiple Instance Learning on Structured Data NIPS 2011
Efficient Offline Communication Policies for Factored Multiagent POMDPs NIPS 2011
A blind sparse deconvolution method for neural spike identification NIPS 2011
Shaping Level Sets with Submodular Functions NIPS 2011
Thinning Measurement Models and Questionnaire Design NIPS 2011
Algorithms and hardness results for parallel large margin learning NIPS 2011
Better Mini-Batch Algorithms via Accelerated Gradient Methods NIPS 2011
Statistical Tests for Optimization Efficiency NIPS 2011
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NIPS 2011
Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning NIPS 2011
On the Universality of Online Mirror Descent NIPS 2011