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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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'25

Papers (including subtopics)

LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models ACL 2025 LongRoPE2: Near-Lossless LLM Context Window Scaling ICML 2025 Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning IJCAI 2025 LongVILA: Scaling Long-Context Visual Language Models for Long Videos ICLR 2025 Lookahead Q-Cache: Achieving More Consistent KV Cache Eviction via Pseudo Query EMNLP 2025 Looped ReLU MLPs May Be All You Need as Practical Programmable Computers AISTATS 2025 LoRaDA: Low-Rank Direct Attention Adaptation for Efficient LLM Fine-tuning EMNLP 2025 LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization ICLR 2025 LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation COLING 2025 LoRA-MGPO: Mitigating Double Descent in Low-Rank Adaptation via Momentum-Guided Perturbation Optimization EMNLP 2025 LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently ICML 2025 LoRA-Pro: Are Low-Rank Adapters Properly Optimized? ICLR 2025 LoRA Training Provably Converges to a Low-Rank Global Minimum Or It Fails Loudly (But it Probably Won’t Fail) ICML 2025 LoSiA: Efficient High-Rank Fine-Tuning via Subnet Localization and Optimization EMNLP 2025 Losing Momentum in Continuous-time Stochastic Optimisation JMLR 2025 Loss Functions and Operators Generated by f-Divergences ICML 2025 Loss Functions for Predictor-based Neural Architecture Search ICCV 2025 Loss Gradient Gaussian Width based Generalization and Optimization Guarantees AISTATS 2025 Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding ICLR 2025 Lossless Acceleration of Large Language Models with Hierarchical Drafting based on Temporal Locality in Speculative Decoding NAACL 2025 LoTUS: Large-Scale Machine Unlearning with a Taste of Uncertainty CVPR 2025 Low coordinate degree algorithms II: Categorical signals and generalized stochastic block models COLT 2025 Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions COLT 2025 Low-Dimension-to-High-Dimension Generalization and Its Implications for Length Generalization ICML 2025 Low End-to-End Latency atop a Speculative Shared Log with Fix-Ante Ordering OSDI 2025