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Kailas Vodrahalli
Kailas Vodrahalli
Ph.D. student, Stanford University
Verified email at stanford.edu
Title
Cited by
Cited by
Year
Harmless interpolation of noisy data in regression
V Muthukumar, K Vodrahalli, V Subramanian, A Sahai
IEEE Journal on Selected Areas in Information Theory 1 (1), 67-83, 2020
2342020
Disparities in dermatology AI performance on a diverse, curated clinical image set
R Daneshjou, K Vodrahalli, RA Novoa, M Jenkins, W Liang, V Rotemberg, ...
Science advances 8 (31), eabq6147, 2022
1202022
Serverless linear algebra
V Shankar, K Krauth, K Vodrahalli, Q Pu, B Recht, I Stoica, ...
Proceedings of the 11th ACM Symposium on Cloud Computing, 281-295, 2020
932020
Are all training examples created equal? an empirical study
K Vodrahalli, K Li, J Malik
arXiv preprint arXiv:1811.12569, 2018
572018
Adversarial training helps transfer learning via better representations
Z Deng, L Zhang, K Vodrahalli, K Kawaguchi, JY Zou
Advances in Neural Information Processing Systems 34, 25179-25191, 2021
402021
3D computer vision based on machine learning with deep neural networks: A review
K Vodrahalli, AK Bhowmik
Journal of the Society for Information Display 25 (11), 676-694, 2017
402017
Do humans trust advice more if it comes from ai? an analysis of human-ai interactions
K Vodrahalli, R Daneshjou, T Gerstenberg, J Zou
Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 763-777, 2022
322022
Disparities in dermatology ai: Assessments using diverse clinical images
R Daneshjou, K Vodrahalli, W Liang, RA Novoa, M Jenkins, V Rotemberg, ...
arXiv preprint arXiv:2111.08006, 2021
302021
Uncalibrated models can improve human-ai collaboration
K Vodrahalli, T Gerstenberg, JY Zou
Advances in Neural Information Processing Systems 35, 4004-4016, 2022
262022
TrueImage: a machine learning algorithm to improve the quality of telehealth photos
K Vodrahalli, R Daneshjou, RA Novoa, A Chiou, JM Ko, J Zou
BIOCOMPUTING 2021: Proceedings of the Pacific Symposium, 220-231, 2020
192020
Can large language models provide useful feedback on research papers? A large-scale empirical analysis
W Liang, Y Zhang, H Cao, B Wang, D Ding, X Yang, K Vodrahalli, S He, ...
arXiv preprint arXiv:2310.01783, 2023
152023
Can large language models provide useful feedback on research papers
W Liang, Y Zhang, H Cao, B Wang, D Ding, X Yang, K Vodrahalli, S He, ...
A large-scale empirical analysis. In arXiv preprint, 2023
72023
Are All Training Examples Created Equal
K Vodrahalli, K Li, J Malik
An Empirical Study. CoRR abs/1811.12569, 2018
72018
Predicting visuo-motor diseases from eye tracking data
K Vodrahalli, M Filipkowski, T Chen, J Zou, YJ Liao
PACIFIC SYMPOSIUM ON BIOCOMPUTING 2022, 242-253, 2021
62021
Some new numeric results concerning the Witsenhausen counterexample
V Subramanian, L Brink, N Jain, K Vodrahalli, A Jalan, N Shinde, A Sahai
2018 56th Annual Allerton Conference on Communication, Control, and …, 2018
62018
Development and clinical evaluation of an artificial intelligence support tool for improving Telemedicine photo quality
K Vodrahalli, J Ko, AS Chiou, R Novoa, A Abid, M Phung, K Yekrang, ...
JAMA dermatology 159 (5), 496-503, 2023
42023
Blind interactive learning of modulation schemes: Multi-agent cooperation without co-design
A Sahai, J Sanz, V Subramanian, C Tran, K Vodrahalli
IEEE Access 8, 63790-63820, 2020
42020
Learning to communicate in a noisy environment
A Sahai, J Sanz, V Subramanian, C Tran, K Vodrahalli
arXiv preprint arXiv:1910.09630, 2019
42019
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations
K Vodrahalli, J Zou
arXiv preprint arXiv:2306.08141, 2023
32023
Learning to communicate with limited co-design
A Sahai, J Sanz, V Subramanian, C Tran, K Vodrahalli
2019 57th Annual Allerton Conference on Communication, Control, and …, 2019
32019
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