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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)

Backward Filtering Forward Deciding in Linear Non-Gaussian State Space Models AISTATS 2024 BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models NeurIPS 2024 BadEdit: Backdooring Large Language Models by Model Editing ICLR 2024 Bagging is an Optimal PAC Learner (Extended Abstract) IJCAI 2024 Bagging Provides Assumption-free Stability JMLR 2024 Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance ICML 2024 Balanced Data Sampling for Language Model Training with Clustering ACL 2024 Balanced-Wav2Vec: Enhancing Stability and Robustness of Representation Learning Through Sample Reweighting Techniques Interspeech 2024 Balancing Act: Constraining Disparate Impact in Sparse Models ICLR 2024 Balancing Act: Distribution-Guided Debiasing in Diffusion Models CVPR 2024 Balancing Context Length and Mixing Times for Reinforcement Learning at Scale NeurIPS 2024 Balancing Humans and Machines: A Study on Integration Scale and Its Impact on Collaborative Performance AAAI 2024 Balancing Similarity and Complementarity for Federated Learning ICML 2024 Banded Square Root Matrix Factorization for Differentially Private Model Training NeurIPS 2024 BanditQ:Fair Bandits with Guaranteed Rewards UAI 2024 Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation ICLR 2024 Bandits with Abstention under Expert Advice NeurIPS 2024 Bandits with Concave Aggregated Reward IJCAI 2024 Bandits with Knapsacks and Predictions UAI 2024 Bandits with Preference Feedback: A Stackelberg Game Perspective NeurIPS 2024 Bandits with Ranking Feedback NeurIPS 2024 Bandits with Replenishable Knapsacks: the Best of both Worlds ICLR 2024 BAPO: Base-Anchored Preference Optimization for Overcoming Forgetting in Large Language Models Personalization EMNLP 2024 Barrier Algorithms for Constrained Non-Convex Optimization ICML 2024 B-ary Tree Push-Pull Method is Provably Efficient for Distributed Learning on Heterogeneous Data NeurIPS 2024