conftrace_
← Machine Learning
Machine Learning ›

Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

1
52
337
806
3400
3289
'00
'05
'10
'15
'20
'25

Papers (including subtopics)

Learnability and the doubling dimension NIPS 2006
Sample Complexity of Policy Search with Known Dynamics NIPS 2006
Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NIPS 2006
Denoising and Dimension Reduction in Feature Space NIPS 2006
Statistical Comparisons of Classifiers over Multiple Data Sets JMLR 2006
On the Complexity of Learning Lexicographic Strategies JMLR 2006
Bounds for Linear Multi-Task Learning JMLR 2006
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals JMLR 2006
Learning the Structure of Linear Latent Variable Models JMLR 2006
In Search of Non-Gaussian Components of a High-Dimensional Distribution JMLR 2006
Some Discriminant-Based PAC Algorithms JMLR 2006
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting JMLR 2006
Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition JMLR 2006
Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation JMLR 2006
Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach JMLR 2006
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis JMLR 2006
Learning Coordinate Covariances via Gradients JMLR 2006
Toward Attribute Efficient Learning of Decision Lists and Parities JMLR 2006
A Direct Method for Building Sparse Kernel Learning Algorithms JMLR 2006
Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation JMLR 2006
Learning Minimum Volume Sets JMLR 2006
Some Theory for Generalized Boosting Algorithms JMLR 2006
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines JMLR 2006
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms JMLR 2006
Infinite-σ Limits For Tikhonov Regularization JMLR 2006