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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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Papers (including subtopics)

Mean-Variance Analysis in Bayesian Optimization under Uncertainty AISTATS 2021 Measure Transport with Kernel Stein Discrepancy AISTATS 2021 Measuring and Improving Faithfulness of Attention in Neural Machine Translation EACL 2021 Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation ACL 2021 Measuring Biases of Word Embeddings: What Similarity Measures and Descriptive Statistics to Use? NAACL 2021 Measuring Dependence with Matrix-based Entropy Functional AAAI 2021 Measuring Generalization with Optimal Transport NeurIPS 2021 Measuring Robustness in Deep Learning Based Compressive Sensing ICML 2021 MedAI at SemEval-2021 Task 5: Start-to-end Tagging Framework for Toxic Spans Detection SemEval 2021 Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences ICML 2021 MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain ACL 2021 Memorization vs. Generalization : Quantifying Data Leakage in NLP Performance Evaluation EACL 2021 Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients AAAI 2021 Memory-Efficient Pipeline-Parallel DNN Training ICML 2021 Memory-efficient Transformers via Top-k Attention EMNLP 2021 Memory-Gated Recurrent Networks AAAI 2021 Memory Optimization for Deep Networks ICLR 2021 MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge NeurIPS 2021 Meta-Aggregator: Learning To Aggregate for 1-Bit Graph Neural Networks ICCV 2021 Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models NeurIPS 2021 Metadata Normalization CVPR 2021 MetaGrad: Adaptation using Multiple Learning Rates in Online Learning JMLR 2021 Meta Learning Backpropagation And Improving It NeurIPS 2021 Meta-Learning Bidirectional Update Rules ICML 2021 Meta-Learning Divergences for Variational Inference AISTATS 2021