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ORCID14th COLT / 5. EuroCOLT 2001: Amsterdam, The Netherlands
- David P. Helmbold, Robert C. Williamson:
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. Lecture Notes in Computer Science 2111, Springer 2001, ISBN 3-540-42343-5 - 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, Alex 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, Alexander 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 M. 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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