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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Reminder
---------- Forwarded message ---------- From: Dumitru Erhan dumitru.erhan@umontreal.ca Date: Wed, Mar 11, 2009 at 13:53 Subject: Seminar at McGill on March 26 at 11:30am To: lisa_seminaires@iro.umontreal.ca
Note that the seminar will be held in McConnell Engineering Building, room 103
-------
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
Reminder - see below
Dumitru
---------- Forwarded message ---------- From: Dumitru Erhan dumitru.erhan@umontreal.ca Date: Wed, Mar 11, 2009 at 13:53 Subject: Seminar at McGill on March 26 at 11:30am To: lisa_seminaires@iro.umontreal.ca
Note that the seminar will be held in McConnell Engineering Building, room 103
-------
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
lisa_seminaires@iro.umontreal.ca
-
Dumitru Erhan