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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)

Exploiting the Limits of Structure Learning via Inherent Symmetry AISTATS 2014
Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics AISTATS 2014
Tilted Variational Bayes AISTATS 2014
On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning AISTATS 2014
Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors AISTATS 2014
Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees AISTATS 2014
Latent Gaussian Models for Topic Modeling AISTATS 2014
A Finite-Sample Generalization Bound for Semiparametric Regression: Partially Linear Models AISTATS 2014
High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation AISTATS 2014
Near Optimal Bayesian Active Learning for Decision Making AISTATS 2014
A Level-set Hit-and-run Sampler for Quasi-Concave Distributions AISTATS 2014
Scalable Collaborative Bayesian Preference Learning AISTATS 2014
A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data AISTATS 2014
Scalable Variational Bayesian Matrix Factorization with Side Information AISTATS 2014
Algebraic Reconstruction Bounds and Explicit Inversion for Phase Retrieval at the Identifiability Threshold AISTATS 2014
Low-Rank Spectral Learning AISTATS 2014
Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data AISTATS 2014
Incremental Tree-Based Inference with Dependent Normalized Random Measures AISTATS 2014
PAC-Bayesian Collective Stability AISTATS 2014
Active Area Search via Bayesian Quadrature AISTATS 2014
Efficient Lifting of MAP LP Relaxations Using k-Locality AISTATS 2014
A Geometric Algorithm for Scalable Multiple Kernel Learning AISTATS 2014
On the Testability of Models with Missing Data AISTATS 2014
Selective Sampling with Drift AISTATS 2014
The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling AISTATS 2014