JSM 2017 Online Program

Legend:
CC = Baltimore Convention Center, H = Hilton Baltimore
* = applied session ! = JSM meeting theme

		Tweet
321	Tue, 8/1/2017, 10:30 AM - 12:20 PM		CC-346
Modern Statistical Learning for Ranking and Crowdsourcing — Topic Contributed Papers
Section on Statistical Learning and Data Science
Organizer(s): Xi Chen, NYU
Chair(s): Xi Chen, NYU
10:35 AM	Top-K Rank Aggregation from Pairwise Comparisons — Yuxin Chen
10:55 AM	Optimal Stopping and Worker Selection in Crowdsourcing: An AdaptiveSequential Probability Ratio Test Framework — Xi Chen, NYU ; Xiaoou Li, University of Minnesota Twin Cities ; Jingcheng Liu, Columbia University ; Zhiliang Ying, Columbia University ; Yunxiao Chen, Emory University
11:15 AM	A Permutation-Based Model for Crowdsourcing: Optimal Estimation and Robustness — Nihar B Shah, Univ of California - Berkeley ; Sivaraman Balakrishnan, Department of Statistics, CMU ; Martin J. Wainwright, EECS and Statistics, University of California, Berkeley
11:35 AM	Sequential Rank Aggregation from Pairwise Comparison — Xiaoou Li, University of Minnesota Twin Cities ; Xi Chen, NYU ; Yunxiao Chen, Emory University ; Jingcheng Liu, Columbia University ; Zhiliang Ying, Columbia University
12:15 PM	Floor Discussion