STA 290 Seminars

Statistics Seminar Series

FALL 2018:

Fall Seminar Instructor: Prof. Thomas Lee

Location: MSB 1147, Colloquium Room. Held on Thursdays at 4:10pm (unless otherwise stated). The first seminar of Fall 2018 will be held on September 27th.

Students who wish to register for STA 290 credit (1 unit; 2 units with instructor's permission) may use CRN 40825. For the requirement for the obtaining 2 credits for STA 290 please contact Prof. Lee.

  • Thur, Sept 27, 4:10pm:
    • James Sharpnack; Department of Statistics, UC Davis
      • Title: "Learning Patterns for Detection with Multiscale Scan Statistics"
      • ABSTRACT
  • Thur, Oct 4, 4:10pm:
    • Przemek Biecek; Warsaw University of Technology and University of Warsaw
      • Title: "Black-box openers: How to explain predictions from complex ML models?"
      • ABSTRACT
  • Thur, Oct 11, 4:10pm:
    • Yong Jae Lee; Department of Computer Science, UC Davis
      • Title: "Learning to localize and anonymize objects with indirect supervision"
      • ABSTRACT
  • Thur, Oct 18, 4:10pm:
    • Jan Hannig; Department of Statistics and Operations Research, UNC Chapel Hill
      • Title: "Angle Based Joint and Individual Variation Explained"
      • ABSTRACT
  • Thur, Oct 25, 4:10pm:
    • Jiming Jiang; Department of Statistics, UC Davis
      • Title: "Sumca: Simple, Unified, Monte-Carlo Assisted Approach to Second-order Unbiased MSPE Estimation"
      • ABSTRACT
  • Thur, Nov 1, 4:10pm:
    • Oscar Madrid Padilla; Department of Statistics, University of Berkeley
      • Title: "Fused lasso on network estimation problems"
      • ABSTRACT
  • Thur, Nov 8, 4:10pm:
    • Lifeng Lai; Department of Electrical and Computer Engineering, UC Davis
      • Title: “Distributed Statistical Inference with Compressed Data”
      • ABSTRACT
  • Thur, Nov 15, 4:10pm:
    • Paul Baines; GE Digital/
      • Title: "Industrial Machine Learning"
      • ABSTRACT
  • Thur, Nov 29, 4:10pm:
    • Bin Nan; Department of Statistics, UC Irvine
  • Thur, Dec 6, 4:10pm:
    • Silvia Crivelli; Computational Chemistry, Materials & Climate, Lawrence Berkeley National Laboratory
      • Title: “Machine learning approaches for protein classification and protein-ligand binding prediction”
      • ABSTRACT


ALL SEMINARS ARE OPEN TO THE PUBLIC. Seminar speakers / titles / abstracts to be updated soon.

For seminar abstracts from previous quarters, please visit the Recent Seminar Abstract Library.