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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Provably Scalable Black-Box Variational Inference with Structured Variational Families ICML 2024 Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning NeurIPS 2024 Proving Linear Mode Connectivity of Neural Networks via Optimal Transport AISTATS 2024 Proving Test Set Contamination in Black-Box Language Models ICLR 2024 Pruning Foundation Models for High Accuracy without Retraining EMNLP 2024 Pruning From Scratch via Shared Pruning Module and Nuclear Norm-Based Regularization WACV 2024 Pruning is Optimal for Learning Sparse Features in High-Dimensions COLT 2024 Pruning neural network models for gene regulatory dynamics using data and domain knowledge NeurIPS 2024 PSC: Extending Context Window of Large Language Models via Phase Shift Calibration EMNLP 2024 PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation NeurIPS 2024 P-TA: Using Proximal Policy Optimization to Enhance Tabular Data Augmentation via Large Language Models ACL 2024 ptwt - The PyTorch Wavelet Toolbox JMLR 2024 Public-data Assisted Private Stochastic Optimization: Power and Limitations NeurIPS 2024 PURE: Prompt Evolution with Graph ODE for Out-of-distribution Fluid Dynamics Modeling NeurIPS 2024 Pursuing Overall Welfare in Federated Learning through Sequential Decision Making ICML 2024 Pursuit of the Cluster Structure of Network Lasso: Recovery Condition and Non-convex Extension JMLR 2024 Pushing Boundaries: Mixup's Influence on Neural Collapse ICLR 2024 Putting Gale & Shapley to Work: Guaranteeing Stability Through Learning NeurIPS 2024 PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference ACL 2024 PyRater: A Python Toolkit for Annotation Analysis COLING 2024 Q-conjugate Message Passing for Efficient Bayesian Inference PGM 2024 QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints L4DC 2024 QCS-SGM+: Improved Quantized Compressed Sensing with Score-Based Generative Models AAAI 2024 QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration JMLR 2024 Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model NeurIPS 2024