This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. ...
Lire la suiteR's open source nature, free availability, and large number of contributor packages have made R the software of choice for ...
Lire la suiteThis book brings together a collection of classic research papers on the Dempster-Shafer theory of belief functions. By bridging ...
Lire la suiteThe papers are organized in topical sections on recognition, statistical models and visual learning, 3D reconstruction and ...
Lire la suiteThis textbook's significant contribution is the unified derivation of data-assimilation techniques from a common fundamental ...
Lire la suiteThis book describes in detail the practice of the Bayesian statistical approach using many examples chosen for their educational ...
Lire la suiteThis book constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. ...
Lire la suiteThe volume is based on the papers that were presented at the international conference Model-Based Reasoning in Science and ...
Lire la suiteThis textbook provides a comprehensive introduction to the theories and techniques of multi-sensor data fusion. It is aimed ...
Lire la suiteThis book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term ...
Lire la suiteThis relatively nontechnical book is the first account of the history of statistics from the Fisher revolution to the computer ...
Lire la suiteThis book gathers contributions to the 4th International Conference on Soft methods in Probability and Statistics. Its aim ...
Lire la suiteThe inspiration for this volume was a workshop held under the auspices of thePASCAL Network of Excellence. The aimof this ...
Lire la suiteThis book covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian ...
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