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 Borkar, Vivek S.
 Second edition.  Singapore : Springer : Hindustan Book Agency, 2022.
 Description
 Book — 1 online resource
 Summary

 1. Introduction
 2. Convergence Analysis
 3. Finite Time Bounds and Traps
 4. Stability Criteria
 5. Stochastic Recursive Inclusions
 6. Asynchronous Schemes
 7. A Limit Theorem for Fluctuations
 8. Multiple Timescales
 9. Constant Stepsize Algorithms
 10. General Noise Models
 11. Stochastic Gradient Schemes
 12. Liapunov and Related Systems
 13. Appendix A: Topics in Analysis
 14. Appendix B: Ordinary Differential Equations
 15. Appendix C: Topics in Probability
 Bibliography
 Index. .
 Borkar, Vivek S.
 Cambridge, UK : Cambridge University Press ; New Delhi, India : Hindustan Book Agency, 2008.
 Description
 Book — ix, 164 p. ; 24 cm.
 Summary

 Preface
 1. Introduction
 2. Basic convergence analysis
 3. Stability criteria
 4. Lockin probability
 5. Stochastic recursive inclusions
 6. Multiple timescales
 7. Asynchronous schemes
 8. A limit theorem for fluctuations
 9. Constant stepsize algorithms
 10. Applications
 11. Appendices
 References
 Index.
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QA274.2 .B67 2008  Unknown 
 Chen, Hanfu.
 Dordrecht ; Boston : Kluwer Academic Publishers, c2002.
 Description
 Book — xv, 357 p. : ill. ; 25 cm.
 Summary

 Preface. Acknowledgments.
 1. RobbinsMonro Algorithm.
 2. Stochastic Approximation Algorithms with Expanding Truncations.
 3. Asymptotic Properties of Stochastic Approximation Algorithms.
 4. Optimization by Stochastic Approximation.
 5. Applications To Signal Processing.
 6. Application to Systems and Control.
 7. Appendices. References. Index.
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QA274.2 .C538 2002  Unknown 
 Kushner, Harold J. (Harold Joseph), 1933
 New York : Springer, c1997.
 Description
 Book — xxi, 417 p. : ill. ; 24 cm.
 Summary

 Applications and issues
 application to learning, state dependent noise and queueing
 applications to signal processing and adaptive control
 mathematical background
 convergence with probability one  Martingale difference noise
 convergence with probability one  correlated noise
 weak convergence  introduction
 weak convergence methods for general algorithms
 applications  proofs of convergence
 rate of convergence
 averaging of the iterates
 distributed/decentralized and asynchronous algorithms.
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QA274.2 .K88 1997  Unknown 
 Csörgö, M.
 Chichester ; New York : John Wiley & Sons, c1993.
 Description
 Book — xiii, 442 p. ; 24 cm.
 Summary

 Strong approximations of partial sums of independent identically distributed random variables
 renewal and related processes
 uniform empirical and quantile processes and their approximations
 weighted approximations of uniform empirical and quantile processes
 asymptotic distributions of functionals of weighted uniform empirical and quantile processes
 general quantile processes and their approximations.
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QA274.2 .C77 1993  Available 
 Ljung, Lennart.
 Basel ; Boston : Birkhäuser Verlag, 1992.
 Description
 Book — 113 p.
SAL3 (offcampus storage)
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QA274.2 L58 1992  Available 
7. Two essays on stochastic income theory [1985]
 Chu, Chinyi.
 Nankang, Taipei : Institute of Economics, Academia Sinica, 1985.
 Description
 Book — x, 213 p. : ill. ; 25 cm.
 Online
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HB601 .C55  Available 
 Bernstein, Andrey, author.
 Golden, CO : National Renewable Energy Laboratory, 2019
 Description
 Book — 1 online resource (8 pages) : color illustrations
 Kuhn, Daniel, 1975
 Berlin ; London : Springer, 2005.
 Description
 Book — xi, 190 p. : ill.
 Nevelson, Mikhail Borisovich.
 Providence : American Mathematical Society, 1976.
 Description
 Book — 243 p. ; 24 cm.
 Online
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QA274 .N4813  Available 
 Stokhasticheskai͡a approksimat͡sii͡a i rekurrentnoe ot͡senivanie. English
 Nevelʹson, Mikhail Borisovich.
 Providence : American Mathematical Society, 1973, c1976
 Description
 Book — 1 online resource (iv, 244 p).
 Summary

