(EURO-) COLT 2001 Preliminary Schedule/Program

Below please find (1) all important events at a glance and, further below (2), the technical conference program.

1. The Conference at a Glance

 

The technical conference program starts Monday July 16th at 9.15 AM and ends Thursday July 19th at 5.01 PM.

Registration

On Sunday evening, July 15th, conference attendees can pick up their registration package in the hotel lobby of the CASA 400 hotel (7.00-10.00 PM). There they can also join us for a mini-reception (7.00-10.00 PM). Conference attendees who do not stay at the CASA 400 hotel and do not want to go there sunday evening, and attendees who arrive late, can pick up their registration package at the conference venue Monday July 16th from 8.30 AM onwards.

Social Events

Invited Talk

Tuesday July 17th, 9.00 AM, David G. Stork of Ricoh California Science Center will give an invited talk.

Impromptu Talks

Wednesday July 18th at 2.00 PM there will be a short session of impromptu talks. You (preferably) have to sign up for these at the registration desk.

Business Meeting

The COLT/EUROCOLT 2001 business meeting will take place Tuesday July 17th, from 5.00-6.00 PM.

 

2. Detailed (Preliminary) Conference Program

Monday July 16th

        

8:30     Registration

9:15     start / welcome / announcements [P. Grünwald/D. Helmbold] 

9:25     2 talks [chair: David Helmbold] 

            Hans-Ulrich Simon, How Many Queries are Needed to learn One Bit of  Information?

 

            Michael Schmitt, Radial Basis Function Neural Networks Have Superlinear VC Dimension

 

10:15   break

10:45   3 talks [chair: Jyrki Kivinen]  

Olivier Bousquet and Manfred K. Warmuth, Tracking a Small Set of  Modes by Mixing Past Posteriors

 

Nicolo Cesa-Bianchi and Gabor Lugosi, Potential-based Algorithms in On-line Prediction and Game Theory

 

Tong Zhang, A Sequential Approximation Bound for Some Sample-Dependent Convex Optimization Problems with Applications in Learning

 

12:00   lunch

2:00     4 talks [chair: Phil Long]

Deepak Chawla, Lin Li and Stephen Scott, Efficiently approximating Weighted Sums with Exponentially Many Terms

 

Koby Crammer and Yoram Singer, Ultraconservative Online Algorithms for Multiclass Problems

 

Paul Goldberg, Estimating a Boolean perceptron from its Average Satisfying Assignment: A bound on the precision required

 

Shie Mannor and Nahum Shimkin, Adaptive Strategies and Regret Minimization in arbitrarily varying Markov Environments

 

3:40     break

4:10     3 talks [chair: Carl Smith]

            John Case, Sanjay Jain, Frank Stephan and Rolf Wiehagen, Robust Learning -- Rich and Poor

 

            Sandra Zilles, On the Synthesis of Strategies Identifying Recursive Functions

 

            Sanjay Jain and Efim Kinber, Intrinsic complexity of learning geometrical concepts from positive data

 

5:25     finish

 

 

Tuesday, July 17th

 

9:00     Invited Talk [introduced by B. Williamson]

Toward a computational theory of data acquisition

by David G. Stork,  Chief Scientist,  Ricoh California Research Center

           

10:00   break

10:30   4 talks [chair: John Shawe-Taylor]

            Antonio Piccolboni and Christian Schindelhauer, Discrete Prediction Games with Arbitrary Feedback and Loss

 

            Peter Bartlett and Shahar Mendelson, Rademacher and Gaussian

Complexities: Risk Bounds and Structural Results

 

            Vladimir Koltchinskii, Dmitry Panchenko and Fernando Lozano, Further

Explanation of the Effectiveness of Voting Methods: The Game

Between Margins and Weights

 

            Shahar Mendelson, Geometric Methods in the Analysis of

Glivenko-Cantelli classes

 

12:10   lunch

2:00     3 talks [chair: Bob Sloan] 

            Shahar Mendelson, Learning Relatively Small Classes

 

            Philip M. Long, On Agnostic Learning with {0, *, 1}-valued and

Real-valued Hypotheses

 

            Paul Goldberg, When can Two Unsupervised Learners Achieve PAC

Separation?

 

3:15     break

3:45     3 talks [chair: Frank Stephan] 

            Peter Grünwald, Strong Entropy Concentration, Game Theory and

Algorithmic Randomness

 

            Ilia Nouretdinov, Volodya Vovk, Michael Vyugin and Alex Gammerman,

Pattern recognition and density estimation under the general iid assumption

 

            Jose L. Balcazar, Jorge Castro and David Guijarro, A General

Dimension for Exact Learning

 

5:00     Business Meeting

6:00     Reception hosted by the city of Amsterdam

Wednesday July 18th

 

9:00     3 talks [chair: Alex Smola]

            Balazs Kegl, Tamas Linder and Gabor Lugosi, Data-Dependent

Margin-Based Generalization Bounds for Classification

 

            Shai Ben-David, Nadav Eiron and Hans Ulrich Simon , Limitations of

Learning Via Embeddings in Euclidean Half-Spaces

 

            Jürgen Forster, Niels Schmitt and Hans Ulrich Simon, Estimating the

optimal Margins of Embeddings in Euclidean Half Spaces

 

10:15   break

10:45   3 talks [chair: Bob Williamson]

            Bernhard Schölkopf, Ralf Herbrich and Alex J. Smola,

A Generalized Representer Theorem

 

            Tong Zhang, A Leave-one-out Validation Bound for Kernel Methods with

Applications in Learning

 

            Mark Herbster, Learning additive models online with fast evaluating kernels

 

12:00   lunch

2:00     Impromptu talks [chair: TBA]/ tour of Amsterdam historical museum (3.45 PM) /

tour of Trippenhuis (4.30 PM) / free time

5:15     Boat trip to evening reception and dinner at Grand Hotel Krasnapolsky

Thursday, July 19th

 

9:00     3 talks [chair: Phil Long]

            Shie Mannor and Ron Meir, Geometric Bounds for Generalization in Boosting

 

            Rocco A. Servedio, Smooth Boosting an Learning with Malicious Noise

 

            Nader Bshouty and Dmitry Gavinsky, On Boosting with Optimal

Poly-Bounded Distributions

 

10:15   break

10:45   3 talks [chair: Paul Vitányi]

Shai Ben-David, Philip M. Long and Yishay Mansour, Agnostic Boosting

 

            Wee Sun Lee and Philip M. Long, A Theoretical analysis of Query

Selection for collaborative Filtering

 

            Nader Bshouty and Vitaly Feldman, On Using Extended Statistical

Queries to avoid Membership Queries

 

12:00   lunch

2:00     3 talks [chair: TBA]

            Nadar Bshouty and Nadav Eiron, Learning Monotone DNF From a

teacher that almost does not answer membership Queries

 

            Rocco A. Servedio, On Learning Monotone DNF under Product Distributions

 

            Nader Bshouty and Avi Owshanko, Learning Regular Sets with an

Incomplete Membership Oracle

 

3:15     break

3:45     3 talks [chair: Peter Grünwald]

            Eyal Even-Dar and Yishay Mansour, Learning rates for Q-Learning

 

            Sham Kakade, Optimizing Average Reward Using Discounted Rewards

 

            Leonid Peshkin and Sayan Mukherjee, Bounds on sample size

for policy evaluation in Markov environments

 

5:00     Closing remarks

5:01     Finish

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Last updated: July 6th, 2001.