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Events for November 30, 2016
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PhD Defense - Greg Harris
Wed, Nov 30, 2016 @ 10:30 AM - 12:30 PM
Thomas Lord Department of Computer Science
University Calendar
Customized Data Mining Objective Functions
Ph.D. candidate: Greg Harris
Wednesday, Nov. 30, 2016
10:30 AM, EEB 110
Abstract:
Interpretable machine learning models, such as classification rule lists, enable knowledge discovery and model vetting by domain experts. Their transparency, however, often comes at the cost of accuracy, when compared to more complex models. Our research seeks to improve the accuracy of such models while retaining their interpretable rule-based form. Our strategy is to generate domain-dependent objective functions that specify heuristic trade-offs tailored for individual datasets.
Our first contribution is FrontierMiner, a new rule-based algorithm for predicting a target class with high precision. It learns a non-parametric objective function directly from the data. We show that FrontierMiner finds higher-precision rules more often than competing rule induction systems in a study involving 1,000 synthetic datasets and 138 real-world classification tasks. Our second contribution is PRIMER, a new algorithm for maximizing event impact on time series. It has an objective function that adapts to the level of noise in the data. It also incorporates user-provided input on the expected response pattern as a heuristic that helps prevent over-fitting. We show PRIMER is competitive with state-of-the-art regression techniques in a large financial event study, yet has improved model interpretability. Our third contribution is a method of learning an objective function from user feedback in the form of pairwise rankings. With this feedback, we use learning-to-rank algorithms to combine existing measures into an overall objective function that more closely matches the user's preference. We conclude the presentation with directions for future research.
Biography:
Greg Harris is currently a PhD candidate in the Computer Science Department at the University of Southern California. His research interests include data mining, pattern recognition, and machine learning. He also holds a Master of Financial Mathematics degree from the University of Minnesota and a Bachelor of Science degree in Applied Physics from Brigham Young University.
Defense Committee: Viktor Prasanna (chair), Cauligi Raghavendra, Ellis Horowitz
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 110
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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CS Colloquium: Grace Hui Yang (Georgetown University) - Statistical Modeling of Information Seeking
Wed, Nov 30, 2016 @ 02:30 PM - 03:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Grace Hui Yang , Georgetown University
Talk Title: Statistical Modeling of Information Seeking
Series: CS Colloquium
Abstract: Many modern IR systems and data exhibit new characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in big data sets (typically collected over long time spans) and models need to respond to these changes. This talk provides an up-to-date introduction to statistical modeling of information seeking. In particular, I will talk about how we model information seeking as a partially observable Markov decision process and achieve high accuracy in the TREC Session Tracks. I will also talk about evaluation in dynamic information retrieval modeling and the TREC Dynamic Domain Track.
Biography: Grace Hui Yang is an Assistant Professor in the Department of Computer Science at Georgetown University. Grace obtained her Ph.D. from the Language Technologies Institute, Carnegie Mellon University in 2011. Grace's current research interests include dynamic search, search engine evaluation, privacy-preserving information retrieval, and information organization. Prior to this, she conducted research on question answering, ontology construction, near-duplicate detection, multimedia information retrieval and opinion and sentiment detection. Grace is a recipient of the National Science Foundation (NSF) Faculty Early Career Development Program (CAREER) Award. Grace co-chaired the SIGIR 2013-2014 Doctoral Consortium, SIGIR 2017 Workshop, and WSDM 2017 Workshop. She served as an area chair for SIGIR 2014-2017 and ACL 2016. Grace also co-organized the TREC Dynamic Domain Track since 2015.
Host: Cyrus Shahabi
Location: Olin Hall of Engineering (OHE) - 100C
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
