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seminars:sml

Data Science Seminar

The former Statistical Machine Learning seminar

The Data Science Seminar is evolved from the former Statistical Machine Learning Seminar which covered topics in statistical theory that was important for machine learning research as well as development and applications of machine learning techniques in interdisciplinary research. The scope of the Data Science Seminar has been broadened to facilitate dialogue among different communities in the data science circle.

It is listed as course MATH 568.

Location: Whitney 100E (See the directions to the department)
Time: Tuesday 12–1
Organizer: Xingye Qiao

See also the Statistics Seminar.
When no seminar talk is scheduled, an internal Machine Learning Working Group meeting is held.
Previous talks in the Statistical Machine Learning Seminar and even earlier talks


Spring 2017

  • January 17
    NO SEMINAR OR GROUP MEETING
  • March 7
    WINTER BREAK
  • March 14
    Speaker: Qiusheng Wu (Geography at Binghamton University)
    Topic: Environmental Monitoring and Analysis with Geospatial Big Data Powered by Google Earth Engine
    Abstract
  • March 21
    Speaker: Utkarsh Dang (Mathematical Sciences and CLT at Binghamton University)
    Topic: Tools for Efficient Statistical Computing in R
    Abstract
  • March 28
    Speaker: Yunzhang Zhu (Ohio State University)
    Topic: Maximum Likelihood Inference for a Large Precision Matrix
    Abstract
  • April 4
    Speaker: Guanhua Yan (CS at Binghamton University)
    Topic: Improving Efficiency of Link Clustering on Multi-Core Machines
    Abstract
  • April 11
    SPRING BREAK
  • May 2
    Speaker: name (Binghamton University)
    Topic: Reserved for Thesis Proposal
    Abstract
seminars/sml.txt · Last modified: 2017/03/23 11:15 by qiao