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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)

Towards the evaluation of automatic simultaneous speech translation from a communicative perspective ACL 2021 Towards Tight Bounds on the Sample Complexity of Average-reward MDPs ICML 2021 Towards Tight Communication Lower Bounds for Distributed Optimisation NeurIPS 2021 Towards tractable optimism in model-based reinforcement learning UAI 2021 Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration AAAI 2021 Towards Understanding Learning in Neural Networks with Linear Teachers ICML 2021 Towards understanding retrosynthesis by energy-based models NeurIPS 2021 Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms AISTATS 2021 Towards Understanding the Spectral Bias of Deep Learning IJCAI 2021 Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond NeurIPS 2021 Toward Understanding the Influence of Individual Clients in Federated Learning AAAI 2021 Track, Check, Repeat: An EM Approach to Unsupervised Tracking CVPR 2021 Tracking Disease Outbreaks from Sparse Data with Bayesian Inference AAAI 2021 Tracking Regret Bounds for Online Submodular Optimization AISTATS 2021 Tractable Approximate Gaussian Inference for Bayesian Neural Networks JMLR 2021 Tractable computation of expected kernels UAI 2021 Tractable contextual bandits beyond realizability AISTATS 2021 Tractable Regularization of Probabilistic Circuits NeurIPS 2021 Tractable structured natural-gradient descent using local parameterizations ICML 2021 Tradeoffs in Data Augmentation: An Empirical Study ICLR 2021 Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling ICML 2021 Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds NeurIPS 2021 Training deep residual networks for uniform approximation guarantees L4DC 2021 Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State NeurIPS 2021 Training Generative Adversarial Networks in One Stage CVPR 2021