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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)

Towards Offline Opponent Modeling with In-context Learning ICLR 2024 Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error ICML 2024 Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm JMLR 2024 Towards Pareto-Efficient RLHF: Paying Attention to a Few High-Reward Samples with Reward Dropout EMNLP 2024 Towards Poisoning Fair Representations ICLR 2024 Towards Principled Graph Transformers NeurIPS 2024 Towards Realistic Model Selection for Semi-supervised Learning ICML 2024 Towards Reliable Learning in the Wild: Generalization and Adaptation AAAI 2024 Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline NeurIPS 2024 Towards Resource-friendly, Extensible and Stable Incomplete Multi-view Clustering ICML 2024 Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology EMNLP 2024 Towards Robust Learning to Optimize with Theoretical Guarantees CVPR 2024 Towards Robust Multi-Label Learning against Dirty Label Noise IJCAI 2024 Towards Robust Out-of-Distribution Generalization Bounds via Sharpness ICLR 2024 Towards Robust Temporal Activity Localization Learning with Noisy Labels COLING 2024 Towards Safe Policy Learning under Partial Identifiability: A Causal Approach AAAI 2024 Towards Sharper Generalization Bounds for Adversarial Contrastive Learning IJCAI 2024 Towards Sharper Risk Bounds for Minimax Problems IJCAI 2024 Towards Stability and Generalization Bounds in Decentralized Minibatch Stochastic Gradient Descent AAAI 2024 Towards Text-guided 3D Scene Composition CVPR 2024 Towards the Dynamics of a DNN Learning Symbolic Interactions NeurIPS 2024 Towards the Fundamental Limits of Knowledge Transfer over Finite Domains ICLR 2024 Towards Theoretical Understandings of Self-Consuming Generative Models ICML 2024 Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms ICML 2024 Towards Tight Convex Relaxations for Contact-Rich Manipulation RSS 2024