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Author Information
Zhenhong Sun (Alibaba Group)
Ming Lin (Alibaba Group)
I am a Staff Algorithm Engineer at DAMO Academy of Alibaba Group (U.S.). My research interests include Mathematical Foundation of Deep Learning and Statistical Machine Learning, with their applications in Neural Architecture Search, Computer Vision, Mobile AI and any other real-world problems. Before I joined Alibaba Group (U.S.), I was a Research Investigator in the Medical School of Michigan University until April 2019. I worked as a postdoctoral researcher in the School of Computer Science at Carnegie Mellon University from July 2014 to Sep 2015. I received my Ph.D. degree in computer science from Tsinghua University in 2014. During my Ph.D. study, I had been a visiting scholar in Michigan State University and in CMU from Dec 2013 to July 2014.
Xiuyu Sun (Alibaba Group)
Zhiyu Tan (Alibaba Group)
Hao Li (Alibaba Group)
rong jin (alibaba group)
Related Events (a corresponding poster, oral, or spotlight)
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2022 Poster: MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection »
Wed. Jul 20th through Thu the 21st Room #118
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2022 Poster: FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting »
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2022 Spotlight: FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting »
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2021 Poster: Dash: Semi-Supervised Learning with Dynamic Thresholding »
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2021 Oral: Dash: Semi-Supervised Learning with Dynamic Thresholding »
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2019 Poster: On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization »
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2019 Poster: On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization »
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2019 Poster: Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence »
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2019 Oral: Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence »
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2019 Oral: On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization »
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2019 Oral: On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization »
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2018 Poster: Dynamic Regret of Strongly Adaptive Methods »
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2018 Oral: Dynamic Regret of Strongly Adaptive Methods »
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