Alexander Grushetsky

Publication Activity (10 Years)

Years Active: 2017-2021
Publications (10 Years): 5

Top Topics

Ranking Functions

Direct Optimization

Gradient Boosting

Learning To Rank Algorithms

Top Venues

Publications

Walker Ravina, Ethan Sterling, Olexiy Oryeshko, Nathan Bell, Honglei Zhuang, Xuanhui Wang, Yonghui Wu, Alexander Grushetsky
Distilling Interpretable Models into Human-Readable Code. CoRR (2021)
Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Alexander Grushetsky, Yonghui Wu, Petr Mitrichev, Ethan Sterling, Nathan Bell, Walker Ravina, Hai Qian
Interpretable Ranking with Generalized Additive Models. WSDM (2021)
Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Alexander Grushetsky, Yonghui Wu, Petr Mitrichev, Ethan Sterling, Nathan Bell, Walker Ravina, Hai Qian
Interpretable Learning-to-Rank with Generalized Additive Models. CoRR (2020)
Natalia Ponomareva, Soroush Radpour, Gilbert Hendry, Salem Haykal, Thomas Colthurst, Petr Mitrichev, Alexander Grushetsky
TF Boosted Trees: A Scalable TensorFlow Based Framework for Gradient Boosting. ECML/PKDD (3) (2017)
Natalia Ponomareva, Soroush Radpour, Gilbert Hendry, Salem Haykal, Thomas Colthurst, Petr Mitrichev, Alexander Grushetsky
TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting. CoRR (2017)