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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)

Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence AISTATS 2014
Robust Forward Algorithms via PAC-Bayes and Laplace Distributions AISTATS 2014
Joint Structure Learning of Multiple Non-Exchangeable Networks AISTATS 2014
Scaling Nonparametric Bayesian Inference via Subsample-Annealing AISTATS 2014
Fast Distribution To Real Regression AISTATS 2014
To go deep or wide in learning? AISTATS 2014
LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series AISTATS 2014
Learning Bounded Tree-width Bayesian Networks using Integer Linear Programming AISTATS 2014
Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables AISTATS 2014
An inclusion optimal algorithm for chain graph structure learning AISTATS 2014
A Stepwise uncertainty reduction approach to constrained global optimization AISTATS 2014
An Analysis of Active Learning with Uniform Feature Noise AISTATS 2014
Black Box Variational Inference AISTATS 2014
Sequential crowdsourced labeling as an epsilon-greedy exploration in a Markov Decision Process AISTATS 2014
Learning Structured Models with the AUC Loss and Its Generalizations AISTATS 2014
Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations AISTATS 2014
Loopy Belief Propagation in the Presence of Determinism AISTATS 2014
Explicit Link Between Periodic Covariance Functions and State Space Models AISTATS 2014
Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch AISTATS 2014
Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression AISTATS 2014
Bayesian Multi-Scale Optimistic Optimization AISTATS 2014
Accelerating ABC methods using Gaussian processes AISTATS 2014
A New Approach to Probabilistic Programming Inference AISTATS 2014
Generating Efficient MCMC Kernels from Probabilistic Programs AISTATS 2014
Efficient Transfer Learning Method for Automatic Hyperparameter Tuning AISTATS 2014