133 citations · 294 across the 9 of their papers we have counts for
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stat.ML2017
A Batch Learning Framework for Scalable Personalized Ranking
Kuan Liu, Prem Natarajan
In designing personalized ranking algorithms, it is desirable to encourage a high precision at the top of the ranked list. Existing methods either seek a smooth convex surrogate fo…
stat.ML2017★ 4 cited
WMRB: Learning to Rank in a Scalable Batch Training Approach
Kuan Liu, Prem Natarajan
We propose a new learning to rank algorithm, named Weighted Margin-Rank Batch loss (WMRB), to extend the popular Weighted Approximate-Rank Pairwise loss (WARP). WMRB uses a new ran…
stat.ML2017★ 42 cited
Kernel Approximation Methods for Speech Recognition
Avner May, Alireza Bagheri Garakani, Zhiyun Lu +9
We study large-scale kernel methods for acoustic modeling in speech recognition and compare their performance to deep neural networks (DNNs). We perform experiments on four speech…