Dear DM members,
We are pleased to announce the finalists for the INFORMS 2024 Data Mining Best Paper Competition Award. The finalists were selected from a pool of high-quality submissions, with each submission double-blind reviewed and scored by a panel of reviewers. The finalists are (ordered alphabetically):
General Track
General Track Finalists will present their works in Session: Data Mining Best Paper Competition (Oct 23 2024 8:00 AM, Regency - 704) in the presence of a panel of judges.
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Title: Trustworthy Feature Importance Avoids Unrestricted Permutations
Authors: Emanuele Borgonovo (Bocconi University); Francesco Cappelli (Bocconi University); Xuefei Lu (SKEMA Business School); Elmar Plischke (Clausthal University of Technology); Cynthia Rudin (Duke University)
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Title: Penalized Additive Gaussian Process for Screening and Optimization of Quantitative and Qualitative Factors in Black-Box Systems
Authors: Yongxiang Li(Shanghai Jiao Tong University); Yu Tian(Shanghai Jiao Tong University); Qian Xiao(University of Georgia); Jianguo Wu(Peking University,)
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Title: Triple Component Matrix Factorization: Untangling Global, Local, and Noisy Components
Authors: Naichen Shi (University of Michigan); Salar Fattahi (University of Michigan); Raed Al Kontar (University of Michigan)
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Title: Cost-aware Bayesian optimization via the Pandora's Box Gittins index
Authors: Qian Xie (Cornell University); Raul Astudillo (Caltech); Peter Frazier (Cornell University); Ziv Scully (Cornell University); Alexander Terenin (Cornell University)
Student Track
Student Track Finalists will present their works in Session: Data Mining Best Student Paper Competition (Oct 20 2024 10:45 AM, Regency - 704) in the presence of a panel of judges.
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Title: Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls
Authors: Aras Selvi (Imperial College Business School); Eleonora Kreacic (JP Morgan AI Research); Mohsen Ghassemi (JP Morgan AI Research); Vamsi Potluru (JP Morgan AI Research); Tucker Balch (JP Morgan AI Research); Manuela Veloso (JP Morgan AI Research)
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Title: MOSS: Multi-Objective Optimization for Stable Rule Sets
Authors: Brian Liu (MIT); Rahul Mazumder (MIT)
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Title: A Bayesian Jump Model-based Pathwise Sampling Approach for Online Anomaly Detection
Authors: Dongmin Li (University of Florida); Miao Bai (University of Connecticut); Di Wang (Shanghai Jiao Tong University); Xiaochen Xian (University of Florida)
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Title: Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
Authors: Jie Wang (Georgia Institute of Technology), March Boedihardjo (Michigan State University), Yao Xie (Georgia Institute of Technology)
Thanks to the reviewers for their time and efforts in the review!
Congratulations to all the finalists!
Competition Steering Committee Chairs:
Hadi Anahideh (University of Illinois Chicago, email: hadis@uic.edu )
Andi Wang (Arizona State University, email: andi.wang@wisc.edu)
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Hadis Anahideh
Assistant Professor
University of Illinois Chicago
Chicago IL
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Hadis Anahideh
Assistant Professor
University of Illinois Chicago
Chicago IL
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