 Preface Introduction Elements of probability and martingales Discrete time Markov processes Markov processes and stochastic equations Convergence of stochastic approximation procedures. I Convergence of stochastic approximation procedures. II Asymptotic normality of the RobbinsMonro procedure Some modifications of stochastic approximation procedures Recursive estimation (discrete time) Recursive estimation (continuous time) Recursive estimation with a control parameter
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12. Stochastic approximation [1969]
 Wasan, M. T.
 London, Cambridge U.P., 1969.
 Description
 Book — x, 202 p. 23 cm.
 Summary

 Preface
 1. Introduction
 2. The RobbinsMonro method
 3. The KieferWolfowitz method
 4. Applications
 5. Multivariate stochasticapproximation methods
 6. Asymptotic normality
 7. The approximation for continuous random processes
 8. Upanddown method
 Appendices
 Bibliography
 Index.
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QA221 .W3  Available 
 Kushner, Harold J. (Harold Joseph), 1933
 2nd ed.  New York : Springer, c2003.
 Description
 Book — xxii, 474 p. : ill. ; 25 cm.
 Summary

 Introduction
 1 Review of Continuous Time Models 1.1 Martingales and Martingale Inequalities 1.2 Stochastic Integration 1.3 Stochastic Differential Equations: Diffusions 1.4 Reflected Diffusions 1.5 Processes with Jumps
 2 Controlled Markov Chains 2.1 Recursive Equations for the Cost 2.2 Optimal Stopping Problems 2.3 Discounted Cost 2.4 Control to a Target Set and Contraction Mappings 2.5 Finite Time Control Problems
 3 Dynamic Programming Equations 3.1 Functionals of Uncontrolled Processes 3.2 The Optimal Stopping Problem 3.3 Control Until a Target Set Is Reached 3.4 A Discounted Problem with a Target Set and Reflection 3.5 Average Cost Per Unit Time
 4 Markov Chain Approximation Method: Introduction 4.1 Markov Chain Approximation 4.2 Continuous Time Interpolation 4.3 A Markov Chain Interpolation 4.4 A Random Walk Approximation 4.5 A Deterministic Discounted Problem 4.6 Deterministic Relaxed Controls
 5 Construction of the Approximating Markov Chains 5.1 One Dimensional Examples 5.2 Numerical Simplifications 5.3 The General Finite Difference Method 5.4 A Direct Construction 5.5 Variable Grids 5.6 Jump Diffusion Processes 5.7 Reflecting Boundaries 5.8 Dynamic Programming Equations 5.9 Controlled and State Dependent Variance
 6 Computational Methods for Controlled Markov Chains 6.1 The Problem Formulation 6.2 Classical Iterative Methods 6.3 Error Bounds 6.4 Accelerated Jacobi and GaussSeidel Methods 6.5 Domain Decomposition 6.6 Coarse GridFine Grid Solutions 6.7 A Multigrid Method 6.8 Linear Programming
 7 The Ergodic Cost Problem: Formulation and Algorithms 7.1 Formulation of the Control Problem 7.2 A Jacobi Type Iteration 7.3 Approximation in Policy Space 7.4 Numerical Methods 7.5 The Control Problem 7.6 The Interpolated Process 7.7 Computations 7.8 Boundary Costs and Controls
 8 Heavy Traffic and Singular Control 8.1 Motivating Examples 8.2 The Heavy Traffic Problem 8.3 Singular Control
 9 Weak Convergence and the Characterization of Processes 9.1 Weak Convergence 9.2 Criteria for Tightness in $D^{k}\left [0, \infty \right )$ 9.3 Characterization of Processes 9.4 An Example 9.5 Relaxed Controls
 10 Convergence Proofs 10.1 Limit Theorems 10.2 Existence of an Optimal Control 10.3 Approximating the Optimal Control 10.4 The Approximating Markov Chain 10.5 Convergence of the Costs 10.6 Optimal Stopping
 11 Convergence for Reflecting Boundaries, Singular Control, and Ergodic Cost Problems 11.1 The Reflecting Boundary Problem 11.2 The Singular Control Problem 11.3 The Ergodic Cost Problem
 12 Finite Time Problems and Nonlinear Filtering 12.1 Explicit Approximations: An Example 12.2 General Explicit Approximations 12.3 Implicit Approximations: An Example 12.4 General Implicit Approximations 12.5 Optimal Control Computations 12.6 Solution Methods 12.7 Nonlinear Filtering
 13 Controlled Variance and Jumps 13.1 Controlled Variance: Introduction 13.2 Controlled Jumps
 14 Problems from the Calculus of Variations: Finite Time Horizon 14.1 Problems with a Continuous Running Cost 14.2 Numerical Schemes and Convergence 14.3 Problems with a Discontinuous Running Cost
 15 Problems from the Calculus of Variations: Infinite Time Horizon 15.1 Problems of Interest 15.2 Numerical Schemes for the Case $k(x, \alpha ) \geq k_0 > 0$ 15.3 Numerical Schemes for the Case $k(x, \alpha ) \geq 0$ 15.4 Remarks on Implementation and Examples
 16 The Viscosity Solution Approach 16.1 Definitions and Some Properties of Viscosity Solutions 16.2 Numerical Schemes 16.3 Proof of Convergence References Index List of Symbols.
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QA274.2 .K88 2003  Unknown 
 Kushner, Harold J. (Harold Joseph), 1933
 New York : SpringerVerlag, c2003.
 Description
 Book — xxii, 474 p. : ill.
 Algorithmes adaptifs et approximations stochastiques. English
 Benveniste, Albert.
 Berlin ; New York : SpringerVerlag, c1990.
 Description
 Book — xi, 365 p. : ill. ; 25 cm.
 Online
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QA274.225 .B4613 1990  Unknown 
 Kushner, Harold J. (Harold Joseph), 1933
 New York : SpringerVerlag, [1978]
 Description
 Book — x, 261 p. : ill. ; 24 cm.
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QA274 .K8  Available 
 SAGA 2007 (2007 : Zurich, Switzerland)
 Berlin, Heidelberg : SpringerVerlag Berlin Heidelberg, 2007.
 Description
 Book — x, 165 p. : ill.
 Summary

