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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)

Joint Bayesian Modelling of Internal Dependencies and Relevant Multimorbidities of a Heterogeneous Disease PGM 2016 Joint Enhancement and Coding of Speech by Incorporating Wiener Filtering in a CELP Codec Interspeech 2016 Joint Learning of Single-Image and Cross-Image Representations for Person Re-Identification CVPR 2016 Jointly Optimizing Activation Coefficients of Convolutive NMF Using DNN for Speech Separation Interspeech 2016 Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization NeurIPS 2016 K2-ABC: Approximate Bayesian Computation with Kernel Embeddings AISTATS 2016 Kernel Estimation and Model Combination in A Bandit Problem with Covariates JMLR 2016 K-Means Clustering with Distributed Dimensions ICML 2016 Kronecker Determinantal Point Processes NeurIPS 2016 k-variates++: more pluses in the k-means++ ICML 2016 L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs JMLR 2016 L1-regularized Neural Networks are Improperly Learnable in Polynomial Time ICML 2016 L2 Acquisition and Production of the English Rhotic Pharyngeal Gesture Interspeech 2016 Ladder Variational Autoencoders NeurIPS 2016 Large-Margin Softmax Loss for Convolutional Neural Networks ICML 2016 Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation AISTATS 2016 Large-Scale Semantic 3D Reconstruction: An Adaptive Multi-Resolution Model for Multi-Class Volumetric Labeling CVPR 2016 Latent Point Process Allocation AISTATS 2016 Latent Space Inference of Internet-Scale Networks JMLR 2016 Latent Variable Graphical Model Selection Using Harmonic Analysis: Applications to the Human Connectome Project (HCP) CVPR 2016 Launch and Iterate: Reducing Prediction Churn NeurIPS 2016 Learnability of Non-I.I.D. ACML 2016 Learning Activity Progression in LSTMs for Activity Detection and Early Detection CVPR 2016 Learning Additive Exponential Family Graphical Models via ℓ_2,1-norm Regularized M-Estimation NeurIPS 2016 Learning and Forecasting Opinion Dynamics in Social Networks NeurIPS 2016