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Home > Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings > Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring
Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings |
José L. Balcázar; Philip M. Long; Frank Stephan
Springer Berlin Heidelberg
Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings
Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring
Authors

Chamy Allenberg; Peter Auer; László Györfi; György Ottucsák

ARI Id

1674219807096_3410850

Access

Not Available Free

Pages

229-243

DOI

10.1007/11894841_20

Chapter URL

https://rd.springer.com/chapter/10.1007/11894841_20

Table of Contents of Book
Showing 1 to 20 of 32 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
Editors’ Introduction
Jose L. Balcázar; Philip M. Long; Frank Stephan
1-9
Solving Semi-infinite Linear Programs Using Boosting-Like Methods
Gunnar Rätsch
10-11
e-Science and the Semantic Web: A Symbiotic Relationship
Carole Goble; Oscar Corcho; Pinar Alper; David De Roure
12-12
Spectral Norm in Learning Theory: Some Selected Topics
Hans Ulrich Simon
13-27
Data-Driven Discovery Using Probabilistic Hidden Variable Models
Padhraic Smyth
28-28
Reinforcement Learning and Apprenticeship Learning for Robotic Control
Andrew Y. Ng
29-31
Learning Unions of ω(1)-Dimensional Rectangles
Alp Atıcı; Rocco A. Servedio
32-47
On Exact Learning Halfspaces with Random Consistent Hypothesis Oracle
Nader H. Bshouty; Ehab Wattad
48-62
Active Learning in the Non-realizable Case
Matti Kääriäinen
63-77
How Many Query Superpositions Are Needed to Learn?
Jorge Castro
78-92
Teaching Memoryless Randomized Learners Without Feedback
Frank J. Balbach; Thomas Zeugmann
93-108
The Complexity of Learning SUBSEQ (A)
Stephen Fenner; William Gasarch
109-123
Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive Data
Matthew de Brecht; Akihiro Yamamoto
124-138
Learning and Extending Sublanguages
Sanjay Jain; Efim Kinber
139-153
Iterative Learning from Positive Data and Negative Counterexamples
Sanjay Jain; Efim Kinber
154-168
Towards a Better Understanding of Incremental Learning
Sanjay Jain; Steffen Lange; Sandra Zilles
169-183
On Exact Learning from Random Walk
Nader H. Bshouty; Iddo Bentov
184-198
Risk-Sensitive Online Learning
Eyal Even-Dar; Michael Kearns; Jennifer Wortman
199-213
Leading Strategies in Competitive On-Line Prediction
Vladimir Vovk
214-228
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 32 entries
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