Research talk: Challenges and opportunities in causal machine learning
- Amit Sharma, Cheng Zhang, Emre Kiciman, Greg Lewis | Microsoft Research
- Microsoft Research Summit 2021 | 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)
-
-
Amit Sharma
Principal Researcher
-
Cheng Zhang
Principal Researcher
-
Emre Kiciman
Senior Principal Research Manager
-
Greg Lewis
Senior Principal Researcher
-
-
Causal Machine Learning
-
Opening remarks: Causal Machine Learning
- Cheng Zhang
-
Research talk: Challenges and opportunities in causal machine learning
- Amit Sharma,
- Cheng Zhang,
- Emre Kiciman
-
Research talk: Causal ML and business
- Jacob LaRiviere
-
-
-
-
Research talk: Causality for medical image analysis
- Daniel Coelho de Castro
-
Research talk: Causal ML and fairness
- Allison Koenecke
-
Panel: Causal ML Research at Microsoft
- Adith Swaminathan,
- Javier González Hernández,
- Justin Ding
-
Research talk: Post-contextual-bandit inference
- Nathan Kallus
-
-
Demo: Enabling end-to-end causal inference at scale
- Eleanor Dillon,
- Amit Sharma
-
Panel: Causal ML at Microsoft
- Juan Lavista Ferres,
- Mingqi Wu,
- Sonia Jaffe
-
Panel: Causal ML in industry
- Greg Lewis,
- Ya Xu,
- Totte Harinen
-
Closing remarks: Causal Machine Learning
- Emre Kiciman
