Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Varadarajan, P. V."'
Autor:
Badanidiyuru, Ashwinkumar, Ghazi, Badih, Kamath, Pritish, Kumar, Ravi, Leeman, Ethan, Manurangsi, Pasin, Varadarajan, Avinash V, Zhang, Chiyuan
We propose a new family of label randomizers for training regression models under the constraint of label differential privacy (DP). In particular, we leverage the trade-offs between bias and variance to construct better label randomizers depending o
Externí odkaz:
http://arxiv.org/abs/2312.05659
Autor:
Aksu, Hidayet, Ghazi, Badih, Kamath, Pritish, Kumar, Ravi, Manurangsi, Pasin, Sealfon, Adam, Varadarajan, Avinash V
The Privacy Sandbox Attribution Reporting API has been recently deployed by Google Chrome to support the basic advertising functionality of attribution reporting (aka conversion measurement) after deprecation of third-party cookies. The API implement
Externí odkaz:
http://arxiv.org/abs/2311.13586
Autor:
Ghazi, Badih, Kamath, Pritish, Kumar, Ravi, Leeman, Ethan, Manurangsi, Pasin, Varadarajan, Avinash V, Zhang, Chiyuan
We study the task of training regression models with the guarantee of label differential privacy (DP). Based on a global prior distribution on label values, which could be obtained privately, we derive a label DP randomization mechanism that is optim
Externí odkaz:
http://arxiv.org/abs/2212.06074
Autor:
Denison, Carson, Ghazi, Badih, Kamath, Pritish, Kumar, Ravi, Manurangsi, Pasin, Narra, Krishna Giri, Sinha, Amer, Varadarajan, Avinash V, Zhang, Chiyuan
A well-known algorithm in privacy-preserving ML is differentially private stochastic gradient descent (DP-SGD). While this algorithm has been evaluated on text and image data, it has not been previously applied to ads data, which are notorious for th
Externí odkaz:
http://arxiv.org/abs/2211.11896
Autor:
Babenko, Boris, Traynis, Ilana, Chen, Christina, Singh, Preeti, Uddin, Akib, Cuadros, Jorge, Daskivich, Lauren P., Maa, April Y., Kim, Ramasamy, Kang, Eugene Yu-Chuan, Matias, Yossi, Corrado, Greg S., Peng, Lily, Webster, Dale R., Semturs, Christopher, Krause, Jonathan, Varadarajan, Avinash V., Hammel, Naama, Liu, Yun
External eye photos were recently shown to reveal signs of diabetic retinal disease and elevated HbA1c. In this paper, we evaluate if external eye photos contain information about additional systemic medical conditions. We developed a deep learning s
Externí odkaz:
http://arxiv.org/abs/2207.08998
Autor:
Bora, Ashish, Balasubramanian, Siva, Babenko, Boris, Virmani, Sunny, Venugopalan, Subhashini, Mitani, Akinori, Marinho, Guilherme de Oliveira, Cuadros, Jorge, Ruamviboonsuk, Paisan, Corrado, Greg S, Peng, Lily, Webster, Dale R, Varadarajan, Avinash V, Hammel, Naama, Liu, Yun, Bavishi, Pinal
Publikováno v:
The Lancet Digital Health (2021)
Diabetic retinopathy (DR) screening is instrumental in preventing blindness, but faces a scaling challenge as the number of diabetic patients rises. Risk stratification for the development of DR may help optimize screening intervals to reduce costs w
Externí odkaz:
http://arxiv.org/abs/2008.04370
Autor:
Narayanaswamy, Arunachalam, Venugopalan, Subhashini, Webster, Dale R., Peng, Lily, Corrado, Greg, Ruamviboonsuk, Paisan, Bavishi, Pinal, Sayres, Rory, Huang, Abigail, Balasubramanian, Siva, Brenner, Michael, Nelson, Philip, Varadarajan, Avinash V.
Publikováno v:
MICCAI 2020
Model explanation techniques play a critical role in understanding the source of a model's performance and making its decisions transparent. Here we investigate if explanation techniques can also be used as a mechanism for scientific discovery. We ma
Externí odkaz:
http://arxiv.org/abs/2007.05500
Autor:
Mitani, Akinori, Liu, Yun, Huang, Abigail, Corrado, Greg S., Peng, Lily, Webster, Dale R., Hammel, Naama, Varadarajan, Avinash V.
Publikováno v:
Nature Biomedical Engineering (2019)
Despite its high prevalence, anemia is often undetected due to the invasiveness and cost of screening and diagnostic tests. Though some non-invasive approaches have been developed, they are less accurate than invasive methods, resulting in an unmet n
Externí odkaz:
http://arxiv.org/abs/1904.06435
Autor:
Babenko, Boris, Balasubramanian, Siva, Blumer, Katy E., Corrado, Greg S., Peng, Lily, Webster, Dale R., Hammel, Naama, Varadarajan, Avinash V.
Background: Patients with neovascular age-related macular degeneration (AMD) can avoid vision loss via certain therapy. However, methods to predict the progression to neovascular age-related macular degeneration (nvAMD) are lacking. Purpose: To devel
Externí odkaz:
http://arxiv.org/abs/1904.05478
Autor:
Varadarajan, Avinash V., Poplin, Ryan, Blumer, Katy, Angermueller, Christof, Ledsam, Joe, Chopra, Reena, Keane, Pearse A., Corrado, Greg S., Peng, Lily, Webster, Dale R.
Publikováno v:
Investigative Ophthalmology & Visual Science (2018)
Refractive error, one of the leading cause of visual impairment, can be corrected by simple interventions like prescribing eyeglasses. We trained a deep learning algorithm to predict refractive error from the fundus photographs from participants in t
Externí odkaz:
http://arxiv.org/abs/1712.07798