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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)

Incremental Neural Coreference Resolution in Constant Memory EMNLP 2020 Incremental Sampling Without Replacement for Sequence Models ICML 2020 In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating Predictors ICML 2020 Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach AAAI 2020 Indirect Stochastic Gradient Quantization and Its Application in Distributed Deep Learning AAAI 2020 Individual Calibration with Randomized Forecasting ICML 2020 Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters ICML 2020 Inefficiency of K-FAC for Large Batch Size Training AAAI 2020 Inexact Tensor Methods with Dynamic Accuracies ICML 2020 Inference for Batched Bandits NeurIPS 2020 Inference Strategies for Machine Translation with Conditional Masking EMNLP 2020 Inferring Continuous Treatment Doses from Historical Data via Model-Based Entropy-Regularized Reinforcement Learning ACML 2020 Inferring learning rules from animal decision-making NeurIPS 2020 Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach WACV 2020 Infinite attention: NNGP and NTK for deep attention networks ICML 2020 Infinite-Horizon Differentiable Model Predictive Control ICLR 2020 Infinite-horizon Off-Policy Policy Evaluation with Multiple Behavior Policies ICLR 2020 Infinitely deep neural networks as diffusion processes AISTATS 2020 Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations AAAI 2020 Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020 Influenza Forecasting Framework based on Gaussian Processes ICML 2020 Information Directed Sampling for Linear Partial Monitoring COLT 2020 Information-Driven Direct RGB-D Odometry CVPR 2020 Information Elicitation Mechanisms for Statistical Estimation AAAI 2020 Information Geometry of Orthogonal Initializations and Training ICLR 2020