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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

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Papers (including subtopics)

Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform NIPS 2010
Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models NIPS 2010
Active Instance Sampling via Matrix Partition NIPS 2010
Functional form of motion priors in human motion perception NIPS 2010
The LASSO risk: asymptotic results and real world examples NIPS 2010
Towards Property-Based Classification of Clustering Paradigms NIPS 2010
Implicit encoding of prior probabilities in optimal neural populations NIPS 2010
Distributed Dual Averaging In Networks NIPS 2010
Probabilistic Inference and Differential Privacy NIPS 2010
Copula Processes NIPS 2010
Learning invariant features using the Transformed Indian Buffet Process NIPS 2010
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA NIPS 2010
Fast detection of multiple change-points shared by many signals using group LARS NIPS 2010
Robust PCA via Outlier Pursuit NIPS 2010
Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition NIPS 2010
Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NIPS 2010
Pairwise Measures of Causal Direction in Linear Non-Gaussian Acyclic Models ACML 2010
Learning Polyhedral Classifiers Using Logistic Function ACML 2010
Ellipsoidal Support Vector Machines ACML 2010
Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering ACML 2010
Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation ACML 2010
Variational Relevance Vector Machine for Tabular Data ACML 2010
Hierarchical Gaussian Process Regression ACML 2010
Content-based Image Retrieval with Multinomial Relevance Feedback ACML 2010
The Coding Divergence for Measuring the Complexity of Separating Two Sets ACML 2010