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A unifying tutorial on approximate message passing

A unifying tutorial on approximate message passing
Paper図書
Oliver Y. Feng ... [et al.]now Publishersc2022
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Computational optimal transport : with applications to data sciences : pbk

Computational optimal transport : with applications to data sciences : pbk
Paper図書
Gabriel Peyré, Marco Cuturinow Publishersc2019
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An introduction to deep reinforcement learning : pbk

An introduction to deep reinforcement learning : pbk
Paper図書
Vincent François-Lavet ... [et al.]now Publishersc2018
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An introduction to Wishart matrix moments : pbk

An introduction to Wishart matrix moments : pbk
Paper図書
Adrian N. Bishop, Pierre del Moral, Angèle Niclasnow Publishersc2018
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Low-rank tensor decompositions

Low-rank tensor decompositions
Paper図書
Andrzej Cichocki ... [et al.]now Publishers2017
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Non-convex optimization for machine learning

Non-convex optimization for machine learning
Paper図書
Prateek Jain, Purushottam Karnow Publishersc2017
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Applications and future perspectives

Applications and future perspectives
Paper図書
Andrzej Cichocki ... [et al.]now Publishersc2017
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Bayesian Reinforcement Learning: A Survey

Bayesian Reinforcement Learning: A Survey
Paper図書
Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamarnow Publishersc2015
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An introduction to matrix concentration inequalities

An introduction to matrix concentration inequalities
Paper図書
Joel A. Troppnow Publishersc2015
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From bandits to monte-carlo tree search : the optimistic principle applied to optimization and planning

From bandits to monte-carlo tree search : the optimistic principle applied to optimization and planning
Paper図書
Rèmi Munosnow Publishersc2014
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Convex optimization : algorithms and complexity

Convex optimization : algorithms and complexity
Paper図書
Sébastien Bubecknow Publishersc2015
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Learning with submodular functions : a convex optimization perspective

Learning with submodular functions : a convex optimization perspective
Paper図書
Francis Bachnow Publishersc2013
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Determinantal point processes for machine learning

Determinantal point processes for machine learning
Paper図書
Alex Kulesza, Ben Taskarnow Publishersc2012
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A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning

A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning
Paper図書
Alborz Geramifard, Thomas J. Walsh, Stefanie Tellex, Girish Chowdhary, Nicholas Roy, Jonathan P. Hownow Publishersc2013
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Regret analysis of stochastic and nonstochastic multi-armed bandit problems

Regret analysis of stochastic and nonstochastic multi-armed bandit problems
Paper図書
Sébastien Bubeck, Nicolò Cesa-Bianchinow Publishersc2012
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Kernels for vector-valued functions : a review

Kernels for vector-valued functions : a review
Paper図書
Mauricio A. Álvarez, Lorenzo Rosasco, Neil D. Lawrencenow Publishersc2012
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Learning deep architectures for AI

Learning deep architectures for AI
Paper図書
Yoshua Bengionow Publishersc2009
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Distributed optimization and statistical learning via the alternating direction method of multipliers : pbk

Distributed optimization and statistical learning via the alternating direction method of multipliers : pbk
Paper図書
Stephen Boyd ... [et al.]Nowc2011
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A survey of statistical network models

A survey of statistical network models
Paper図書
Anna Goldenberg, Alice X. Zheng, Stephen E. Fienberg, and Edoardo M. Airoldinow Publishers[2009]
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Graphical models, exponential families, and variational inference

Graphical models, exponential families, and variational inference
Paper図書
Martin J. Wainwright, Michael I. Jordannow Publishersc2008
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