 Invited Papers. On Computation and Communication with Small Bias. Design Strategies for Minimal Perfect Hash Functions. Hamming, Permutations and Automata. Probabilistic Techniques in Algorithmic Game Theory. Randomized Algorithms and Probabilistic Analysis in Wireless Networking. Contributed Papers. A First Step Towards Analyzing the Convergence Time in PlayerSpecific Singleton Congestion Games. Communication Problems in Random LineofSight AdHoc Radio Networks. Approximate Discovery of Random Graphs. A VNS Algorithm for Noisy Problems and Its Application to Project Portfolio Analysis. Digit Set Randomization in Elliptic Curve Cryptography. Lower Bounds for HitandRun Direct Search. An Exponential Gap Between LasVegas and Deterministic Sweeping Finite Automata. Stochastic Methods for Dynamic OVSF Code Assignment in 3G Networks. On the Support Size of Stable Strategies in Random Games.
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 SAGA 2005 (2005 : Moscow State University)
 Berlin ; New York : Springer, 2005.
 Description
 Book — viii, 238 p. : ill.
 SAGA 2005 (2005 : Moscow State University)
 Berlin ; New York : Springer, 2005.
 Description
 Book — viii, 238 p. : ill. ; 24 cm.
 Summary

This book constitutes the refereed proceedings of the Third International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2005, held in Moscow, Russia in October 2005. The 14 revised full papers presented together with 5 invited papers were carefully reviewed and selected for inclusion in the book. The contributed papers included in this volume cover both theoretical as well as applied aspects of stochastic computations whith a special focus on new algorithmic ideas involving stochastic decisions and the design and evaluation of stochastic algorithms within realistic scenarios.
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QA9.58 .S24 2005  Available 
 SAGA 2003 (2003 : Hatfield, Hertfordshire, England)
 Berlin ; New York : Springer, c2003.
 Description
 Book — viii, 166 p. : ill. ; 24 cm.
 Summary

This book constitutes the refereed proceedings of the Second International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2003, held in Hatfield, UK in September 2003.The 12 revised full papers presented together with three invited papers were carefully reviewed and selected for inclusion in the book. Among the topics addressed are ant colony optimization, randomized algorithms for the intersection problem, local search for constraint satisfaction problems, randomized local search and combinatorial optimization, simulated annealing, probabilistic global search, network communication complexity, open shop scheduling, aircraft routing, traffic control, randomized straightline programs, and stochastic automata and probabilistic transformations.
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