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Meta-learning Feature Representations for Adaptive Gaussian Processes via Implicit Differentiation


May 05, 2022
Wenlin Chen, Austin Tripp, José Miguel Hernández-Lobato

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* 17 pages, 6 figures, 3 tables, 1 algorithm 

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Optimal Client Sampling for Federated Learning


Oct 26, 2020
Wenlin Chen, Samuel Horvath, Peter Richtarik

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* 11 pages, 10 pages of Appendix, 6 Figures, 3 algorithms, code available: https://github.com/SamuelHorvath/FL-optimal-client-sampling 

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Deep Learning Recommendation Model for Personalization and Recommendation Systems


May 31, 2019
Maxim Naumov, Dheevatsa Mudigere, Hao-Jun Michael Shi, Jianyu Huang, Narayanan Sundaraman, Jongsoo Park, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Alisson G. Azzolini, Dmytro Dzhulgakov, Andrey Mallevich, Ilia Cherniavskii, Yinghai Lu, Raghuraman Krishnamoorthi, Ansha Yu, Volodymyr Kondratenko, Stephanie Pereira, Xianjie Chen, Wenlin Chen, Vijay Rao, Bill Jia, Liang Xiong, Misha Smelyanskiy

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* 10 pages, 6 figures 

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Multi-Scale Convolutional Neural Networks for Time Series Classification


May 11, 2016
Zhicheng Cui, Wenlin Chen, Yixin Chen

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Compressing Convolutional Neural Networks


Jun 14, 2015
Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen

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Compressing Neural Networks with the Hashing Trick


Apr 19, 2015
Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen

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A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing


Sep 06, 2014
Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen

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* 10 pages 

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