11. COLT 1998: Madison, Wisconsin, USA

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 Sata with Co-Training. 92-100
  

Invited Talk II

• Stuart J. 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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