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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)

DAG Learning on the Permutahedron ICLR 2023 Dancing in the Dark: A Benchmark towards General Low-light Video Enhancement ICCV 2023 DANI-Net: Uncalibrated Photometric Stereo by Differentiable Shadow Handling, Anisotropic Reflectance Modeling, and Neural Inverse Rendering CVPR 2023 DART: Distance Assisted Recursive Testing JMLR 2023 DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks CVPR 2023 DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity ICLR 2023 Data Augmented Flatness-aware Gradient Projection for Continual Learning ICCV 2023 Data Banzhaf: A Robust Data Valuation Framework for Machine Learning AISTATS 2023 Data Consistent Deep Rigid MRI Motion Correction MIDL 2023 Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer ICLR 2023 Data-Copying in Generative Models: A Formal Framework ICML 2023 DataDAM: Efficient Dataset Distillation with Attention Matching ICCV 2023 Data-Driven Invariant Learning for Probabilistic Programs (Extended Abstract) IJCAI 2023 Data-driven memory-dependent abstractions of dynamical systems L4DC 2023 Data-driven Optimal Filtering for Linear Systems with Unknown Noise Covariances NeurIPS 2023 Data-driven Stochastic Output-Feedback Predictive Control: Recursive Feasibility through Interpolated Initial Conditions L4DC 2023 Data-Driven Subgroup Identification for Linear Regression ICML 2023 Data Feedback Loops: Model-driven Amplification of Dataset Biases ICML 2023 Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity ICLR 2023 Data Level Lottery Ticket Hypothesis for Vision Transformers IJCAI 2023 Data Market Design through Deep Learning NeurIPS 2023 Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value ICML 2023 DataPerf: Benchmarks for Data-Centric AI Development NeurIPS 2023 Data Representations’ Study of Latent Image Manifolds ICML 2023 Data Sampling and (In)stability in Machine Translation Evaluation ACL 2023