Research talk: Challenges and opportunities in causal machine learning
This talk will highlight the big challenges in causal ML research and present our vision for development and use of causal ML technology for real-world decision making. Microsoft Researchers will focus on what’s needed to achieve the twin benefits: how can machine learning become more robust through causal reasoning, and how causal inference algorithms become more scalable and testable through machine learning techniques.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
- Track:
- Causal Machine Learning
- Date:
- Speakers:
- Amit Sharma, Cheng Zhang, Emre Kiciman, Greg Lewis
- Affiliation:
- Microsoft Research
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Amit Sharma
Principal Researcher
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Cheng Zhang
Principal Researcher
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Emre Kiciman
Senior Principal Research Manager
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Greg Lewis
Senior Principal Researcher
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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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Panel: Challenges and opportunities of causality
Speakers:- Susan Athey,
- Yoshua Bengio,
- Judea Pearl
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Research talk: Causal ML and fairness
Speakers:- Allison Koenecke
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Panel: Causal ML Research at Microsoft
Speakers:- Daniel McDuff,
- Javier González,
- Justin Ding
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Research talk: Post-contextual-bandit inference
Speakers:- Nathan Kallus
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Panel: Causal ML in industry
Speakers:- Ya Xu,
- Totte Harinen,
- Dawen Liang
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