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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)

Knowledge Graph Completion by Intermediate Variables Regularization NeurIPS 2024 KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Server EMNLP 2024 Known Knowns and Unknowns: Near-realtime Earth Observation Via Query Bifurcation in Serval NSDI 2024 Koopman-based generalization bound: New aspect for full-rank weights ICLR 2024 KPConvX: Modernizing Kernel Point Convolution with Kernel Attention CVPR 2024 KPEval: Towards Fine-Grained Semantic-Based Keyphrase Evaluation ACL 2024 Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks NeurIPS 2024 Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate AISTATS 2024 KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization NeurIPS 2024 L0-Sampler: An L0 Model Guided Volume Sampling for NeRF CVPR 2024 L2B: Learning to Bootstrap Robust Models for Combating Label Noise CVPR 2024 L2P-MIP: Learning to Presolve for Mixed Integer Programming ICLR 2024 Label Alignment Regularization for Distribution Shift JMLR 2024 Label Confidence Weighted Learning for Target-level Sentence Simplification EMNLP 2024 Label Noise: Ignorance Is Bliss NeurIPS 2024 Label Noise Robustness of Conformal Prediction JMLR 2024 Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach WACV 2024 Lagrangian inspired polynomial estimator for black-box learning and control of underactuated systems L4DC 2024 LaMDA: Large Model Fine-Tuning via Spectrally Decomposed Low-Dimensional Adaptation EMNLP 2024 Langevin Policy for Safe Reinforcement Learning ICML 2024 Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning NeurIPS 2024 Language Generation in the Limit NeurIPS 2024 Language Model Decoding as Direct Metrics Optimization ICLR 2024 Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch ICML 2024 Language Models as Black-Box Optimizers for Vision-Language Models CVPR 2024