Selected Publications

Most of previous machine learning algorithms are proposed based on the i.i.d. hypothesis. However, this ideal assumption is often violated in real applications. Therefore, how to address the agnostic selection bias for robust model learning is of paramount importance for both academic research and real applications. In this paper, we incorporate causal technique into predictive modeling and propose a novel Causally Regularized Logistic Regression (CRLR) algorithm by jointly optimize global confounder balancing and weighted logistic regression.
In ACM MM, 2018

Recent Publications

. Causally Regularized Learning with Agnostic Data Selection Bias. In ACM MM, 2018.

Preprint Code Dataset

Recent Posts

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Projects

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Teaching

TA of Digital Image Processing (Undergraduate Course), Spring 2017, 2018

Teaching Assitant, Department of Computer Science and Technology, Tsinghua University

TA of Deep Learning Summer School, 2018

Teaching Assitant, Department of Computer Science and Technology, Tsinghua University

Contact

  • shenzy13 at qq dot com (primary); shenzy17 at mails dot tsinghua dot edu dot cn (alternative)
  • Room 9-317, East Main Building, Tsinghua University, Beijing, 100084, P.R.China