Stochastic Algorithms: Foundations and Applications

Invited Papers.- Scenario Reduction Techniques in Stochastic Programming.- Statistical Learning of Probabilistic BDDs.- Regular Contributions.- Learning Volatility of Discrete Time Series Using Prediction with Expert Advice.- Prediction of Long-Range Dependent Time Series Data with Performance Guarantee.- Bipartite Graph Representation of Multiple Decision Table Classifiers.- Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies.- On Evolvability: The Swapping Algorithm, Product Distributions, and Covariance.- A Generic Algorithm for Approximately Solving Stochastic Graph Optimization Problems.- How to Design a Linear Cover Time Random Walk on a Finite Graph.- Propagation Connectivity of Random Hypergraphs.- Graph Embedding through Random Walk for Shortest Paths Problems.- Relational Properties Expressible with One Universal Quantifier Are Testable.- Theoretical Analysis of Local Search in Software Testing.- Firefly Algorithms for Multimodal Optimization.- Economical Caching with Stochastic Prices.- Markov Modelling of Mitochondrial BAK Activation Kinetics during Apoptosis.- Stochastic Dynamics of Logistic Tumor Growth.