[Lisa_seminaires] Fwd: Seminar at McGill on March 26 at 11:30am

Dumitru Erhan dumitru.erhan at umontreal.ca
Mer 25 Mar 13:03:01 EDT 2009


Reminder - see below

Dumitru


---------- Forwarded message ----------
From: Dumitru Erhan <dumitru.erhan at umontreal.ca>
Date: Wed, Mar 11, 2009 at 13:53
Subject: Seminar at McGill on March 26 at 11:30am
To: lisa_seminaires at iro.umontreal.ca


Note that the seminar will be held in McConnell Engineering Building, room 103

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Sandra Zilles (postdoc at UofA) will be visiting again March 26-27,
and will be giving a talk on Thu March 26, 11:30am.

Title: Cooperative teaching, active learning, and sample compression

Abstract:
The problem of how a teacher and a learner can cooperate in the
process of learning concepts from examples in order to minimize the
required sample size without  "coding tricks" has been widely addressed,
yet without achieving teaching and learning protocols that meet what
intuitively seems an optimal choice for selecting samples in teaching.
In this presentation, two models of cooperative teaching and learning
are introduced.

The model of "subset teaching sets" is based on the idea that both
teacher and learner can iteratively exploit the assumption that the
partner is cooperative, comparable to a two-player game.
The corresponding variant of the teaching dimension turns out to be
nonmonotonic with respect to subclasses of concept classes. That
means, there are concept classes that become easier to teach when
they are expanded. We will discuss why this nonmonotonicity might
be natural in cooperative teaching scenarios.

A second model introduced overcomes the nonmonotonicity of the
subset teaching dimension. "Recursive teaching sets" are based on
nested concept classes. The nesting here reflects the complexity of
teaching subclasses of the given concept class.

We will see how both new models can drastically reduce the sample
size required for teaching a concept - without using coding tricks
(for a simple and intuitive notion of "coding trick").
For instance, monomials can be taught with only two examples
independent of the number of variables (in both models).

It will be shown how this theory of cooperative learning can open
new ways of (a) showing inherent connections between teaching
and active learning and (b) tackling a long-standing open question
on sample compression.

(joint work with Robert Holte, Steffen Lange, and Martin Zinkevich)


Hope to see you there!
Doina



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