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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)

On the Spectral Bias of Neural Networks ICML 2019 On the statistical rate of nonlinear recovery in generative models with heavy-tailed data ICML 2019 On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions CVPR 2019 On the Turing Completeness of Modern Neural Network Architectures ICLR 2019 On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks ICLR 2019 On the Universality of Invariant Networks ICML 2019 On the Value of Target Data in Transfer Learning NeurIPS 2019 On Tractable Computation of Expected Predictions NeurIPS 2019 On Variational Bounds of Mutual Information ICML 2019 Open Domain Event Extraction Using Neural Latent Variable Models ACL 2019 OpenMarkov, an Open-Source Tool for Probabilistic Graphical Models IJCAI 2019 Open Problem: Do Good Algorithms Necessarily Query Bad Points? COLT 2019 Open Problem: How fast can a multiclass test set be overfit? COLT 2019 Open Problem: Is Margin Sufficient for Non-Interactive Private Distributed Learning? COLT 2019 Open Problem: Monotonicity of Learning COLT 2019 Open Problem: Risk of Ruin in Multiarmed Bandits COLT 2019 Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory COLT 2019 Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards ICML 2019 Optimal Auctions through Deep Learning ICML 2019 Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness COLT 2019 Optimal Best Markovian Arm Identification with Fixed Confidence NeurIPS 2019 Optimal Collusion-Free Teaching ALT 2019 Optimal Control Via Neural Networks: A Convex Approach ICLR 2019 Optimal Convergence Rates for Convex Distributed Optimization in Networks JMLR 2019 Optimal Dynamic Auctions Are Virtual Welfare Maximizers AAAI 2019