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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)

Improving generalization by controlling label-noise information in neural network weights ICML 2020 Improving Joint Training of Inference Networks and Structured Prediction Energy Networks EMNLP 2020 Improving Lives of Indebted Farmers Using Deep Learning: Predicting Agricultural Produce Prices Using Convolutional Neural Networks AAAI 2020 Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation AISTATS 2020 Improving model calibration with accuracy versus uncertainty optimization NeurIPS 2020 Improving Neural Network Training in Low Dimensional Random Bases NeurIPS 2020 Improving Policy-Constrained Kidney Exchange via Pre-Screening NeurIPS 2020 Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms NeurIPS 2020 Improving Text Generation with Student-Forcing Optimal Transport EMNLP 2020 Improving the Gating Mechanism of Recurrent Neural Networks ICML 2020 Improving the Robustness of Capsule Networks to Image Affine Transformations CVPR 2020 Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning AAAI 2020 Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking ICML 2020 Improving Transformer Models by Reordering their Sublayers ACL 2020 Improving Transformer Optimization Through Better Initialization ICML 2020 Imputation estimators for unnormalized models with missing data AISTATS 2020 Imputer: Sequence Modelling via Imputation and Dynamic Programming ICML 2020 Imputing typological values via phylogenetic inference EMNLP 2020 IMS at SemEval-2020 Task 1: How Low Can You Go? Dimensionality in Lexical Semantic Change Detection SemEval 2020 Incentivized Exploration for Multi-Armed Bandits under Reward Drift AAAI 2020 Inconsistency Measurement for Improving Logical Formula Clustering IJCAI 2020 Incorporating Interpretable Output Constraints in Bayesian Neural Networks NeurIPS 2020 Incorporating Noisy Length Constraints into Transformer with Length-aware Positional Encodings COLING 2020 Increasing Learning Efficiency of Self-Attention Networks through Direct Position Interactions, Learnable Temperature, and Convoluted Attention COLING 2020 Incremental learning of EMG-based control commands using Gaussian Processes CoRL 2020