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11th COLT 1998: Madison, Wisconsin, USA
- Peter L. Bartlett, Yishay Mansour:

Proceedings of the Eleventh Annual Conference on Computational Learning Theory, COLT 1998, Madison, Wisconsin, USA, July 24-26, 1998. ACM 1998, ISBN 1-58113-057-0
Session 1
- Nicolò Cesa-Bianchi, Gábor Lugosi:

On Sequential Prediction of Individual Sequences Relative to a Set of Experts. 1-11 - V. G. Vovk, Chris Watkins:

Universal Portfolio Selection. 12-23 - Mark Herbster, Manfred K. Warmuth:

Tracking the Best Regressor. 24-31 - Kenji Yamanishi

:
Minimax Relative Loss Analysis for Sequential Prediction Algorithms Using Parametric Hypotheses. 32-43
Session 2
- John Case, Sanjay Jain, Matthias Ott, Arun Sharma, Frank Stephan:

Robust Learning Aided by Context. 44-55 - Jochen Nessel:

Birds Can Fly. 56-63 - Andrew R. Mitchell:

Learnability of a Subclass of Extended Pattern Languages. 64-71 - Léa Meyer:

Aspects of Complexity of Conservative Probabilistic Learning. 72-78
Invited Talk I
- Meir Feder:

Learning to Communicate via Unknown Channel (Abstract). 79
Session 3
- Robert E. Schapire, Yoram Singer:

Improved Boosting Algorithms using Confidence-Rated Predictions. 80-91 - Avrim Blum, Tom M. Mitchell:

Combining Labeled and Unlabeled Data with Co-Training. 92-100
Invited Talk II
- Stuart Russell

:
Learning Agents for Uncertain Environments (Extended Abstract). 101-103
Session 4
- Claudio Gentile, David P. Helmbold:

Improved Lower Bounds for Learning from Noisy Examples: An Information-Theoretic Approach. 104-115 - Philip M. Long:

The complexity of learning according to two models of a drifting environment. 116-125 - Philip M. Long:

On the Sample Complexity of Learning Functions with Bounded Variation. 126-133 - David Gamarnik:

Efficient Learning of Monotone Concepts via Quadratic Optimization. 134-143
Session 5
- Andreas Birkendorf, Norbert Klasner, Christian Kuhlmann, Hans Ulrich Simon

:
Structural Results about Exact Learning with Unspecified Attribute Values. 144-153 - Roni Khardon:

Learning First Order Universal Horn Expressions. 154-165 - Irene Tsapara

, György Turán:
Learning Atomic Formulas with Prescribed Properties. 166-174 - Thomas R. Amoth, Paul Cull, Prasad Tadepalli

:
Exact Learning of Tree Patterns from Queries and Counterexamples. 175-186
Session 6
- Sanjay Jain, Carl H. Smith, Rolf Wiehagen:

On the Power of Learning Robustly. 187-197 - Rüdiger Reischuk, Thomas Zeugmann:

Learning One-Variable Pattern Languages in Linear Average Time. 198-208
Session 7
- Yoav Freund, Robert E. Schapire:

Large Margin Classification Using the Perceptron Algorithm. 209-217 - Martin Anthony, Sean B. Holden:

Cross-Validation for Binary Classification by Real-Valued Functions: Theoretical Analysis. 218-229 - David A. McAllester:

Some PAC-Bayesian Theorems. 230-234 - Matthias Miltrup, Georg Schnitger:

Neural Networks and Efficient Associative Memory. 235-246
Session 8
- Yoav Freund:

Self Bounding Learning Algorithms. 247-258 - Christopher D. Rosin:

Sample Complexity of Model-Based Search. 259-267 - Michael J. Kearns, Dana Ron:

Testing Problems with Sub-Learning Sample Complexity. 268-279 - Baruch Awerbuch, Stephen G. Kobourov

:
Polylogarithmic-Overhead Piecemeal Graph Exploration. 280-286
Session 9
- Leslie G. Valiant:

Projection Learning. 287-293 - Amos Beimel, Felix Geller, Eyal Kushilevitz:

The Query Complexity of Finding Local Minima in the Lattice. 294-302

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