conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Optimization

14,983 papers

Papers per year

18
112
342
1289
1646
'05
'10
'15
'20
'25

Papers

Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning NIPS 2008
An interior-point stochastic approximation method and an L1-regularized delta rule NIPS 2008
Online Metric Learning and Fast Similarity Search NIPS 2008
Bayesian Network Score Approximation using a Metagraph Kernel NIPS 2008
Fast Rates for Regularized Objectives NIPS 2008
Regularized Policy Iteration NIPS 2008
Dimensionality Reduction for Data in Multiple Feature Representations NIPS 2008
Mind the Duality Gap: Logarithmic regret algorithms for online optimization NIPS 2008
Multi-label Multiple Kernel Learning NIPS 2008
Multi-resolution Exploration in Continuous Spaces NIPS 2008
Sparsity of SVMs that use the epsilon-insensitive loss NIPS 2008
Automatic online tuning for fast Gaussian summation NIPS 2008
Estimating Robust Query Models with Convex Optimization NIPS 2008
Near-optimal Regret Bounds for Reinforcement Learning NIPS 2008
Online Optimization in X-Armed Bandits NIPS 2008
On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost NIPS 2008
Fitted Q-iteration by Advantage Weighted Regression NIPS 2008
On the Generalization Ability of Online Strongly Convex Programming Algorithms NIPS 2008
Clustered Multi-Task Learning: A Convex Formulation NIPS 2008
One sketch for all: Theory and Application of Conditional Random Sampling NIPS 2008
Algorithms for Sparse Linear Classifiers in the Massive Data Setting JMLR 2008
Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data JMLR 2008
Multi-class Discriminant Kernel Learning via Convex Programming JMLR 2008
Bouligand Derivatives and Robustness of Support Vector Machines for Regression JMLR 2008
Accelerated Neural Evolution through Cooperatively Coevolved Synapses JMLR 2008