基本信息
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职业迁徙
个人简介
I am currently working at ByteDance as head of the applied machine learning (AML) research team. Previously, I worked as a research scientist at Google.
Research Highlights:
Learning large-scale end-to-end retrieval models without resorting to approximate nearest neighbor search,
Deep Retrieval: An End-to-End Learnable Structure Model for Large-Scale Recommendations, 2020
Neural networks meet structured Bayesian methods,
Fully Supervised Speaker Diarization provides better accuracy and efficiency in speaker diarization, ICASSP 2019.
Official Google AI blog.
Media reports: VentureBeat, SiliconANGLE, InfoQ, futurism, cnBeta, Sina Tech, iThome, ChinaEmail, eepw, QbitAI, oschina.
Open source on github with 700+ stars!
A generic approach for sequence modeling through segmentations,
Sequence Modeling via Segmentations, ICML 2017;
Towards Neural Phrase-based Machine Translation (code), ICLR 2018;
Subgoal Discovery for Hierarchical Dialogue Policy Learning, EMNLP 2018.
Neural Phrase-to-Phrase Machine Translation on Arxiv.
Lookahead convolution architecture (ICLR 2016 workshop) enabled the deployment of an end-to-end speech recognition system (ICML 2016) to benefit hundreds of millions of users (http://maps.baidu.com) by significantly reducing the latency. See a torch implementation.
Collaborative topic models (KDD 2011) are used by New York Times for their recommendation engine.
Research Highlights:
Learning large-scale end-to-end retrieval models without resorting to approximate nearest neighbor search,
Deep Retrieval: An End-to-End Learnable Structure Model for Large-Scale Recommendations, 2020
Neural networks meet structured Bayesian methods,
Fully Supervised Speaker Diarization provides better accuracy and efficiency in speaker diarization, ICASSP 2019.
Official Google AI blog.
Media reports: VentureBeat, SiliconANGLE, InfoQ, futurism, cnBeta, Sina Tech, iThome, ChinaEmail, eepw, QbitAI, oschina.
Open source on github with 700+ stars!
A generic approach for sequence modeling through segmentations,
Sequence Modeling via Segmentations, ICML 2017;
Towards Neural Phrase-based Machine Translation (code), ICLR 2018;
Subgoal Discovery for Hierarchical Dialogue Policy Learning, EMNLP 2018.
Neural Phrase-to-Phrase Machine Translation on Arxiv.
Lookahead convolution architecture (ICLR 2016 workshop) enabled the deployment of an end-to-end speech recognition system (ICML 2016) to benefit hundreds of millions of users (http://maps.baidu.com) by significantly reducing the latency. See a torch implementation.
Collaborative topic models (KDD 2011) are used by New York Times for their recommendation engine.
研究兴趣
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arxiv(2024)
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arxiv(2023)
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PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023pp.47-57, (2023)
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