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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
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828
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2000
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Papers (including subtopics)

When Do GNNs Work: Understanding and Improving Neighborhood Aggregation IJCAI 2020 When Do Neural Networks Outperform Kernel Methods? NeurIPS 2020 When to Use Convolutional Neural Networks for Inverse Problems CVPR 2020 Why and when should you pool? Analyzing Pooling in Recurrent Architectures EMNLP 2020 Why are Adaptive Methods Good for Attention Models? NeurIPS 2020 Why Are Learned Indexes So Effective? ICML 2020 Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER AAAI 2020 Why bigger is not always better: on finite and infinite neural networks ICML 2020 Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? --- A Neural Tangent Kernel Perspective NeurIPS 2020 Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity ICLR 2020 Why Having 10,000 Parameters in Your Camera Model Is Better Than Twelve CVPR 2020 Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout AISTATS 2020 Wide Hidden Expansion Layer for Deep Convolutional Neural Networks WACV 2020 Wide Neural Networks with Bottlenecks are Deep Gaussian Processes JMLR 2020 Winnowing with Gradient Descent COLT 2020 Wisdom of the Ensemble: Improving Consistency of Deep Learning Models NeurIPS 2020 With Little Power Comes Great Responsibility EMNLP 2020 WONDER: Weighted One-shot Distributed Ridge Regression in High Dimensions JMLR 2020 Woodbury Transformations for Deep Generative Flows NeurIPS 2020 WoodFisher: Efficient Second-Order Approximation for Neural Network Compression NeurIPS 2020 Word-level Textual Adversarial Attacking as Combinatorial Optimization ACL 2020 Word Representations Concentrate and This is Good News! CoNLL 2020 Word Rotator’s Distance EMNLP 2020 Worst-Case Analysis for Randomly Collected Data NeurIPS 2020 Would you describe a leopard as yellow? Evaluating crowd-annotations with justified and informative disagreement COLING 2020