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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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828
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2000
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Papers (including subtopics)

Information is Power: Intrinsic Control via Information Capture NeurIPS 2021 Information Laundering for Model Privacy ICLR 2021 Information-theoretic generalization bounds for black-box learning algorithms NeurIPS 2021 Information-Theoretic Generalization Bounds for Stochastic Gradient Descent COLT 2021 Information theoretic meta learning with Gaussian processes UAI 2021 Information-Theoretic Methods in Deep Neural Networks: Recent Advances and Emerging Opportunities IJCAI 2021 Information-Theoretic Regularization for Multi-Source Domain Adaptation ICCV 2021 Informed Sampling for Diversity in Concept-to-Text NLG EMNLP 2021 Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting AAAI 2021 InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training NAACL 2021 Initialization and Regularization of Factorized Neural Layers ICLR 2021 Insights on Neural Representations for End-to-End Speech Recognition Interspeech 2021 Instance-adaptive training with noise-robust losses against noisy labels EMNLP 2021 Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates NeurIPS 2021 Instance-dependent Label-noise Learning under a Structural Causal Model NeurIPS 2021 Instance-Optimal Compressed Sensing via Posterior Sampling ICML 2021 Instance-optimal Mean Estimation Under Differential Privacy NeurIPS 2021 Instance Specific Approximations for Submodular Maximization ICML 2021 Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits AISTATS 2021 Integer-Arithmetic-Only Certified Robustness for Quantized Neural Networks ICCV 2021 Integer programming-based error-correcting output code design for robust classification UAI 2021 Integer Programming for Causal Structure Learning in the Presence of Latent Variables ICML 2021 Integrated Directional Gradients: Feature Interaction Attribution for Neural NLP Models ACL 2021 Integrated Latent Heterogeneity and Invariance Learning in Kernel Space NeurIPS 2021 Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints JMLR 2021