conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Optimization

14,983 papers

Papers per year

18
112
342
1289
1646
'05
'10
'15
'20
'25

Papers

Randomized Exploration in Reinforcement Learning with General Value Function Approximation ICML 2021
Distributed Second Order Methods with Fast Rates and Compressed Communication ICML 2021
How to Learn when Data Reacts to Your Model: Performative Gradient Descent ICML 2021
Feature Clustering for Support Identification in Extreme Regions ICML 2021
Policy Gradient Bayesian Robust Optimization for Imitation Learning ICML 2021
In-Database Regression in Input Sparsity Time ICML 2021
Objective Bound Conditional Gaussian Process for Bayesian Optimization ICML 2021
Fast margin maximization via dual acceleration ICML 2021
Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ICML 2021
Bilevel Optimization: Convergence Analysis and Enhanced Design ICML 2021
Prioritized Level Replay ICML 2021
Streaming and Distributed Algorithms for Robust Column Subset Selection ICML 2021
Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits ICML 2021
Training Recurrent Neural Networks via Forward Propagation Through Time ICML 2021
Practical and Private (Deep) Learning Without Sampling or Shuffling ICML 2021
Learning from History for Byzantine Robust Optimization ICML 2021
Improved Algorithms for Agnostic Pool-based Active Classification ICML 2021
Self Normalizing Flows ICML 2021
Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets ICML 2021
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training ICML 2021
I-BERT: Integer-only BERT Quantization ICML 2021
The Lipschitz Constant of Self-Attention ICML 2021
Bias-Robust Bayesian Optimization via Dueling Bandits ICML 2021
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More ICML 2021
Kernel Stein Discrepancy Descent ICML 2021