Simulated annealing and Boltzmann machines - a stochastic approach to combinatorial optimization and neural computing

SIMULATED ANNEALING. Combinatorial Optimization. Simulated Annealing. Asymptotic Convergence. Finite-Time Approximation. Simulated Annealing in Practice. Parallel Simulated Annealing Algorithms. BOLTZMANN MACHINES. Neural Computing. Boltzmann Machines. Combinatorial Optimization and Boltzmann Machines. Classification and Boltzmann Machines. Learning and Boltzmann Machines. Appendix. Bibliography. Indices.

[1]  R. T. Cox.  Probability, frequency and reasonable expectation , 1990 .

[2]  Glenn Shafer,et al.  Readings in Uncertain Reasoning , 1990 .

[3]  Gregory F. Cooper,et al.  Probabilistic inference in multiply connected belief networks using loop cutsets , 1990, Int. J. Approx. Reason..

[4]  R. W. Robinson.  Counting unlabeled acyclic digraphs , 1977 .

[5]  David J. Spiegelhalter,et al.  Sequential updating of conditional probabilities on directed graphical structures , 1990, Networks.

[6]  R. H. J. M. Otten,et al.  The Annealing Algorithm , 1989 .

[7]  Judea Pearl,et al.  Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..

[8]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[9]  Éric D. Taillard,et al.  Robust taboo search for the quadratic assignment problem , 1991, Parallel Comput..

[10]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[11]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[12]  J. Rissanen.  Stochastic Complexity and Modeling , 1986 .

[13]  Steffen L. Lauritzen,et al.  aHUGIN: A System Creating Adaptive Causal Probabilistic Networks , 1992, UAI.

[14]  Uffe Kjærulff,et al.  A Computational Scheme for Reasoning in Dynamic Probabilistic Networks , 1992, UAI.

[15]  Edward H. Shortliffe,et al.  A rule-based computer program for advising physicians regarding antimicrobial therapy selection , 1974, ACM '74.

[16]  T. Speed,et al.  Recursive causal models , 1984, Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics.

[17]  L. Ingber.  Very fast simulated re-annealing , 1989 .

[18]  JORMA RISSANEN,et al.  A universal data compression system , 1983, IEEE Trans. Inf. Theory.

[19]  T. Speed,et al.  Markov Fields and Log-Linear Interaction Models for Contingency Tables , 1980 .

[20]  R. F.,et al.  Mathematical Statistics , 1944, Nature.

[21]  Stuart L. Crawford,et al.  Constructor: A System for the Induction of Probabilistic Models , 1990, AAAI.

[22]  Solomon Kullback,et al.  Approximating discrete probability distributions , 1969, IEEE Trans. Inf. Theory.

[23]  Judea Pearl,et al.  Evidential Reasoning Using Stochastic Simulation of Causal Models , 1987, Artif. Intell..

[24]  Eric Horvitz,et al.  Dynamic Network Models for Forecasting , 1992, UAI.

[25]  Judea Pearl,et al.  An Algorithm for Deciding if a Set of Observed Independencies Has a Causal Explanation , 1992, UAI.

[26]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[27]  H. Bozdogan.  Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions , 1987 .

[28]  A. Dawid.  Conditional Independence in Statistical Theory , 1979 .

[29]  N. Wermuth,et al.  Graphical and recursive models for contingency tables , 1983 .

[30]  A. Tversky,et al.  Extensional versus intuitive reasoning: the conjunction fallacy in probability judgment , 1983 .

[31]  Ross D. Shachter,et al.  Simulation Approaches to General Probabilistic Inference on Belief Networks , 2013, UAI.

[32]  N. Wermuth,et al.  On Substantive Research Hypotheses, Conditional Independence Graphs and Graphical Chain Models , 1990 .

[33]  R. Nishii.  Maximum likelihood principle and model selection when the true model is unspecified , 1988 .

[34]  Max Henrion,et al.  Some Practical Issues in Constructing Belief Networks , 1987, UAI.

[35]  Rangasami L. Kashyap,et al.  Optimal Choice of AR and MA Parts in Autoregressive Moving Average Models , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[36]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.