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Entropy Optimization And Mathematical Programming
Christin Wirth
- 01 Jan 2016
33
TL;DR: The entropy optimization and mathematical programming is universally compatible with any devices to read and an online access to it is set as public so you can get it instantly.
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Abstract: entropy optimization and mathematical programming is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the entropy optimization and mathematical programming is universally compatible with any devices to read.
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Citations
Online Learning in Markov Decision Processes with Changing Cost Sequences
Travis Dick,András György,Csaba Szepesvári +2 more
- 21 Jun 2014
TL;DR: This paper considers online learning in finite Markov decision processes (MDPs) with changing cost sequences under full and bandit-information with two methods for this problem: MD2 (mirror descent with approximate projections) and the continuous exponential weights algorithm with Dikin walks.
81
Fast Primal-Dual Gradient Method for Strongly Convex Minimization Problems with Linear Constraints
Alexey Chernov,Pavel Dvurechensky,Alexander Gasnikov +2 more
- 19 Sep 2016
TL;DR: The Fast Gradient Method is extended to make it primal-dual so that it allows not only to solve the dual problem, but also to construct nearly optimal and nearly feasible solution of the primal problem.
54
Quantitative modeling of user performance in multitasking environments
Shijing Liu,Chang S. Nam +1 more
TL;DR: A framework to quantitatively evaluate multitasking systems and improve human performance in order to understand the interaction between systems and human operators is provided.
23
Inferences from a network to a subnetwork and vice versa under an assumption of symmetry
TL;DR: This note summarizes some mathematical relations between the probability distributions for the states of a network of binary units and a subnetwork thereof, under an assumption of symmetry, which are standard results of probability theory, but seem to be rarely used in neuroscience.
Optimization Models for Reaction Networks: Information Divergence, Quadratic Programming and Kirchhoff’s Laws
Julio Michael Stern,Fábio Nakano +1 more
- 05 Mar 2014
TL;DR: A simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law is presented, and the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models is compared.
12
References
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