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2020 – today
- 2023
[i8]Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, Mike Schaekermann, Amy Wang, Mohamed Amin, Sami Lachgar, Philip Andrew Mansfield, Sushant Prakash, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Nenad Tomasev, Yun Liu
, Renee Wong, Christopher Semturs, S. Sara Mahdavi, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Shekoofeh Azizi, Alan Karthikesalingam, Vivek Natarajan:
Towards Expert-Level Medical Question Answering with Large Language Models. CoRR abs/2305.09617 (2023)- [i7]David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy, Tatiana Matejovicova, Melih Barsbey, Patricia Strachan, Mike Schaekermann, Jan Freyberg, Rajeev Rikhye, Beverly Freeman, Javier Perez Matos, Umesh Telang, Dale R. Webster, Yuan Liu, Gregory S. Corrado, Yossi Matias, Pushmeet Kohli, Yun Liu, Arnaud Doucet, Alan Karthikesalingam:
Evaluating AI systems under uncertain ground truth: a case study in dermatology. CoRR abs/2307.02191 (2023) - [i6]Tao Tu, Shekoofeh Azizi, Danny Driess, Mike Schaekermann, Mohamed Amin, Pi-Chuan Chang, Andrew Carroll, Chuck Lau, Ryutaro Tanno, Ira Ktena, Basil Mustafa, Aakanksha Chowdhery, Yun Liu, Simon Kornblith, David J. Fleet, Philip Andrew Mansfield, Sushant Prakash, Renee Wong, Sunny Virmani, Christopher Semturs, S. Sara Mahdavi, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Karan Singhal, Pete Florence, Alan Karthikesalingam, Vivek Natarajan:
Towards Generalist Biomedical AI. CoRR abs/2307.14334 (2023) - 2022
- [j6]Vivek Krishna Pradhan, Mike Schaekermann, Matthew Lease:
In Search of Ambiguity: A Three-Stage Workflow Design to Clarify Annotation Guidelines for Crowd Workers. Frontiers Artif. Intell. 5: 828187 (2022) - [j5]Lora Aroyo, Matthew Lease, Praveen K. Paritosh, Mike Schaekermann:
Data excellence for AI: why should you care? Interactions 29(2): 66-69 (2022) - 2021
- [j4]Danula Hettiachchi, Mike Schaekermann, Tristan McKinney, Matthew Lease:
The Challenge of Variable Effort Crowdsourcing and How Visible Gold Can Help. Proc. ACM Hum. Comput. Interact. 5(CSCW2): 332:1-332:26 (2021) - [c10]Danula Hettiachchi, Mark Sanderson, Jorge Gonçalves, Simo Hosio, Gabriella Kazai, Matthew Lease, Mike Schaekermann, Emine Yilmaz:
Investigating and Mitigating Biases in Crowdsourced Data. CSCW Companion 2021: 331-334 - [i5]Danula Hettiachchi, Mike Schaekermann, Tristan McKinney, Matthew Lease:
The Challenge of Variable Effort Crowdsourcing and How Visible Gold Can Help. CoRR abs/2105.09457 (2021) - [i4]Lora Aroyo, Matthew Lease, Praveen K. Paritosh, Mike Schaekermann:
Data Excellence for AI: Why Should You Care. CoRR abs/2111.10391 (2021) - [i3]Danula Hettiachchi, Mark Sanderson, Jorge Gonçalves, Simo Hosio, Gabriella Kazai, Matthew Lease, Mike Schaekermann, Emine Yilmaz:
Proceedings of the CSCW 2021 Workshop - Investigating and Mitigating Biases in Crowdsourced Data. CoRR abs/2111.14322 (2021) - [i2]Vivek Krishna Pradhan, Mike Schaekermann, Matthew Lease:
In Search of Ambiguity: A Three-Stage Workflow Design to Clarify Annotation Guidelines for Crowd Workers. CoRR abs/2112.02255 (2021) - 2020
