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)

Explainable Data-Driven Optimization: From Context to Decision and Back Again ICML 2023 Explaining Adversarial Robustness of Neural Networks from Clustering Effect Perspective ICCV 2023 Explaining Reinforcement Learning with Shapley Values ICML 2023 Explaining the effects of non-convergent MCMC in the training of Energy-Based Models ICML 2023 Explanation Selection Using Unlabeled Data for Chain-of-Thought Prompting EMNLP 2023 Explicitly Minimizing the Blur Error of Variational Autoencoders ICLR 2023 Explicit Regularization in Overparametrized Models via Noise Injection AISTATS 2023 Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models NeurIPS 2023 Exploiting Correlated Auxiliary Feedback in Parameterized Bandits NeurIPS 2023 Exploiting hidden structures in non-convex games for convergence to Nash equilibrium NeurIPS 2023 Exploiting Network Compressibility and Topology in Zero-Cost NAS AutoML 2023 Exploration for Free: How Does Reward Heterogeneity Improve Regret in Cooperative Multi-agent Bandits? UAI 2023 Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference AISTATS 2023 Exploration in Reward Machines with Low Regret AISTATS 2023 Exploration on Physics-Informed Neural Networks on Partial Differential Equations (Student Abstract) AAAI 2023 Exploration via Epistemic Value Estimation AAAI 2023 Exploring and Interacting with the Set of Good Sparse Generalized Additive Models NeurIPS 2023 Exploring Geometry of Blind Spots in Vision models NeurIPS 2023 Exploring Local Norms in Exp-concave Statistical Learning COLT 2023 Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks NeurIPS 2023 Exploring Lottery Prompts for Pre-trained Language Models ACL 2023 Exploring Model Transferability through the Lens of Potential Energy ICCV 2023 Exploring the Cognitive Knowledge Structure of Large Language Models: An Educational Diagnostic Assessment Approach EMNLP 2023 Exploring the Optimal Choice for Generative Processes in Diffusion Models: Ordinary vs Stochastic Differential Equations NeurIPS 2023 Exploring the Relationship between Alignment and Cross-lingual Transfer in Multilingual Transformers ACL 2023