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CS Colloquium: Robert D. Nowak (University of Wisconsin-Madison) - A Notation and System for Inferring Event Stream Abstractions
Tue, Nov 08, 2016 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Robert D. Nowak, University of Wisconsin-Madison
Talk Title: Learning Human Preferences and Perceptions From Data
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Modeling human perception has many applications in cognitive, social, and educational science, as well as in advertising and commerce. This talk discusses theory and methods for learning rankings and embeddings representing perceptions from datasets of human judgments, such as ratings or comparisons. I will briefly describe an ongoing large-scale experiment with the New Yorker magazine that deals with ranking cartoon captions using on our nextml.org system. Then I will discuss our recent work on ordinal embedding, also known as non-metric multidimensional scaling, which is the problem of representing items (e.g., images) as points in a low-dimensional Euclidean space given constraints of the form "item i is closer to item j than item k." In other words, the goal is to find a geometric representation of data that is faithful to comparative similarity judgments. This classic problem is often used to gauge and visualize perceptual similarities. A variety of algorithms exist for learning metric embeddings from comparison data, but the accuracy and performance of these methods were poorly understood. I will present a new theoretical framework that quantifies the accuracy of learned embeddings and indicates how many comparisons suffice as a function of the number of items and the dimension of the embedding. Furthermore, the theory points to new algorithms that outperform previously proposed methods. I will also describe a few applications of ordinal embedding.
This joint work with Lalit Jain and Kevin Jamieson.
http://nextml.org/assets/next.pdf
https://arxiv.org/pdf/1606.07081v1.pdf
Host: Yan Liu
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Everyone Is Invited
Contact: Assistant to CS chair