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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
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2000
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Papers (including subtopics)

Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models NeurIPS 2024 Retraining-Free Model Quantization via One-Shot Weight-Coupling Learning CVPR 2024 Retrieval-Augmented Score Distillation for Text-to-3D Generation ICML 2024 Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization ICLR 2024 Revealing Confounding Biases: A Novel Benchmarking Approach for Aggregate-Level Performance Metrics in Health Assessments Interspeech 2024 Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data NeurIPS 2024 Revealing the Parametric Knowledge of Language Models: A Unified Framework for Attribution Methods ACL 2024 Revealing the Proximate Long-Tail Distribution in Compositional Zero-Shot Learning AAAI 2024 Reverie: Low Pass Filter-Based Switch Buffer Sharing for Datacenters with RDMA and TCP Traffic NSDI 2024 Reverse Diffusion Monte Carlo ICLR 2024 Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference NeurIPS 2024 Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference NeurIPS 2024 Revisiting Adversarial Patches for Designing Camera-Agnostic Attacks against Person Detection NeurIPS 2024 Revisiting Adversarial Training at Scale CVPR 2024 Revisiting Catastrophic Forgetting in Large Language Model Tuning EMNLP 2024 Revisiting Causal Discovery from a Complexity-Theoretic Perspective IJCAI 2024 Revisiting Convergence of AdaGrad with Relaxed Assumptions UAI 2024 Revisiting Differentially Private ReLU Regression NeurIPS 2024 Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks AAAI 2024 Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity ICML 2024 Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning NeurIPS 2024 Revisiting OPRO: The Limitations of Small-Scale LLMs as Optimizers ACL 2024 Revisiting Parallel Context Windows: A Frustratingly Simple Alternative and Chain-of-Thought Deterioration ACL 2024 Revisiting RIP Guarantees for Sketching Operators on Mixture Models JMLR 2024 Revisiting Sampson Approximations for Geometric Estimation Problems CVPR 2024