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)

Sequential Patient Recruitment and Allocation for Adaptive Clinical Trials AISTATS 2019
Probabilistic Forecasting with Spline Quantile Function RNNs AISTATS 2019
Exponential Weights on the Hypercube in Polynomial Time AISTATS 2019
Sharp Analysis of Learning with Discrete Losses AISTATS 2019
Designing Optimal Binary Rating Systems AISTATS 2019
Stochastic Negative Mining for Learning with Large Output Spaces AISTATS 2019
Learning One-hidden-layer Neural Networks under General Input Distributions AISTATS 2019
A Geometric Perspective on the Transferability of Adversarial Directions AISTATS 2019
Non-linear process convolutions for multi-output Gaussian processes AISTATS 2019
Bridging the gap between regret minimization and best arm identification, with application to A/B tests AISTATS 2019
Gaussian Process Modulated Cox Processes under Linear Inequality Constraints AISTATS 2019
Implicit Kernel Learning AISTATS 2019
Variational Information Planning for Sequential Decision Making AISTATS 2019
Renyi Differentially Private ERM for Smooth Objectives AISTATS 2019
Projection-Free Bandit Convex Optimization AISTATS 2019
Test without Trust: Optimal Locally Private Distribution Testing AISTATS 2019
Distributed Maximization of "Submodular plus Diversity" Functions for Multi-label Feature Selection on Huge Datasets AISTATS 2019
Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach AISTATS 2019
Safe Convex Learning under Uncertain Constraints AISTATS 2019
The non-parametric bootstrap and spectral analysis in moderate and high-dimension AISTATS 2019
Training Variational Autoencoders with Buffered Stochastic Variational Inference AISTATS 2019
Regularized Contextual Bandits AISTATS 2019
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization AISTATS 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features AISTATS 2019
Distributional reinforcement learning with linear function approximation AISTATS 2019