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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)

Residual Learning in Diffusion Models CVPR 2024 Resilience of Large Language Models for Noisy Instructions EMNLP 2024 Resiliency at Scale: Managing Google’s TPUv4 Machine Learning Supercomputer NSDI 2024 Resilient Constrained Reinforcement Learning AISTATS 2024 ResLoRA: Identity Residual Mapping in Low-Rank Adaption ACL 2024 Resolving Discrepancies in Compute-Optimal Scaling of Language Models NeurIPS 2024 Resonance RoPE: Improving Context Length Generalization of Large Language Models ACL 2024 Resource-Efficient Transformer Pruning for Finetuning of Large Models CVPR 2024 REST: Retrieval-Based Speculative Decoding NAACL 2024 ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift ICLR 2024 Rethinking 3D Convolution in ℓ_p-norm Space NeurIPS 2024 Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective ICLR 2024 Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework ICLR 2024 Rethinking Centered Kernel Alignment in Knowledge Distillation IJCAI 2024 Rethinking CNN’s Generalization to Backdoor Attack from Frequency Domain ICLR 2024 Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits ICML 2024 Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective NeurIPS 2024 Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints NeurIPS 2024 Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning JMLR 2024 Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD ICML 2024 Rethinking Evaluation Methods for Machine Unlearning EMNLP 2024 Rethinking FID: Towards a Better Evaluation Metric for Image Generation CVPR 2024 Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective ICML 2024 Rethinking Human Motion Prediction with Symplectic Integral CVPR 2024 Rethinking Imbalance in Image Super-Resolution for Efficient Inference NeurIPS 2024