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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)

Learning Efficient Anomaly Detectors from K-NN Graphs AISTATS 2015
Gamma Processes, Stick-Breaking, and Variational Inference AISTATS 2015
Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation AISTATS 2015
Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields AISTATS 2015
Sensor Selection for Crowdsensing Dynamical Systems AISTATS 2015
Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence AISTATS 2015
Exploiting Symmetries to Construct Efficient MCMC Algorithms With an Application to SLAM AISTATS 2015
State Space Methods for Efficient Inference in Student-t Process Regression AISTATS 2015
Learning from Data with Heterogeneous Noise using SGD AISTATS 2015
Data modeling with the elliptical gamma distribution AISTATS 2015
WASP: Scalable Bayes via barycenters of subset posteriors AISTATS 2015
Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields AISTATS 2015
A Dirichlet Process Mixture Model for Spherical Data AISTATS 2015
Inferring Block Structure of Graphical Models in Exponential Families AISTATS 2015
Two-stage sampled learning theory on distributions AISTATS 2015
Predicting Preference Reversals via Gaussian Process Uncertainty Aversion AISTATS 2015
Streaming Variational Inference for Bayesian Nonparametric Mixture Models AISTATS 2015
Particle Gibbs with Ancestor Sampling for Probabilistic Programs AISTATS 2015
A Greedy Homotopy Method for Regression with Nonconvex Constraints AISTATS 2015
Stochastic Block Transition Models for Dynamic Networks AISTATS 2015
Minimizing Nonconvex Non-Separable Functions AISTATS 2015
Scalable Nonparametric Multiway Data Analysis AISTATS 2015
The Log-Shift Penalty for Adaptive Estimation of Multiple Gaussian Graphical Models AISTATS 2015
Open Problem: Restricted Eigenvalue Condition for Heavy Tailed Designs COLT 2015
Open Problem: The landscape of the loss surfaces of multilayer networks COLT 2015