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Invited Talk (Posner Lecture)
Learning with Intelligent Teacher: Similarity Control and Knowledge Transfer
Vladimir Vapnik

Thu Dec 10 06:00 AM -- 06:50 AM (PST) @ Level 2 room 210 AB

In the talk, I will introduce a model of learning with Intelligent Teacher. In this model, Intelligent Teacher supplies (some) training examples $\mathscr{(x_i, y_i), i=1, \dots , l, x_i \in X,y_i \in \{-1,1\}}$ with additional (privileged) information) $\mathscr{x_i^* \in X^*}$ forming training triplets $\mathscr (x_i,x_i^*, y_i), i, \dots , l$. Privileged information is available only for training examples and $not\, available\, for\, text\, examples$. Using privileged information it is required to find a better training processes (that use less examples or more accurate with the same number of examples) than the classical ones. In this lecture, I will present two additional mechanisms that exist in learning with Intelligent Teacher * The mechanism to control Student's concept of examples similarity and * The mechanism to transfer knowledge that can be obtained in space of privileged information to the desired space of decision rules. Privileged information exists for many inference problem and Student-Teacher interaction can be considered as the basic element of intelligent behavior.

Author Information

Vladimir Vapnik (Columbia University and Facebook AI Research, New York)

<p>Vladimir Vapnik is leading scientist in the field of Machine Learning. He laid foundations of the general learning theory, called Vapnik-Chervonenkis (VC) theory, introduced one of the most effective machine learning methods, called Support Vector Machine (SVM) method, and introduced a new learning paradigm, called Learning with Intelligent Teacher.</p> <p>Vladimir is member of National Academy of Engineering (2006), winer of many international Awards which include: the Humboldt Award (2003) the Gabor Award (2005), the Paris Kanellakis Award (2008), the Neural Networks Pioneer Award (2010), the Frank Rosenblatt Award (2012), the Benjamin Franklin Medal in Computer and Cognitive Science (2012), the C&C Prize (Japan), and Kamp de Friet Award (2014).</p>

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