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Author Information
Yingzhen Li (Microsoft Research Cambridge)
Cheng Zhang (Microsoft Research, Cambridge, UK)
Cheng Zhang is a principal researcher at Microsoft Research Cambridge, UK. She leads the Data Efficient Decision Making (Project Azua) team in Microsoft. Before joining Microsoft, she was with the statistical machine learning group of Disney Research Pittsburgh, located at Carnegie Mellon University. She received her Ph.D. from the KTH Royal Institute of Technology. She is interested in advancing machine learning methods, including variational inference, deep generative models, and sequential decision-making under uncertainty; and adapting machine learning to social impactful applications such as education and healthcare. She co-organized the Symposium on Advances in Approximate Bayesian Inference from 2017 to 2019.
Related Events (a corresponding poster, oral, or spotlight)
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2020 Tutorial: (Track1) Advances in Approximate Inference »
Mon. Dec 7th 04:00 -- 06:30 PM Room Virtual
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2021 Workshop: Deep Generative Models and Downstream Applications »
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2020 Poster: VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data »
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2020 Poster: A Causal View on Robustness of Neural Networks »
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2019 Poster: Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck »
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2019 Poster: Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation »
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2019 Poster: Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model »
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