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Learning Theory Estimates with Observations from General Stationary Stochastic Processes.

• Authors : Hang, Hanyuan¹ ; Feng, Yunlong¹ ; Steinwart, Ingo²

• Source: Neural Computation. 2016, Vol. 28 Issue 12, p2853-2889. 37p. 2 Diagrams, 2 Charts.

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A COMPARISON OF THE STOCHASTIC PROCESSES OF STRUCTURAL AND TIME-SERIES EXCHANGE-RATE MODELS.

• Authors : Ahking, Francis W.; Miller, Stephen M.

Subjects: STOCHASTIC processes; FOREIGN exchange rates; RANDOM walks

• Source: Review of Economics & Statistics. Aug87, Vol. 69 Issue 3, p496. 7p.

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Gradual Modifications and Abrupt Replacements: Two Stochastic Lexical Ingredients of Language Evolution.

• Authors : Pasquini, Michele¹ (AUTHOR) ; Serva, Maurizio² (AUTHOR) ; Vergni, Davide¹ (AUTHOR)

• Source: Computational Linguistics. Jun2023, Vol. 49 Issue 2, p301-323. 23p.

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Robust Stability Analysis of Delayed Stochastic Neural Networks via Wirtinger-Based Integral Inequality.

• Authors : Suresh R; Department of Applied Mathematics, Sri Venkateswara College of Engineering, Sriperumbudur, India 602 117 .; Manivannan A

Subjects: Algorithms* ; Neural Networks, Computer* ; Stochastic Processes*

• Source: Neural computation [Neural Comput] 2021 Jan; Vol. 33 (1), pp. 227-243. Date of Electronic Publication: 2020 Nov 30.Publisher: MIT Press Country of Publication: United States NLM ID: 9426182 Publication Model: Print-Electronic Cited Medium:

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A Simple Model for Low Variability in Neural Spike Trains.

• Authors : Ferrari, Ulisse¹ ; Deny, Stéphane² ; Marre, Olivier¹

• Source: Neural Computation. Nov2018, Vol. 30 Issue 11, p3009-3036. 28p. 8 Graphs.

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Morphological Computation and Morphological Control: Steps Toward a Formal Theory and Applications.

• Authors : Füchslin, Rudolf M.¹ ; Dzyakanchuk, Andrej² ; Flumini, Dandolo¹

• Source: Artificial Life. Winter2013, Vol. 19 Issue 1, p9-34. 26p. 4 Color Photographs, 1 Black and White Photograph, 1 Diagram, 2 Charts, 1 Graph.

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Making the Error-Controlling Algorithm of Observable Operator Models Constructive.

• Authors : Ming-Jie Zhao^1,2 ; Jaeger, Herbert ; Thon, Michael¹

• Source: Neural Computation. Dec2009, Vol. 21 Issue 12, p3460-3486. 27p. 6 Graphs.

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From Pavlov Conditioning to Hebb Learning.

• Authors : Agliari, Elena^1,2 (AUTHOR) ; Aquaro, Miriam^1,2 (AUTHOR) ; Barra, Adriano^2,3 (AUTHOR)

• Source: Neural Computation. May2023, Vol. 35 Issue 5, p930-957. 28p. 3 Charts, 8 Graphs.

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EMPIRICAL BAYES METHODS FOR DYNAMIC FACTOR MODELS.

• Authors : Koopman, S. J.^1,2; Mesters, G.³

Subjects: *STOCHASTIC processes; *ESTIMATION theory; *MONTE Carlo method

• Source: Review of Economics & Statistics. Jul2017, Vol. 99 Issue 3, p486-498. 13p. 4 Charts, 1 Graph.

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Understanding Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning.

• Authors : Nguyen A; University of Wyoming .; Yosinski J

Subjects: Automation* ; Creativity* ; Learning*

• Source: Evolutionary computation [Evol Comput] 2016 Fall; Vol. 24 (3), pp. 545-72. Date of Electronic Publication: 2016 Jul 01.Publisher: MIT Press Country of Publication: United States NLM ID: 9513581 Publication Model: Print-Electronic Cited Medium:

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