14. COLT / 5. EuroCOLT 2001: Amsterdam, The Netherlands

• Hans-Ulrich Simon:
  How Many Queries Are Needed to Learn One Bit of Information? 1-13
  
• Michael Schmitt:
  Radial Basis Function Neural Networks Have Superlinear VC Dimension. 14-30
  
• Olivier Bousquet, Manfred K. Warmuth:
  Tracking a Small Set of Experts by Mixing Past Posteriors. 31-47
  
• Nicolò Cesa-Bianchi, Gábor Lugosi:
  Potential-Based Algorithms in Online Prediction and Game Theory. 48-64
  
• Tong Zhang:
  A Sequential Approximation Bound for Some Sample-Dependent Convex Optimization Problems with Applications in Learning. 65-81
  
• Deepak Chawla, Lin Li, Stephen Scott:
  Efficiently Approximating Weighted Sums with Exponentially Many Terms. 82-98
  
• Koby Crammer, Yoram Singer:
  Ultraconservative Online Algorithms for Multiclass Problems. 99-115
  
• Paul W. Goldberg:
  Estimating a Boolean Perceptron from Its Average Satisfying Assignment: A Bound on the Precision Required. 116-127
  
• Shie Mannor, Nahum Shimkin:
  Adaptive Strategies and Regret Minimization in Arbitrarily Varying Markov Environments. 128-142
  
• John Case, Sanjay Jain, Frank Stephan, Rolf Wiehagen:
  Robust Learning - Rich and Poor. 143-159
  
• Sandra Zilles:
  On the Synthesis of Strategies Identifying Recursive Functions. 160-176
  
• Sanjay Jain, Efim B. Kinber:
  Intrinsic Complexity of Learning Geometrical Concepts from Positive Data. 177-193
  
• David G. Stork:
  Toward a Computational Theory of Data Acquisition and Truthing. 194-207
  
• Antonio Piccolboni, Christian Schindelhauer:
  Discrete Prediction Games with Arbitrary Feedback and Loss. 208-223
  
• Peter L. Bartlett, Shahar Mendelson:
  Rademacher and Gaussian Complexities: Risk Bounds and Structural Results. 224-240
  
• Vladimir Koltchinskii, Dmitriy Panchenko, Fernando Lozano:
  Further Explanation of the Effectiveness of Voting Methods: The Game between Margins and Weights. 241-255
  
• Shahar Mendelson:
  Geometric Methods in the Analysis of Glivenko-Cantelli Classes. 256-272
  
• Shahar Mendelson:
  Learning Relatively Small Classes. 273-288
  
• Philip M. Long:
  On Agnostic Learning with {0, *, 1}-Valued and Real-Valued Hypotheses. 289-302
  
• Paul W. Goldberg:
  When Can Two Unsupervised Learners Achieve PAC Separation? 303-319
  
• Peter Grünwald:
  Strong Entropy Concentration, Game Theory, and Algorithmic Randomness. 320-336
  
• Ilia Nouretdinov, Volodya Vovk, Michael V. Vyugin, Alexander Gammerman:
  Pattern Recognition and Density Estimation under the General i.i.d. Assumption. 337-353
  
• José L. Balcázar, Jorge Castro, David Guijarro:
  A General Dimension for Exact Learning. 354-367
  
• Balázs Kégl, Tamás Linder, Gábor Lugosi:
  Data-Dependent Margin-Based Generalization Bounds for Classification. 368-384
  
• Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon:
  Limitations of Learning via Embeddings in Euclidean Half-Spaces. 385-401
  
• Jürgen Forster, Niels Schmitt, Hans-Ulrich Simon:
  Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces. 402-415
  
• Bernhard Schölkopf, Ralf Herbrich, Alex J. Smola:
  A Generalized Representer Theorem. 416-426
  
• Tong Zhang:
  A Leave-One-out Cross Validation Bound for Kernel Methods with Applications in Learning. 427-443
  
• Mark Herbster:
  Learning Additive Models Online with Fast Evaluating Kernels. 444-460
  
• Shie Mannor, Ron Meir:
  Geometric Bounds for Generalization in Boosting. 461-472
  
• Rocco A. Servedio:
  Smooth Boosting and Learning with Malicious Noise. 473-489
  
• Nader H. Bshouty, Dmitry Gavinsky:
  On Boosting with Optimal Poly-Bounded Distributions. 490-506
  
• Shai Ben-David, Philip M. Long, Yishay Mansour:
  Agnostic Boosting. 507-516
  
• Wee Sun Lee, Philip M. Long:
  A Theoretical Analysis of Query Selection for Collaborative Filtering. 517-528
  
• Nader H. Bshouty, Vitaly Feldman:
  On Using Extended Statistical Queries to Avoid Membership Queries. 529-545
  
• Nader H. Bshouty, Nadav Eiron:
  Learning Monotone DNF from a Teacher That Almost Does Not Answer Membership Queries. 546-557
  
• Rocco A. Servedio:
  On Learning Monotone DNF under Product Distributions. 558-573
  
• Nader H. Bshouty, Avi Owshanko:
  Learning Regular Sets with an Incomplete Membership Oracle. 574-588
  
• Eyal Even-Dar, Yishay Mansour:
  Learning Rates for Q-Learning. 589-604
  
• Sham Kakade:
  Optimizing Average Reward Using Discounted Rewards. 605-615
  
• Leonid Peshkin, Sayan Mukherjee:
  Bounds on Sample Size for Policy Evaluation in Markov Environments. 616-630
  

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