Panel: Causal ML Research at Microsoft
Causal machine learning is poised to be the next AI revolution, providing a firm foundation for robust predictions, efficient decisions and human-interpretable explanations. This panel brings together a subset of experts across the Microsoft Research labs to describe their explorations in the frontier of causal ML research. You will learn how MSR approaches explainable AI using causality, how open simulators like CausalCity can accelerate causal discovery, how recommender systems can perform robust counterfactual reasoning, and how important applications in healthcare are enabled by our latest advances in causal ML.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
- Track:
- Causal Machine Learning
- Date:
- Speakers:
- Adith Swaminathan, Javier González Hernández, Justin Ding, Daniel McDuff
- Affiliation:
- Microsoft Research
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
