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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)

Prompt Gradient Projection for Continual Learning ICLR 2024 Prompting a Pretrained Transformer Can Be a Universal Approximator ICML 2024 Prompting Hard or Hardly Prompting: Prompt Inversion for Text-to-Image Diffusion Models CVPR 2024 Prompt Learning with Extended Kalman Filter for Pre-trained Language Models IJCAI 2024 Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models ICLR 2024 Proper Laplacian Representation Learning ICLR 2024 Proportion-based Sensitivity Analysis of Uncontrolled Confounding Bias in Causal Inference IJCAI 2024 ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs EMNLP 2024 Prospective Learning: Learning for a Dynamic Future NeurIPS 2024 Protected Test-Time Adaptation via Online Entropy Matching: A Betting Approach NeurIPS 2024 Protein Discovery with Discrete Walk-Jump Sampling ICLR 2024 Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction ICLR 2024 Provable Accelerated Convergence of Nesterov’s Momentum for Deep ReLU Neural Networks ALT 2024 Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks NeurIPS 2024 Provable Acceleration of Nesterov’s Accelerated Gradient Method over Heavy Ball Method in Training Over-Parameterized Neural Networks IJCAI 2024 Provable Advantage in Quantum PAC Learning COLT 2024 Provable and Efficient Dataset Distillation for Kernel Ridge Regression NeurIPS 2024 Provable Benefits of Complex Parameterizations for Structured State Space Models NeurIPS 2024 Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective ICML 2024 Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes ICLR 2024 Provable Contrastive Continual Learning ICML 2024 Provable Editing of Deep Neural Networks using Parametric Linear Relaxation NeurIPS 2024 Provable local learning rule by expert aggregation for a Hawkes network AISTATS 2024 Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning ICLR 2024 Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks ICML 2024