Advanced Lectures on Machine Learning

Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures

Shahar Mendelson, Alexander J. Smola (Herausgeber)

Buch | Softcover

X, 266 Seiten

2003 | 2003
Springer Berlin (Verlag)
978-3-540-00529-2 (ISBN)

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Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11-22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will ?nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop.

A Few Notes on Statistical Learning Theory.- A Short Introduction to Learning with Kernels.- Bayesian Kernel Methods.- An Introduction to Boosting and Leveraging.- An Introduction to Reinforcement Learning Theory: Value Function Methods.- Learning Comprehensible Theories from Structured Data.- Algorithms for Association Rules.- Online Learning of Linear Classifiers.

Erscheint lt. Verlag	31.1.2003
Reihe/Serie	Lecture Notes in Artificial Intelligence
Reihe/Serie	Lecture Notes in Computer Science
Zusatzinfo	X, 266 p.
Verlagsort	Berlin
Sprache	englisch
Maße	155 x 235 mm
Gewicht	410 g
Themenwelt	Informatik ► Theorie / Studium ► Algorithmen
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Sozialwissenschaften
Schlagworte	algorithm • Algorithm analysis and problem complexity • Algorithmic Learning Theory • algorithms • Boosting • Data Analysis • Data Mining • Discovery Science • Hardcover, Softcover / Informatik, EDV/Informatik • HC/Informatik, EDV/Informatik • Kernel Method • Kernel Methods • Knowledge Discovery • learning • Learning Algorithms • Learning Logic • Learning theory • machine learning • Reinforcement Learning • statistical learning theory
ISBN-10	3-540-00529-3 / 3540005293
ISBN-13	978-3-540-00529-2 / 9783540005292
Zustand	Neuware