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In recent years, machine learning has seen important advances in its theoretical and practical domains, with some of the most significant applications in online marketing and commerce, personalized medicine, and data-driven policy-making. This dramatic success has led to increased expectations for autonomous systems to make the right decision at the right target at the right time. This gives rise to one of the major challenges of machine learning today that is the understanding of the cause-effect connection. Indeed, actions, intervention, and decisions have important consequences, and so, in seeking to make the best decision, one must understand the process of identifying causality. By embracing causal reasoning autonomous systems will be able to answer counterfactual questions, such as “What if I had treated a patient differently?”, and “What if had ranked a list differently?” thus helping to establish the evidence base for important decision-making processes.
The purpose of this workshop is to bring together experts from different fields to discuss the relationships between machine learning and causal inference and to discuss and highlight the formalization and algorithmization of causality toward achieving human-level machine intelligence.
This purpose will guide the makeup of the invited talks and the topics for the panel discussions. The panel discussions will tackle controversial topics, with the intent of drawing out an engaging intellectual debate and conversation across fields.
This workshop will lead to advance and extend knowledge on how machine learning could be used to conduct causal inference, and how causal inference could support the development of machine learning methods for improved decision-making.
Sat 8:45 a.m. - 9:00 a.m.
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Opening Remarks
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Thorsten Joachims · Nathan Kallus · Michele Santacatterina · Adith Swaminathan · David Sontag · Angela Zhou 🔗 |
Sat 9:00 a.m. - 9:30 a.m.
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Susan Athey
(Presentation)
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Susan Athey 🔗 |
Sat 9:30 a.m. - 10:00 a.m.
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Andrea Rotnitzky
(Presentation)
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Andrea Rotnitzky 🔗 |
Sat 10:00 a.m. - 10:15 a.m.
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Poster Spotlights
Poster spotlights ID: 10, 11, 16, 17, 20, 24, 31 |
Hongseok Namkoong · Marie Charpignon · Maja Rudolph · Amanda Coston · Yuta Saito · Paramveer Dhillon · Alexander Markham 🔗 |
Sat 10:15 a.m. - 11:00 a.m.
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Coffee break, posters, and 1-on-1 discussions
(Break)
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Yangyi Lu · Daniel Chen · Hongseok Namkoong · Marie Charpignon · Maja Rudolph · Amanda Coston · Julius von Kügelgen · Niranjani Prasad · Paramveer Dhillon · Yunzong Xu · Yixin Wang · Alexander Markham · David Rohde · Rahul Singh · Zichen Zhang · Negar Hassanpour · Ankit Sharma · Ciarán Lee · Jean Pouget-Abadie · Jesse Krijthe · Divyat Mahajan · Nan Rosemary Ke · Peter Wirnsberger · Vira Semenova · Dmytro Mykhaylov · Dennis Shen · Kenta Takatsu · Liyang Sun · Jeremy Yang · Alexander Franks · Pak Kan Wong · Tauhid Zaman · Shira Mitchell · min kyoung kang · Qi Yang
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Sat 11:00 a.m. - 11:30 a.m.
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Susan Murphy
(Presentation)
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Susan Murphy 🔗 |
Sat 11:30 a.m. - 12:00 p.m.
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Ying-Qi Zhao
(Presentation)
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Ying-Qi Zhao 🔗 |
Sat 12:00 p.m. - 12:45 p.m.
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Tentative topic: Reasoning about untestable assumptions in the face of unknowable counterfactuals
(Panel discussion)
Tentative topic: How machine learning, and causal inference work together: cross-pollination and new challenges. |
🔗 |
Sat 12:45 p.m. - 2:30 p.m.
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Lunch
(Break)
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🔗 |
Sat 2:30 p.m. - 3:00 p.m.
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Susan Shortreed
(Presentation)
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Susan Shortreed 🔗 |
Sat 3:00 p.m. - 3:15 p.m.
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Contributed talk 1
(Presentation)
Oral Spotlights ID: 8,9, 27 |
Daniel Chen · Jörn Boehnke · Yixin Wang · Jean Bonaldi 🔗 |
Sat 3:15 p.m. - 3:30 p.m.
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Contributed talk 2
(Presentation)
Oral Spotlights ID: 57, 93, 113 |
Divyat Mahajan · Khashayar Khosravi · Alexander D'Amour 🔗 |
Sat 3:30 p.m. - 3:45 p.m.
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Poster Spotlights
Poster Spotlights ID: 34, 35, 39, 50, 56, 68, 75, 111, 112 |
Théophile Griveau-Billion · Rahul Singh · Zichen Zhang · Ciarán Lee · Jesse Krijthe · Grace Charles · Vira Semenova · Rahul Ladhania · Miruna Oprescu 🔗 |
Sat 3:45 p.m. - 4:30 p.m.
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Coffee break, posters, and 1-on-1 discussions
(Break)
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Julius von Kügelgen · David Rohde · Candice Schumann · Grace Charles · Victor Veitch · Vira Semenova · Mert Demirer · Vasilis Syrgkanis · Suraj Nair · Aahlad Puli · Masatoshi Uehara · Aditya Gopalan · Yi Ding · Ignavier Ng · Khashayar Khosravi · Eli Sherman · Shuxi Zeng · Aleksander Wieczorek · Hao Liu · Kyra Gan · Jason Hartford · Miruna Oprescu · Alexander D'Amour · Jörn Boehnke · Yuta Saito · Théophile Griveau-Billion · Chirag Modi · Shyngys Karimov · Jeroen Berrevoets · Logan Graham · Imke Mayer · Dhanya Sridhar · Issa Dahabreh · Alan Mishler · Duncan Wadsworth · Khizar Qureshi · Rahul Ladhania · Gota Morishita · Paul Welle
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Sat 5:00 p.m. - 5:15 p.m.
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Closing Remarks
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🔗 |
Author Information
Michele Santacatterina (TRIPODS Center for Data Science - Cornell University)
Thorsten Joachims (Cornell)
Nathan Kallus (Cornell University)
Adith Swaminathan (Microsoft Research)
David Sontag (MIT)
Angela Zhou (Cornell University)
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