conftrace_

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)

Gaussian Regression with Convex Constraints AISTATS 2019
Risk-Averse Stochastic Convex Bandit AISTATS 2019
Error bounds for sparse classifiers in high-dimensions AISTATS 2019
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers AISTATS 2019
Scalable Thompson Sampling via Optimal Transport AISTATS 2019
On the Interaction Effects Between Prediction and Clustering AISTATS 2019
Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds AISTATS 2019
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models AISTATS 2019
Unbiased Implicit Variational Inference AISTATS 2019
Efficient Linear Bandits through Matrix Sketching AISTATS 2019
Orthogonal Estimation of Wasserstein Distances AISTATS 2019
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity AISTATS 2019
Greedy and IHT Algorithms for Non-convex Optimization with Monotone Costs of Non-zeros AISTATS 2019
Block Stability for MAP Inference AISTATS 2019
A Stein–Papangelou Goodness-of-Fit Test for Point Processes AISTATS 2019
Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain AISTATS 2019
Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs AISTATS 2019
Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems AISTATS 2019
Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity AISTATS 2019
Accelerated Coordinate Descent with Arbitrary Sampling and Best Rates for Minibatches AISTATS 2019
Pathwise Derivatives for Multivariate Distributions AISTATS 2019
Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning AISTATS 2019
Blind Demixing via Wirtinger Flow with Random Initialization AISTATS 2019
Performance Metric Elicitation from Pairwise Classifier Comparisons AISTATS 2019
Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm AISTATS 2019