Peter Auer
Publications / Theses
- 1998
- Published
Approximating Hyper-Rechtangles: Learning and Pseudorandon Sets
Auer, P., Long, P. M. & Srinivasan, A., 1998, In: Journal of computer and system sciences (JCSS). 57, p. 376-388Research output: Contribution to journal › Article › Research › peer-review
- Published
Introduction to the Special Issue on Computational Learning Theory
Auer, P. & Maas, W., 1998, In: Algorithmica. 22, p. 1-2Research output: Contribution to journal › Article › Research › peer-review
- Published
On Learning from Ambiguous Information
Auer, P., 1998, In: Periodica polytechnica / Electrical engineering. 1, p. 115-122Research output: Contribution to journal › Article › Research › peer-review
- Published
On-line Learning with Malicious Noise and the Closure Algorithm
Auer, P. & Cesa-Bianchi, N., 1998, In: Annals of mathematics and artificial intelligence. 23, p. 83-99Research output: Contribution to journal › Article › Research › peer-review
- Published
Some thoughts on Boosting and Neural Networks
Auer, P., 1998, 3. Cottbuser Workshop "Aspekte des Neuronalen Lernens". p. 11-28Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Tracking the Best Disjunction
Auer, P. & Warmuth, M. K., 1998, In: Machine learning. 32, p. 127-150Research output: Contribution to journal › Article › Research › peer-review
- 1997
- Published
Approximating Hyper-Rectangles: Learning and Pseudo-random Sets
Auer, P., Long, P. M. & Srinivasan, A., 1997, Proc. 29th Ann. Symp. Theory of Computing. p. 314-323Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Learning Nested Differences in the Presence of Malicious Noise
Auer, P., 1997, In: THEORETICAL COMPUTER SCIENCE. 185, p. 159-175Research output: Contribution to journal › Article › Research › peer-review
- Published
On Learning from Multi-Instance Examples: Empirical Evaluation of a Theoretical Approach
Auer, P., 1997, On Learning from Multi-Instance Examples: Empirical Evaluation of a Theoretical Approach. p. 21-29Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
The Perceptron algorithm vs. Winnow: linear vs. logarithmic mistake bounds when few input variables are relevant
Auer, P., Kivinen, J. & Warmuth, M. K., 1997, In: Artificial intelligence. p. 325-343Research output: Contribution to journal › Article › Research › peer-review
