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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)

The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers NeurIPS 2021 The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks COLT 2021 The Elastic Lottery Ticket Hypothesis NeurIPS 2021 The Energy and Carbon Footprint of Training End-to-End Speech Recognizers Interspeech 2021 The Fewer the Merrier: Pruning Preferred Operators with Novelty IJCAI 2021 The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization NeurIPS 2021 The future is log-Gaussian: ResNets and their infinite-depth-and-width limit at initialization NeurIPS 2021 The Great Misalignment Problem in Human Evaluation of NLP Methods EACL 2021 The Heads Hypothesis: A Unifying Statistical Approach Towards Understanding Multi-Headed Attention in BERT AAAI 2021 The Heavy-Tail Phenomenon in SGD ICML 2021 The Heterogeneity Hypothesis: Finding Layer-Wise Differentiated Network Architectures CVPR 2021 The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning ICML 2021 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks ICML 2021 The Implicit Bias of Minima Stability: A View from Function Space NeurIPS 2021 The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective AAAI 2021 The Importance of Pessimism in Fixed-Dataset Policy Optimization ICLR 2021 The Inductive Bias of Quantum Kernels NeurIPS 2021 The inductive bias of ReLU networks on orthogonally separable data ICLR 2021 The Intrinsic Dimension of Images and Its Impact on Learning ICLR 2021 The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities COLT 2021 The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective NeurIPS 2021 The Limitations of Limited Context for Constituency Parsing ACL 2021 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets ICML 2021 The Limits of Optimal Pricing in the Dark NeurIPS 2021 The Lipschitz Constant of Self-Attention ICML 2021