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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)

Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more ICML 2022 GENIE: Higher-Order Denoising Diffusion Solvers NeurIPS 2022 GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation ICLR 2022 Geometrically Adaptive Dictionary Attack on Face Recognition WACV 2022 Geometry-Aware Hierarchical Bayesian Learning on Manifolds WACV 2022 Geometry-Inspired Top-K Adversarial Perturbations WACV 2022 Gerrymandering under Uncertain Preferences (Student Abstract) AAAI 2022 GLaM: Efficient Scaling of Language Models with Mixture-of-Experts ICML 2022 Global Context With Discrete Diffusion in Vector Quantised Modelling for Image Generation CVPR 2022 Global Convergence and Stability of Stochastic Gradient Descent NeurIPS 2022 Global Convergence of Direct Policy Search for State-Feedback H_∞ Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential NeurIPS 2022 Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning CVPR 2022 Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression NeurIPS 2022 Globally Convergent Policy Search for Output Estimation NeurIPS 2022 Globally Gated Deep Linear Networks NeurIPS 2022 Globally Optimal Hierarchical Reinforcement Learning for Linearly-Solvable Markov Decision Processes AAAI 2022 Global Optimization Networks ICML 2022 Global Sensing and Measurements Reuse for Image Compressed Sensing CVPR 2022 Global Tracking via Ensemble of Local Trackers CVPR 2022 GlobEnc: Quantifying Global Token Attribution by Incorporating the Whole Encoder Layer in Transformers NAACL 2022 GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models NeurIPS 2022 GNN2GNN: Graph neural networks to generate neural networks UAI 2022 Going Deeper into Permutation-Sensitive Graph Neural Networks ICML 2022 Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? NeurIPS 2022 GOOD: A Graph Out-of-Distribution Benchmark NeurIPS 2022