Panel: Causal ML in industry
Causal ML is widely used by data science teams in the tech world to give business decision makers data-driven answers. In this panel data science leaders at Amazon, LinkedIn, Netflix and Toyota will offer their unique perspectives on what problems they are solving, which tools have proven effective or ineffective, where they see the future of the field, and what they wish they’d learned sooner.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
- トラック:
- Causal Machine Learning
- 日付:
- スピーカー:
- Greg Lewis, Ya Xu, Totte Harinen, Dawen Liang
- 所属:
- Microsoft Research, LinkedIn, Toyota Research Institute, Netflix
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Greg Lewis
Senior Principal Researcher
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Ya Xu
Head of Data
LinkedIn
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Totte Harinen
Data Scientist
Toyota Research Institute
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Dawen Liang
Senior Research Scientist
Netflix
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Causal Machine Learning
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Opening remarks: Causal Machine Learning
Speakers:- Cheng Zhang
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Research talk: Causal ML and business
Speakers:- Jacob LaRiviere
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Research talk: Can causal learning improve the privacy of ML models?
Speakers:- Shruti Tople
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Panel: Challenges and opportunities of causality
Speakers:- Eric Horvitz,
- Yoshua Bengio,
- Susan Athey
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Research talk: Causal ML and fairness
Speakers:- Allison Koenecke
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Panel: Causal ML Research at Microsoft
Speakers:- Adith Swaminathan,
- Javier González Hernández,
- Justin Ding
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Research talk: Post-contextual-bandit inference
Speakers:- Nathan Kallus
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Demo: Enabling end-to-end causal inference at scale
Speakers:- Eleanor Dillon,
- Amit Sharma
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Panel: Causal ML in industry
Speakers:- Ya Xu,
- Totte Harinen,
- Dawen Liang
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Closing remarks: Causal Machine Learning
Speakers:- Emre Kiciman