- [b1]Mike Schaekermann:
Human-AI Interaction in the Presence of Ambiguity: From Deliberation-based Labeling to Ambiguity-aware AI. University of Waterloo, Ontario, Canada, 2020 - [j3]Mike Schaekermann, Christopher Homan, Lora Aroyo, Praveen K. Paritosh, Kurt D. Bollacker, Chris Welty:
The AI Bookie - Place Your Bets: Will Machine Learning Outgrow Human Labeling? AI Mag. 41(4): 123-126 (2020) - [c9]Mike Schaekermann, Graeme Beaton, Elaheh Sanoubari, Andrew Lim, Kate Larson, Edith Law:
Ambiguity-aware AI Assistants for Medical Data Analysis. CHI 2020: 1-14 - [c8]Mike Schaekermann, Carrie J. Cai, Abigail E. Huang, Rory Sayres:
Expert Discussions Improve Comprehension of Difficult Cases in Medical Image Assessment. CHI 2020: 1-13
2010 – 2019
- 2019
- [j2]Mike Schaekermann, Graeme Beaton, Minahz Habib, Andrew Lim, Kate Larson, Edith Law:
Understanding Expert Disagreement in Medical Data Analysis through Structured Adjudication. Proc. ACM Hum. Comput. Interact. 3(CSCW): 76:1-76:23 (2019) - [c7]Robin Cohen, Mike Schaekermann, Sihao Liu, Michael Cormier:
Trusted AI and the Contribution of Trust Modeling in Multiagent Systems. AAMAS 2019: 1644-1648 - [c6]Mike Schaekermann, Graeme Beaton, Minahz Habib, Andrew Lim, Kate Larson, Edith Law:
Capturing Expert Arguments from Medical Adjudication Discussions in a Machine-readable Format. WWW (Companion Volume) 2019: 1131-1137 - 2018
- [j1]Mike Schaekermann, Joslin Goh, Kate Larson, Edith Law:
Resolvable vs. Irresolvable Disagreement: A Study on Worker Deliberation in Crowd Work. Proc. ACM Hum. Comput. Interact. 2(CSCW): 154:1-154:19 (2018) - [c5]Mike Schaekermann, Edith Law, Kate Larson, Andrew Lim:
Expert Disagreement in Sequential Labeling: A Case Study on Adjudication in Medical Time Series Analysis. SAD/CrowdBias@HCOMP 2018: 55-66 - [i1]Sonia Phene, R. Carter Dunn, Naama Hammel, Yun Liu, Jonathan Krause, Naho Kitade, Mike Schaekermann, Rory Sayres, Derek J. Wu, Ashish Bora, Christopher Semturs, Anita Misra, Abigail E. Huang, Arielle Spitze, Felipe A. Medeiros, April Y. Maa, Monica Gandhi, Gregory S. Corrado, Lily Peng, Dale R. Webster:
Deep Learning to Assess Glaucoma Risk and Associated Features in Fundus Images. CoRR abs/1812.08911 (2018) - 2017
- [c4]Edith Law, Pierre-Yves Oudeyer, Ming Yin, Mike Schaekermann, Alex C. Williams:
Designing for Curiosity: An Interdisciplinary Workshop. CHI Extended Abstracts 2017: 586-592 - [c3]Rina R. Wehbe, Elisa D. Mekler, Mike Schaekermann, Edward Lank, Lennart E. Nacke:
Testing Incremental Difficulty Design in Platformer Games. CHI 2017: 5109-5113 - [c2]Mike Schaekermann, Giovanni Ribeiro, Guenter Wallner, Simone Kriglstein, Daniel M. Johnson, Anders Drachen, Rafet Sifa, Lennart E. Nacke:
Curiously Motivated: Profiling Curiosity with Self-Reports and Behaviour Metrics in the Game "Destiny". CHI PLAY 2017: 143-156 - [c1]Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart:
Online Bayesian Transfer Learning for Sequential Data Modeling. ICLR (Poster) 2017
Coauthor Index
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last updated on 2023-11-13 23:27 CET by the dblp team
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