I am a graduate student in Computer Science at Cornell University broadly working in the area of machine learning and algorithms. More specifically, I am interested in problems around counterfactual policy learning and evaluation in addition to thinking about questions on fairness, interpretability and transparency in such settings. I am extremely fortunate to be advised by Thorsten Joachims.
Fair Learning-to-Rank from Implicit Feedback [arXiv]
Himank Yadav*, Zhengxiao Du*, Thorsten Joachims
Under Review as a Conference Submission. 2019.
Detecting Failures in an Asynchronous System That Never Stops Changing [thesis]
Dissertation. Texas A&M University. 2018.
Wide Baseline Matching [report]
Qianqian Wang, Himank Yadav, Wenqi Xian
Counters: Identifying and Summarizing Opposing Media Articles [report]
Himank Yadav, Katherine Van Koevering
Applicability of Language Models to Fact Checking [report]
George Karagiannis, FlorianSuri-Payer, Himank Yadav