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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

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Improved Regret Bounds for Tracking Experts with Memory NeurIPS 2021 Improved Regret Bounds of Bilinear Bandits using Action Space Analysis ICML 2021 Improved Regret for Zeroth-Order Stochastic Convex Bandits COLT 2021 Improved Shrinkage Prediction under a Spiked Covariance Structure JMLR 2021 Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP NeurIPS 2021 Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration AAAI 2021 Improving Adversarial Robustness via Channel-wise Activation Suppressing ICLR 2021 Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints AAAI 2021 Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss NeurIPS 2021 Improving approximate optimal transport distances using quantization UAI 2021 Improving Arabic Diacritization with Regularized Decoding and Adversarial Training ACL 2021 Improving black-box optimization in VAE latent space using decoder uncertainty NeurIPS 2021 Improving Causal Discovery By Optimal Bayesian Network Learning AAAI 2021 Improving Classifier Confidence using Lossy Label-Invariant Transformations AISTATS 2021 Improving Conditional Coverage via Orthogonal Quantile Regression NeurIPS 2021 Improving Deep Learning Interpretability by Saliency Guided Training NeurIPS 2021 Improving Dialogue State Tracking with Turn-based Loss Function and Sequential Data Augmentation EMNLP 2021 Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness AAAI 2021 Improving Factual Consistency of Abstractive Summarization via Question Answering ACL 2021 Improving Gaussian mixture latent variable model convergence with Optimal Transport ACML 2021 Improving Generalization of Batch Whitening by Convolutional Unit Optimization ICCV 2021 Improving Gradient Flow with Unrolled Highway Expectation Maximization AAAI 2021 Improving Gradient Regularization using Complex-Valued Neural Networks ICML 2021 Improving Hashing Algorithms for Similarity Search via MLE and the Control Variates Trick ACML 2021 Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding ICML 2021