Hi! I am a Ph.D. student advised by Prof. Prem Natarajan. My research interests include algorithms and applications of machine learning. I am interested in large scale optimization, metric learning, deep learning, and kernel methods. I am also interested in developing learning algorithms for recommender systems, network analysis, and natural language processing tasks.
News
- Nov.17: our paper A Batch Learning Framework for Scalable Personalized Ranking got accepted by AAAI 2018!
- Aug.17: Will start a research internship in Snap. Inc. in the coming fall!
- Feb.17: Released our Tensorflow based toolkit for implicit recommendation algorithms. Feel free to give a try! github repo
Technical reports
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Kernel Approximation Methods for Speech Recognition
(under journal review)
[arXiv]
-
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets
[arXiv]
Publications
-
A Batch Learning Framework for Scalable Personalized Ranking
[arXiv]
[github]
Kuan Liu, Prem Natarajan. in AAAI 2018 proceedings.
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Sequential Heterogeneous Attribute Embedding for Item Recommendation
[github]
Kuan Liu, Xing Shi, Prem Natarajan. ICDM 2017 SERecsys workshop.
-
WMRB: Learning to Rank in a Scalable Batch Training Approach
[pdf]
[github]
Kuan Liu, Prem Natarajan. in ACM RecSys 2017 Poster Proceedings.
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Temporal Learning and Sequence Modeling for a Job Recommender System
[arXiv]
[github]
[slides]
Kuan Liu, Xing Shi, Anoop Kumar, Linhong Zhu, Prem Natarajan. in ACM RecSys Challenge 2016.
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A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition
[pdf]
Zhiyun Lu*, Dong Guo*, Alireza Bagheri Garakani*, Kuan Liu*, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha. in ICASSP 2016. (* : Equal Contribution)