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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
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Papers (including subtopics)

Toward L_∞Recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields COLT 2023 Toward Robust Uncertainty Estimation with Random Activation Functions AAAI 2023 Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality COLT 2023 Towards Attack-tolerant Federated Learning via Critical Parameter Analysis ICCV 2023 Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism ICLR 2023 Towards Better Decision Forests: Forest Alternating Optimization CVPR 2023 Towards Better Gradient Consistency for Neural Signed Distance Functions via Level Set Alignment CVPR 2023 Towards Bridging the Performance Gaps of Joint Energy-Based Models CVPR 2023 Towards Building More Robust NER datasets: An Empirical Study on NER Dataset Bias from a Dataset Difficulty View EMNLP 2023 Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games NeurIPS 2023 Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models ICML 2023 Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations CVPR 2023 Towards Constituting Mathematical Structures for Learning to Optimize ICML 2023 Towards convergence to Nash equilibria in two-team zero-sum games ICLR 2023 Towards credible visual model interpretation with path attribution ICML 2023 Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask? NeurIPS 2023 Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression NeurIPS 2023 Towards Decision-Friendly AUC: Learning Multi-Classifier with AUCµ AAAI 2023 Towards Deep Attention in Graph Neural Networks: Problems and Remedies ICML 2023 Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function Classes ALT 2023 Towards Equivariant Optical Flow Estimation With Deep Learning WACV 2023 Towards Fair and Comprehensive Comparisons for Image-Based 3D Object Detection ICCV 2023 Towards Faithful Dialogues via Focus Learning ACL 2023 Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning NeurIPS 2023 Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior NeurIPS 2023