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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)

Distributional Reinforcement Learning for Multi-Dimensional Reward Functions NeurIPS 2021 Distributional Reinforcement Learning via Moment Matching AAAI 2021 Distributional Robustness Loss for Long-Tail Learning ICCV 2021 Distributional Sliced-Wasserstein and Applications to Generative Modeling ICLR 2021 Distribution-Aware Adaptive Multi-Bit Quantization CVPR 2021 Distribution-Free Calibration Guarantees for Histogram Binning without Sample Splitting ICML 2021 Distribution-free inference for regression: discrete, continuous, and in between NeurIPS 2021 Distribution-free uncertainty quantification for classification under label shift UAI 2021 DivAug: Plug-In Automated Data Augmentation With Explicit Diversity Maximization ICCV 2021 Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals NeurIPS 2021 Diverse Message Passing for Attribute with Heterophily NeurIPS 2021 Diverse Video Generation using a Gaussian Process Trigger ICLR 2021 Diversifying Dialog Generation via Adaptive Label Smoothing ACL 2021 Diversifying Sample Generation for Accurate Data-Free Quantization CVPR 2021 Diversity Enhanced Active Learning with Strictly Proper Scoring Rules NeurIPS 2021 DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel NeurIPS 2021 Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling AAAI 2021 Document-Level Relation Extraction with Reconstruction AAAI 2021 Does Invariant Risk Minimization Capture Invariance? AISTATS 2021 Does Preprocessing Help Training Over-parameterized Neural Networks? NeurIPS 2021 Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learning EACL 2021 Do Image Classifiers Generalize Across Time? ICCV 2021 Do Input Gradients Highlight Discriminative Features? NeurIPS 2021 Domain Divergences: A Survey and Empirical Analysis NAACL 2021 Domain Generalization by Marginal Transfer Learning JMLR 2021