Computational Learning Theory

14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, The Netherlands, July 16-19, 2001, Proceedings

By: David Helmbold (Editor), Bob Williamson (Editor)

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Paperback | 4 July 2001

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This volume contains papers presented at the joint 14th Annual Conference on Computational Learning Theory and 5th European Conference on Computat- nal Learning Theory, held at the Trippenhuis in Amsterdam, The Netherlands from July 16 to 19, 2001. The technical program contained 40 papers selected from 69 submissions. In addition, David Stork (Ricoh California Research Center) was invited to give an invited lecture and make a written contribution to the proceedings. The Mark Fulk Award is presented annually for the best paper co-authored by a student. This year's award was won by Olivier Bousquet for the paper "Tracking a Small Set of Modes by Mixing Past Posteriors" (co-authored with Manfred K. Warmuth). We gratefully thank all of the individuals and organizations responsible for the success of the conference. We are especially grateful to the program c- mittee: Dana Angluin (Yale), Peter Auer (Univ. of Technology, Graz), Nello Christianini (Royal Holloway), Claudio Gentile (Universit`a di Milano), Lisa H- lerstein (Polytechnic Univ.), Jyrki Kivinen (Univ. of Helsinki), Phil Long (- tional Univ. of Singapore), Manfred Opper (Aston Univ.), John Shawe-Taylor (Royal Holloway), Yoram Singer (Hebrew Univ.), Bob Sloan (Univ. of Illinois at Chicago), Carl Smith (Univ. of Maryland), Alex Smola (Australian National Univ.), and Frank Stephan (Univ. of Heidelberg), for their e?orts in reviewing and selecting the papers in this volume.

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Non-Fiction Computing & I.T.Computer Science Mathematical Theory of Computation Medicine Medicine in General Artificial Intelligence Machine Learning Mathematics Mathematical Foundation Mathematical Logic Computer Programming & Software Development

Algorithms & Data Structures

How Many Queries Are Needed to Learn One Bit of Information?	p. 1
Radial Basis Function Neural Networks Have Superlinear VC Dimension	p. 14
Tracking a Small Set of Experts by Mixing Past Posteriors	p. 31
Potential-Based Algorithms in Online Prediction and Game Theory	p. 48
A Sequential Approximation Bound for Some Sample-Dependent Convex Optimization Problems with Applications in Learning	p. 65
Efficiently Approximating Weighted Sums with Exponentially Many Terms	p. 82
Ultraconservative Online Algorithms for Multiclass Problems	p. 99
Estimating a Boolean Perceptron from Its Average Satisfying Assignment: A Bound on the Precision Required	p. 116
Adaptive Strategies and Regret Minimization in Arbitrarily Varying Markov Environments	p. 128
Robust Learning - Rich and Poor	p. 143
On the Synthesis of Strategies Identifying Recursive Functions	p. 160
Intrinsic Complexity of Learning Geometrical Concepts from Positive Data	p. 177
Toward a Computational Theory of Data Acquisition and Truthing	p. 194
Discrete Prediction Games with Arbitrary Feedback and Loss	p. 208
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results	p. 224
Further Explanation of the Effectiveness of Voting Methods: The Game between Margins and Weights	p. 241
Geometric Methods in the Analysis of Glivenko-Cantelli Classes	p. 256
Learning Relatively Small Classes	p. 273
On Agnostic Learning with {0,*,1}-Valued and Real-Valued Hypotheses	p. 289
When Can Two Unsupervised Learners Achieve PAC Separation?	p. 303
Strong Entropy Concentration, Game Theory, and Algorithmic Randomness	p. 320
Pattern Recognition and Density Estimation under the General i.i.d. Assumption	p. 337
A General Dimension for Exact Learning	p. 354
Data-Dependent Margin-Based Generalization Bounds for Classification	p. 368
Limitations of Learning via Embeddings in Euclidean Half-Spaces	p. 385
Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces	p. 402
A Generalized Representer Theorem	p. 416
A Leave-One-out Cross Validation Bound for Kernel Methods with Applications in Learning	p. 427
Learning Additive Models Online with Fast Evaluating Kernels	p. 444
Geometric Bounds for Generalization in Boosting	p. 461
Smooth Boosting and Learning with Malicious Noise	p. 473
On Boosting with Optimal Poly-Bounded Distributions	p. 490
Agnostic Boosting	p. 507
A Theoretical Analysis of Query Selection for Collaborative Filtering	p. 517
On Using Extended Statistical Queries to Avoid Membership Queries	p. 529
Learning Monotone DNF from a Teacher That Almost Does Not Answer Membership Queries	p. 546
On Learning Monotone DNF under Product Distributions	p. 558
Learning Regular Sets with an Incomplete Membership Oracle	p. 574
Learning Rates for Q-Learning	p. 589
Optimizing Average Reward Using Discounted Rewards	p. 605
Bounds on Sample Size for Policy Evaluation in Markov Environments	p. 616
Author Index	p. 631
Table of Contents provided by Publisher. All Rights Reserved.

Computational Learning Theory

14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, The Netherlands, July 16-19, 2001, Proceedings

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