1 Subjects: “...Probability and Statistics in Computer Science...”

2 Table of Contents: “... Concluding Remarks -- 4. Probability Theory -- 4.1 Basic Concepts -- 4.2 Probabilities on Different Sample...”

3 Subjects: “...Probability and Statistics in Computer Science...”

4 Table of Contents: “... -- Probability and Topology -- Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing...”

5 Table of Contents: “..., expectations, and neural networks -- Imprecise quantifiers and conditional probabilities -- Default logics...”

6 Table of Contents: “... -- Probabilistic Rough Set Approaches to Ordinal Classification with Monotonicity Constraints -- Web Page...”

7 Table of Contents: “... IV: Bayes Networks -- Introduction to Bayes Networks -- Elements of Probability and Graph Theory...”

8 Table of Contents: “... of Probability and Graph Theory -- Decompositions -- Evidence Propagation -- Learning Graphical Models -- Belief...”

9 Table of Contents: “... of Probability and Graph Theory -- Decompositions -- Evidence Propagation -- Learning Graphical Models -- Belief...”

10 Table of Contents: “... Based on Partial Probabilistic Information -- A New Contextual Discounting Rule for Lower Probabilities...”

11 Table of Contents: “... -- Normative argumentation and qualitative probability -- Towards a formalization of narratives: Actions...”

12 Table of Contents: “... Applied to Mutual Information and Feature Selection -- Fusing Probabilistic Information on Maximum Entropy...”

13 Table of Contents: “... for Classification -- Estimation of Possibility-Probability Distributions -- Bayesian Assaying of GUHA Nuggets...”

14 Table of Contents: “..., Independence, Probability and Game Theory -- Similarity Relations and Independence Concepts -- Imprecision...”

15 “.... Such extensions of classical probability theory and statistics are useful in many real-life situations, since...”