Foundations and Trends in Machine Learning

37.2(top 0.1%)

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67(top 100%)

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31.7K(top 10%)

citations

40(top 20%)

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38.0(top 1%)

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all documents

33.2K

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64(top 20%)

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Top Articles

#	Title	Journal	Year	Citations
1	Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers	Foundations and Trends in Machine Learning	2010	12,393
2	Learning Deep Architectures for AI	Foundations and Trends in Machine Learning	2009	5,667
3	Advances and Open Problems in Federated Learning	Foundations and Trends in Machine Learning	2021	1,594
4	Graphical Models, Exponential Families, and Variational Inference	Foundations and Trends in Machine Learning	2007	1,233
5	An Introduction to Variational Autoencoders	Foundations and Trends in Machine Learning	2019	1,083
6	Computational Optimal Transport: With Applications to Data Science	Foundations and Trends in Machine Learning	2019	1,054
7	Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems	Foundations and Trends in Machine Learning	2012	952
8	Online Learning and Online Convex Optimization	Foundations and Trends in Machine Learning	2011	892
9	Convex Optimization: Algorithms and Complexity	Foundations and Trends in Machine Learning	2015	674
10	An Introduction to Deep Reinforcement Learning	Foundations and Trends in Machine Learning	2018	644
11	An Introduction to Conditional Random Fields	Foundations and Trends in Machine Learning	2012	549
12	Metric Learning: A Survey	Foundations and Trends in Machine Learning	2013	530
13	Optimization with Sparsity-Inducing Penalties	Foundations and Trends in Machine Learning	2011	525
14	Adaptation, Learning, and Optimization over Networks	Foundations and Trends in Machine Learning	2014	511
15	A Survey of Statistical Network Models	Foundations and Trends in Machine Learning	2009	497
16	Kernels for Vector-Valued Functions: A Review	Foundations and Trends in Machine Learning	2012	379
17	Determinantal Point Processes for Machine Learning	Foundations and Trends in Machine Learning	2012	306
18	An Introduction to Matrix Concentration Inequalities	Foundations and Trends in Machine Learning	2015	303
19	A Tutorial on Thompson Sampling	Foundations and Trends in Machine Learning	2018	297
20	Introduction to Multi-Armed Bandits	Foundations and Trends in Machine Learning	2019	279
21	Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions	Foundations and Trends in Machine Learning	2016	276
22	Non-convex Optimization for Machine Learning	Foundations and Trends in Machine Learning	2017	230
23	Kernel Mean Embedding of Distributions: A Review and Beyond	Foundations and Trends in Machine Learning	2017	193
24	Dimension Reduction: A Guided Tour	Foundations and Trends in Machine Learning	2009	181
25	Generalized Low Rank Models	Foundations and Trends in Machine Learning	2016	177
26	Convex Optimization: Algorithms and Complexity	Foundations and Trends in Machine Learning	2015	152
27	Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 2 Applications and Future Perspectives	Foundations and Trends in Machine Learning	2017	137
28	Model-based Reinforcement Learning: A Survey	Foundations and Trends in Machine Learning	2023	137
29	Learning with Submodular Functions: A Convex Optimization Perspective	Foundations and Trends in Machine Learning	2013	136
30	From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning	Foundations and Trends in Machine Learning	2014	124
31	Randomized Algorithms for Matrices and Data	Foundations and Trends in Machine Learning	2010	96
32	Backward Simulation Methods for Monte Carlo Statistical Inference	Foundations and Trends in Machine Learning	2013	89
33	Property Testing: A Learning Theory Perspective	Foundations and Trends in Machine Learning	2007	84
34	A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning	Foundations and Trends in Machine Learning	2013	75
35	A Survey of Statistical Network Models	Foundations and Trends in Machine Learning	2009	73
36	Graph Neural Networks for Natural Language Processing: A Survey	Foundations and Trends in Machine Learning	2023	73
37	Theory of Disagreement-Based Active Learning	Foundations and Trends in Machine Learning	2014	71
38	Explaining the Success of Nearest Neighbor Methods in Prediction	Foundations and Trends in Machine Learning	2018	71
39	Dynamical Variational Autoencoders: A Comprehensive Review	Foundations and Trends in Machine Learning	2021	59
40	Spectral Methods for Data Science: A Statistical Perspective	Foundations and Trends in Machine Learning	2021	45
41	Data Analytics on Graphs Part III: Machine Learning on Graphs, from Graph Topology to Applications	Foundations and Trends in Machine Learning	2020	36
42	Conformal Prediction: A Gentle Introduction	Foundations and Trends in Machine Learning	2023	34
43	Graph Kernels: State-of-the-Art and Future Challenges	Foundations and Trends in Machine Learning	2020	30
44	Learning Representation and Control in Markov Decision Processes: New Frontiers	Foundations and Trends in Machine Learning	2007	29
45	Patterns of Scalable Bayesian Inference	Foundations and Trends in Machine Learning	2016	29
46	Data Analytics on Graphs Part I: Graphs and Spectra on Graphs	Foundations and Trends in Machine Learning	2020	27
47	Minimum-Distortion Embedding	Foundations and Trends in Machine Learning	2021	25
48	Data Analytics on Graphs Part II: Signals on Graphs	Foundations and Trends in Machine Learning	2020	23
49	Elements of Sequential Monte Carlo	Foundations and Trends in Machine Learning	2019	21
50	A Unifying Tutorial on Approximate Message Passing	Foundations and Trends in Machine Learning	2022	20

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