High-Dimensional Data

Prasad Naik and Michel Wedel, Track Co-Chairs

Seventh Invitational Choice Symposium
Sponsored by University of Pennsylvania, Wharton School
Philadelphia, Pennsylvania
June 13-17, 2007

Track Participants

Lynd Bacon (LBA Associates), Anand Bodapati (UCLA), Wagner Kamakura (Duke), Jeffrey Kreulen (IBM Research), Peter Lenk (Univ of Michigan), David Madigan (Columbia), Alan Montgomery (Carnegie Mellon Univ), Prasad Naik (Univ of California Davis), Michel Wedel (University of Maryland).

Background and Purpose

Our session track focuses on the analysis of massive datasets in marketing, for example, scanner and transaction data, geodemographic data, clickstream/social network data, image/text databases, recommendation systems and search engines.

Symposium Schedule and Abstracts

Introduction and Abstracts for "High-Dimensional Data"

Presentations

Thursday, June 14

Alan Montgomery (Carnegie Mellon Univ), Computational Challenges for Real-Time Marketing with Large Datasets
Lynd Bacon (LBA Associates), Understanding Choices and Preferences with Massive, Complex On-line Data
Wagner Kamakura (Duke), Comments on "High Dimensional Data Analysis"

Friday, June 15
Jeffrey Kreulen (IBM Research), Leveraging Structured and Unstructed Information Analytics to Create Business Value
David Madigan (Columbia), Statistical Modeling: Bigger and Bigger

Saturday, June 16
Anand Bodapati (UCLA), Issues in the Modeling of Behavior in Online Social Networks
Michel Wedel (Univ of Maryland), State of the Art Recommendation Systems: the Good, the Bad and the Ugly
Peter Lenk, (Univ of Michigan), Approximate Bayes Methods for Massive Data in Conditionally Conjugate Hierarchical Bayes Models
Prasad Naik (Univ of California Davis), Inverse Regression Methods: A Review, Applications and Prospects

Sunday, June 17
Prasad Naik (Univ of California Davis) and Michel Wedel (Maryland), Symposium Plenary Session, Massive Choice Data