Skip to content
conftrace_

Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
'5
'10
'15
'20
'25

Papers (including subtopics)

Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms NeurIPS 2024 Learning in reverse causal strategic environments with ramifications on two sided markets ICLR 2024 Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds COLT 2024 Learning Intrinsic Dimension via Information Bottleneck for Explainable Aspect-based Sentiment Analysis COLING 2024 Learning invariant representations of time-homogeneous stochastic dynamical systems ICLR 2024 Learning Label Dependencies for Visual Information Extraction IJCAI 2024 Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG ICLR 2024 Learning Linear Block Error Correction Codes ICML 2024 Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity NeurIPS 2024 Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds ICML 2024 Learning Macroscopic Dynamics from Partial Microscopic Observations NeurIPS 2024 Learning model uncertainty as variance-minimizing instance weights ICLR 2024 Learning Multi-Task Sparse Representation Based on Fisher Information AAAI 2024 Learning multivariate temporal point processes via the time-change theorem AISTATS 2024 Learning Nash Equilibria in Rank-1 Games ICLR 2024 Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees NeurIPS 2024 Learning Neural Networks with Sparse Activations COLT 2024 Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random NeurIPS 2024 Learning Non-Gaussian Graphical Models via Hessian Scores and Triangular Transport JMLR 2024 Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s) ICLR 2024 Learning Optimal Contracts: How to Exploit Small Action Spaces ICLR 2024 Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls JMLR 2024 Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression NeurIPS 2024 Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series ICML 2024 Learning Pareto Set for Multi-Objective Continuous Robot Control IJCAI 2024