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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)

Soft-constrained Schrödinger Bridge: a Stochastic Control Approach AISTATS 2024 Soft convex quantization: revisiting Vector Quantization with convex optimization L4DC 2024 SoftDedup: an Efficient Data Reweighting Method for Speeding Up Language Model Pre-training ACL 2024 Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement CVPR 2024 Soft-Label Integration for Robust Toxicity Classification NeurIPS 2024 Soft metrics for evaluation with disagreements: an assessment COLING 2024 Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models ICLR 2024 Soft Shadow Diffusion (SSD): Physics-inspired Learning for 3D Computational Periscopy ECCV 2024 SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling NAACL 2024 Solving Attention Kernel Regression Problem via Pre-conditioner AISTATS 2024 Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns? EMNLP 2024 Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint AISTATS 2024 Solving Inverse Problems via Diffusion Optimal Control NeurIPS 2024 Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency ICLR 2024 Solving Non-rectangular Reward-Robust MDPs via Frequency Regularization AAAI 2024 Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration with Provable Guarantees AAAI 2024 Solving Sparse \& High-Dimensional-Output Regression via Compression NeurIPS 2024 Solving Spectrum Unmixing as a Multi-Task Bayesian Inverse Problem with Latent Factors for Endmember Variability AAAI 2024 Some Constructions of Private, Efficient, and Optimal K-Norm and Elliptic Gaussian Noise COLT 2024 Some Fundamental Aspects about Lipschitz Continuity of Neural Networks ICLR 2024 Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training ICLR 2024 SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning EMNLP 2024 Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation NeurIPS 2024 SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity ICML 2024 Space and time continuous physics simulation from partial observations ICLR 2024