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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)

Decoder Tuning: Efficient Language Understanding as Decoding ACL 2023 Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction CVPR 2023 DecompX: Explaining Transformers Decisions by Propagating Token Decomposition ACL 2023 Decoupling-and-Aggregating for Image Exposure Correction CVPR 2023 Decoupling MaxLogit for Out-of-Distribution Detection CVPR 2023 DE-CROP: Data-Efficient Certified Robustness for Pretrained Classifiers WACV 2023 DEDRIFT: Robust Similarity Search under Content Drift ICCV 2023 DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization NeurIPS 2023 Deep Contract Design via Discontinuous Networks NeurIPS 2023 Deep Deterministic Uncertainty: A New Simple Baseline CVPR 2023 Deep Dive Into Gradients: Better Optimization for 3D Object Detection With Gradient-Corrected IoU Supervision CVPR 2023 Deep Equilibrium Non-Autoregressive Sequence Learning ACL 2023 Deep Equilibrium Object Detection ICCV 2023 DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement Interspeech 2023 Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimation ICCV 2023 Deep Gaussian mixture ensembles UAI 2023 Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models ICLR 2023 Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search ICML 2023 Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models AISTATS 2023 Deep Hashing-based Dynamic Stock Correlation Estimation via Normalizing Flow IJCAI 2023 Deep Hashing With Minimal-Distance-Separated Hash Centers CVPR 2023 Deep Incubation: Training Large Models by Divide-and-Conquering ICCV 2023 Deep Joint Source-Channel Coding with Iterative Source Error Correction AISTATS 2023 Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations AAAI 2023 Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization ICLR 2023