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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)

Modeling All Response Surfaces in One for Conditional Search Spaces AAAI 2025 Modeling Complex System Dynamics with Flow Matching Across Time and Conditions ICLR 2025 Modeling Latent Non-Linear Dynamical System over Time Series AAAI 2025 Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent ICML 2025 Modeling Uncertainty in Composed Image Retrieval via Probabilistic Embeddings ACL 2025 Modelling Populations of Interaction Networks via Distance Metrics JMLR 2025 Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization ACL 2025 Model predictive control is almost optimal for restless bandits COLT 2025 Model selection for behavioral learning data and applications to contextual bandits AISTATS 2025 Models of Heavy-Tailed Mechanistic Universality ICML 2025 Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence ICML 2025 Model Uncertainty Quantification by Conformal Prediction in Continual Learning ICML 2025 ModernBERT or DeBERTaV3? Examining Architecture and Data Influence on Transformer Encoder Models Performance IJCNLP 2025 MoDification: Mixture of Depths Made Easy NAACL 2025 Modified K-means Algorithm with Local Optimality Guarantees ICML 2025 ModRWKV: Transformer Multimodality in Linear Time EMNLP 2025 Modular Duality in Deep Learning ICML 2025 MoFE: Mixture of Frozen Experts Architecture NAACL 2025 MoKA:Parameter Efficiency Fine-Tuning via Mixture of Kronecker Product Adaption COLING 2025 MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling ICLR 2025 MolRAG: Unlocking the Power of Large Language Models for Molecular Property Prediction ACL 2025 Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning ICML 2025 MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking ICML 2025 MONAS-ESNN: Multi-Objective Neural Architecture Search for Efficient Spiking Neural Networks WACV 2025 Monitoring Primitive Interactions During the Training of DNNs AAAI 2025