Justin Ko

According to our database, Justin Ko authored at least 13 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A multiscale cavity method for sublinear-rank symmetric matrix factorization.

Jean Barbier, Justin Ko, Anas A. Rahman

CoRR, 2024

Crowdsourcing Dermatology Images with Google Search Ads: Creating a Real-World Skin Condition Dataset.

Abbi Ward, Jimmy Li, Julie Wang, Sriram Lakshminarasimhan, Ashley Carrick, Bilson J. L. Campana, Jay Hartford, Pradeep Kumar S, Tiya Tiyasirichokchai, Sunny Virmani, Renee Wong, Yossi Matias, Gregory S. Corrado, Dale R. Webster, Dawn Siegel, Steven Lin, Justin Ko, Alan Karthikesalingam, Christopher Semturs, Pooja Rao

CoRR, 2024

Closing the AI generalization gap by adjusting for dermatology condition distribution differences across clinical settings.

Rajeev V. Rikhye, Aaron Loh, Grace Eunhae Hong, Preeti Singh, Margaret Ann Smith, Vijaytha Muralidharan, Doris Wong, Rory Sayres, Michelle Phung, Nicolas Betancourt, Bradley Fong, Rachna Sahasrabudhe, Khoban Nasim, Alec Eschholz, Basil Mustafa, Jan Freyberg, Terry Spitz, Yossi Matias, Gregory S. Corrado, Katherine Chou, Dale R. Webster, Peggy Bui, Yuan Liu, Yun Liu, Justin Ko, Steven Lin

CoRR, 2024

Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models.

Pierre Mergny, Justin Ko, Florent Krzakala

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Fundamental Limits of Non-Linear Low-Rank Matrix Estimation.

Pierre Mergny, Justin Ko, Florent Krzakala, Lenka Zdeborová

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Optimal Algorithms for the Inhomogeneous Spiked Wigner Model.

Aleksandr Pak, Justin Ko, Florent Krzakala

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Development and Clinical Evaluation of an AI Support Tool for Improving Telemedicine Photo Quality.

Kailas Vodrahalli, Justin Ko, Albert S. Chiou, Roberto A. Novoa, Abubakar Abid, Michelle Phung, Kiana Yekrang, Paige Petrone, James Zou, Roxana Daneshjou

CoRR, 2022

Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set.

Roxana Daneshjou, Kailas Vodrahalli, Roberto A. Novoa, Melissa Jenkins, Weixin Liang, Veronica Rotemberg, Justin Ko, Susan M. Swetter, Elizabeth E. Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, Johan A. C. Allerup, Utako Okata-Karigane, James Zou, Albert Chiou

CoRR, 2022

2021

Disparities in Dermatology AI: Assessments Using Diverse Clinical Images.

Roxana Daneshjou, Kailas Vodrahalli, Weixin Liang, Roberto A. Novoa, Melissa Jenkins, Veronica Rotemberg, Justin Ko, Susan M. Swetter, Elizabeth E. Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, James Zou, Albert Chiou

CoRR, 2021

Towards Realization of Augmented Intelligence in Dermatology: Advances and Future Directions.

Roxana Daneshjou, Carrie Kovarik, Justin M. Ko

CoRR, 2021

TrueImage: A Machine Learning Algorithm to Improve the Quality of Telehealth Photos.

Kailas Vodrahalli, Roxana Daneshjou, Roberto A. Novoa, Albert Chiou, Justin M. Ko, James Zou

Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 2021

2017

Dermatologist-level classification of skin cancer with deep neural networks.

Andre Esteva, Brett Kuprel, Roberto A. Novoa, Justin Ko, Susan M. Swetter, Helen M. Blau, Sebastian Thrun

Nat., 2017

Skin Cancer Detection and Tracking Using Data Synthesis and Deep Learning.

Yunzhu Li, Andre Esteva, Brett Kuprel, Roberto A. Novoa, Justin Ko, Sebastian Thrun

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017