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1. Variable Gain Design in Stochastic Iterative Learning Control
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2026, Springer Verlag, Singapore
ISBN-13: 9789819782833
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2. Variable Gain Design in Stochastic Iterative Learning Control
by Shen, Dong
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2026, Springer Verlag, Singapore
ISBN-13: 9789819782833
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3. Convexity in Newton's Method
by José Antonio Ezquerro Fernández; Miguel Ángel Hernández Verón
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2025, Springer Nature
eBook ISBN: 9783031857539
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4. Computational Methods for Transition States and Pathways in Rare Events
by Shuting Gu
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2025, Taylor & Francis
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5. Variable Gain Design in Stochastic Iterative Learning Control
by Dong Shen
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2025, Springer Nature
eBook ISBN: 9789819782802
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6. Optimal Iterative Learning Control
by Bing Chu; David H. Owens
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2025, Springer Nature
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7. Convexity in Newton's Method
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2025, Birkhauser Verlag AG
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8. New Developments of Newton-Type Iterations for Solving Nonlinear Problems
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2025, Springer International Publishing AG
ISBN-13: 9783031633638
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9. Computational Methods for Transition States and Pathways in Rare Events
by Gu, Shuting
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2025, CRC Press
ISBN-13: 9781032996479
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10. Conditional Gradient Methods: From Core Principles to AI Applications
by Braun, Gábor, and Carderera, Alejandro, and Combettes, Cyrille W.
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2025, Society for Industrial & Applied Mathematics,U.S.
ISBN-13: 9781611978551
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11. Conditional Gradient Methods
by Gábor Braun
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2025, John Wiley & Sons
ISBN-13: 9781611978551
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12. Conditional Gradient Methods: From Core Principles to AI Applications
by Braun, Gábor, and Carderera, Alejandro, and Combettes, Cyrille W.
Seller Description: New. Intended for professional and scholarly audience. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers. See More Details
2025, Society for Industrial & Applied Mathematics,U.S.
ISBN-13: 9781611978551
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