Program | Hikone Data Science 2020

13-14, November, 2020

This symposium will run as a virtual symposium
>> registration form << (closed)


13 Nov (Fri)


JST: UTC+9:00 Session A
chair: Chisako Muramatsu

"Accelerating AI Research – An Introduction to The Latest Technology from NVIDIA for Data Scientist"
Colleen Ruan(Nvidia, Japan)
> Abstract


"Causality diagnosis and Its applications in Industry"
Chunchen Liu (Damo academy, Alibaba group, China)
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chair: Xiaokang Zhou

"Data Science Applications in Energy Efficiency for Smart Building Design"
Ke Yan (National University of Singapore, Singapore)
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"Randomized learning algorithms under heavy-tailed feedback"
Matthew J. Holland (Osaka University, Japan)
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JST: UTC+9:00 Session B
chair: Shohei Shimizu

"Discovering Temporal Causal Relations from Low-Resolution Data"
MingMing Gong (The University of Melbourne, Australia)
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"Recent results on estimating feature relevance and indirect causal contributions"
Patrick Bloebaum (Amazon research tubingen, Germany)
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chair: Ryo Nishide

"Neural Graph Processing: an embedding-based approach"
Cesare Alippi (Politecnico di Milano, Italy)
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14 Nov (Sat)


JST: UTC+9:00 Session C
chair: Osamu Ichikawa

"Semiparametric Inference for Non-monotone Missing-Not-at-Random Data: the No Self-Censoring Model"
Daniel Malinsky (Columbia University, United States of America)
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"Causal Discovery with unobserved confounding and non-Gaussian data"
Samuel Wang (Universityof Chicago’s Booth School of Business, United States of America)
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chair: Akimichi Takemura

"Cultural Color Keyword Analysis using Twitter Text Mining"
Moritz Marutschke (Ritsumeikan University, Japan)
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"Experience of the Development of International Data Science Program at TNI"
Paskorn Apirukvorapinit (Thai-Nichi Institute of Technology, Thailand)
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