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Wenlin Chen

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Diffusive Gibbs Sampling

Feb 05, 2024
Wenlin Chen, Mingtian Zhang, Brooks Paige, José Miguel Hernández-Lobato, David Barber

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It HAS to be Subjective: Human Annotator Simulation via Zero-shot Density Estimation

Sep 30, 2023
Wen Wu, Wenlin Chen, Chao Zhang, Philip C. Woodland

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Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking

Jul 12, 2023
Xuewei Wang, Qiang Jin, Shengyu Huang, Min Zhang, Xi Liu, Zhengli Zhao, Yukun Chen, Zhengyu Zhang, Jiyan Yang, Ellie Wen, Sagar Chordia, Wenlin Chen, Qin Huang

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Leveraging Task Structures for Improved Identifiability in Neural Network Representations

Jun 26, 2023
Wenlin Chen, Julien Horwood, Juyeon Heo, José Miguel Hernández-Lobato

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Neural Characteristic Activation Value Analysis for Improved ReLU Network Feature Learning

May 25, 2023
Wenlin Chen, Hong Ge

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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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Optimal Client Sampling for Federated Learning

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

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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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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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