ICMS Workshop on the Vapnik-Chervonenkis Dimension
Programme (as at 5th September)

The following is a provisional programme for the Meeting, which takes place from Monday 9th to Friday 13th September. The 10:00 orientation talk on Monday will be at a superficial level -- providing no more than signposts for the rest meeting -- and most participants will want to join at the start of the meeting proper, at 11:00. All talks are at 14 India Street.

Disclaimer: this provisional timtable is likely to become less accurate as the week progresses. In particular, it may be necessary to re-pack the contributed talks to accommodate late offers; this may involve adjusting the times given here by up to 10 minutes or so.

Monday

09:00 onwards

Registration.

10:00

A bluffers' guide to the V-C Dimension.

10:30-11:00

Break.

11:00

[Start of workshop proper.] David Haussler (University of California at Santa Cruz), VC Dimension, Covering Numbers and Worst-case Prediction of Individual Sequences

12:10-15:00

Lunch break.

15:00

Nicolò Cesa-Bianchi (University of Milan), A graph-theoretic generalization of the Sauer-Shelah Lemma.

15:40

David Steinsaltz (Technische Universität, Berlin), Vapnik-Cervonenkis techniques for estimating the maxima of certain stochastic processes.

16:20

Shai Ben-David (Technion), Ideals over the reals defined by notions of shattering.

17:00

End.

Tuesday

09:50

Anselm Blumer (Tufts University, MA), Tutorial on PAC Learning.

11:00-11:30

Break.

11:30

Martin Anthony (London School of Economics), Probabilistic generalisation of functions, and uniform convergence.

12:10-15:40

Lunch break.

15:40

John Shawe-Taylor (Royal Holloway College, London), The role of the fat shattering dimension in concept learning.

16:20

Michael Schmitt (Technische Universität, Graz), On the VC-dimension of networks of spiking neurons.

17:00

David Ritchie (James Clerk Maxwell Foundation), James Clerk Maxwell.

18:00

Reception.

[Please turn over.]

Wednesday

09:50

Mark Jerrum (University of Edinburgh), General upper bounds for VC dimension in terms of descriptive and computational complexity.

10:20

Leonid Gurvits (NEC Research Institute, Princeton), Combinatorial and topological properties of VC-dimension and its generalizations.

11:00-11:30

Break.

11:30

Angus Macintyre (Merton College, Oxford), The connection between model theory and VC dimension.

12:10

End.

Thursday

09:50

Shai Ben-David (Technion), VC-dimension, sample-compression schemes and learning.

11:00-11:30

Break.

11:30

Sean B. Holden (University College, London), VC dimension and the sample complexity of error estimation techniques.

12:10-15:00

Lunch break.

15:00

Eli Shamir (Hebrew University, Jerusalem), Dimension of query spaces and noise-robust learning.

15:40

Paul Fischer (Universität Dortmund), A power law for the sample size when learning in the presence of noise.

16:20

Hans Ulrich Simon (Universität Dortmund), Learning in the presence of malicious noise beyond the information-theoretic barrier

17:00

End.

Friday

9:50

Jirí Matousek (Charles University, Prague), Geometric applications: discrepancy and derandomization.

11:00-11:30

Break.

11:30

Peter L. Bartlett (Australian National University), Pattern classification and scale-sensitive versions of the VC-dimension for neural networks.

12:10

Pascal Koiran (ENS, Lyon), VC dimension of feedforward and recurrent neural networks.

12:50

End.

• About this document ...