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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)

A Comparison of Perceptually Motivated Loss Functions for Binary Mask Estimation in Speech Separation Interspeech 2017 A Contrast Function and Algorithm for Blind Separation of Audio Signals Interspeech 2017 A Core-Guided Approach to Learning Optimal Causal Graphs IJCAI 2017 Acoustic-to-Articulatory Mapping Based on Mixture of Probabilistic Canonical Correlation Analysis Interspeech 2017 A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space ACML 2017 Active Heteroscedastic Regression ICML 2017 Active Learning for Accurate Estimation of Linear Models ICML 2017 Active Learning for Top-K Rank Aggregation from Noisy Comparisons ICML 2017 Active-set Methods for Submodular Minimization Problems JMLR 2017 Adaptable Pouring: Teaching Robots Not to Spill using Fast but Approximate Fluid Simulation CoRL 2017 Adapting Topic Models using Lexical Associations with Tree Priors EMNLP 2017 Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound Condition NeurIPS 2017 Adaptive Active Hypothesis Testing under Limited Information NeurIPS 2017 Adaptive and Move Making Auxiliary Cuts for Binary Pairwise Energies CVPR 2017 Adaptive Batch Size for Safe Policy Gradients NeurIPS 2017 Adaptive Bayesian Sampling with Monte Carlo EM NeurIPS 2017 Adaptive Consensus ADMM for Distributed Optimization ICML 2017 Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP ICML 2017 Adaptive Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks IJCAI 2017 Adaptive Manifold Regularized Matrix Factorization for Data Clustering IJCAI 2017 Adaptive Multichannel Dereverberation for Automatic Speech Recognition Interspeech 2017 Adaptive Multiple-Arm Identification ICML 2017 Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation CVPR 2017 Adaptive Sampling Probabilities for Non-Smooth Optimization ICML 2017 Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression IJCAI 2017