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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)

SpaCE: The Spatial Confounding Environment ICLR 2024 Space-Time Continuous PDE Forecasting using Equivariant Neural Fields NeurIPS 2024 Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs NeurIPS 2024 Spanning Training Progress: Temporal Dual-Depth Scoring (TDDS) for Enhanced Dataset Pruning CVPR 2024 SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization NeurIPS 2024 Sparse Bayesian Deep Learning for Cross Domain Medical Image Reconstruction AAAI 2024 Sparse Bayesian Generative Modeling for Compressive Sensing NeurIPS 2024 Sparse Dimensionality Reduction Revisited ICML 2024 SparseFlow: Accelerating Transformers by Sparsifying Information Flows ACL 2024 SparseGrad: A Selective Method for Efficient Fine-tuning of MLP Layers EMNLP 2024 Sparse High Rank Adapters NeurIPS 2024 Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference ICML 2024 Sparse is Enough in Fine-tuning Pre-trained Large Language Models ICML 2024 SparseLLM: Towards Global Pruning of Pre-trained Language Models NeurIPS 2024 Sparse Logistic Regression with High-order Features for Automatic Grammar Rule Extraction from Treebanks COLING 2024 Sparse maximal update parameterization: A holistic approach to sparse training dynamics NeurIPS 2024 Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging ICLR 2024 Sparse NMF with Archetypal Regularization: Computational and Robustness Properties JMLR 2024 SparseOcc: Rethinking Sparse Latent Representation for Vision-Based Semantic Occupancy Prediction CVPR 2024 Sparser, Better, Deeper, Stronger: Improving Static Sparse Training with Exact Orthogonal Initialization ICML 2024 Sparse Recovery With Multiple Data Streams: An Adaptive Sequential Testing Approach JMLR 2024 Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces JMLR 2024 Sparsest Models Elude Pruning: An Exposé of Pruning’s Current Capabilities ICML 2024 Sparse-to-dense Multimodal Image Registration via Multi-Task Learning ICML 2024 Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning ICLR 2024