no code implementations • 11 May 2021 • Chang Li, Hua Ouyang
Unbiased Learning to Rank (ULTR) studies the problem of learning a ranking function based on biased user interactions.
no code implementations • 14 Aug 2016 • Makoto Yamada, Jiliang Tang, Jose Lugo-Martinez, Ermin Hodzic, Raunak Shrestha, Avishek Saha, Hua Ouyang, Dawei Yin, Hiroshi Mamitsuka, Cenk Sahinalp, Predrag Radivojac, Filippo Menczer, Yi Chang
However, sophisticated learning models are computationally unfeasible for data with millions of features.
no code implementations • 1 Jun 2016 • Tianyi Zhou, Hua Ouyang, Yi Chang, Jeff Bilmes, Carlos Guestrin
We propose a new random pruning method (called "submodular sparsification (SS)") to reduce the cost of submodular maximization.
no code implementations • 10 Nov 2014 • Makoto Yamada, Avishek Saha, Hua Ouyang, Dawei Yin, Yi Chang
We propose a feature selection method that finds non-redundant features from a large and high-dimensional data in nonlinear way.
no code implementations • NeurIPS 2009 • Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray
The long-standing problem of efficient nearest-neighbor (NN) search has ubiquitous applications ranging from astrophysics to MP3 fingerprinting to bioinformatics to movie recommendations.