Следене
David Dao
Заглавие
Позовавания
Позовавания
Година
Towards Efficient Data Valuation Based on the Shapley Value
R Jia*, D Dao*, B Wang, FA Hubis, M Gurel, N Hynes, B Li, C Zhang, ...
AISTATS, 2019
4352019
Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms
R Jia, D Dao, B Wang, FA Hubis, NM Gurel, B Li, C Zhang, CJ Spanos, ...
VLDB, 2019
2162019
CellProfiler Analyst: interactive data exploration, analysis, and classification of large biological image sets
D Dao, AN Fraser, J Hung, V Ljosa, S Singh, AE Carpenter
Bioinformatics, 057976, 2016
1432016
An open-source solution for advanced imaging flow cytometry data analysis using machine learning
H Hennig, P Rees, T Blasi, L Kamentsky, J Hung, D Dao, AE Carpenter, ...
Methods 112, 201-210, 2017
1012017
A demonstration of sterling: a privacy-preserving data marketplace
N Hynes, D Dao, D Yan, R Cheng, D Song
Proceedings of the VLDB Endowment 11 (12), 2086-2089, 2018
962018
Data capsule: A new paradigm for automatic compliance with data privacy regulations
L Wang, JP Near, N Somani, P Gao, A Low, D Dao, D Song
Heterogeneous Data Management, Polystores, and Analytics for Healthcare …, 2019
542019
Scalability vs. utility: Do we have to sacrifice one for the other in data importance quantification?
R Jia, F Wu, X Sun, J Xu, D Dao, B Kailkhura, C Zhang, B Li, D Song
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
512021
Data debugging with shapley importance over end-to-end machine learning pipelines
B Karlaš, D Dao, M Interlandi, B Li, S Schelter, W Wu, C Zhang
arXiv preprint arXiv:2204.11131, 2022
312022
Anatomy of BioJS, an open source community for the life sciences
G Yachdav, T Goldberg, S Wilzbach, D Dao, I Shih, S Choudhary, ...
Elife 4, e07009, 2015
292015
Ease. ml: A lifecycle management system for machine learning
L Aguilar Melgar, D Dao, S Gan, NM Gürel, N Hollenstein, J Jiang, ...
Proceedings of the Annual Conference on Innovative Data Systems Research …, 2021
262021
Geo-bench: Toward foundation models for earth monitoring
A Lacoste, N Lehmann, P Rodriguez, E Sherwin, H Kerner, B Lütjens, ...
Advances in Neural Information Processing Systems 36, 2024
242024
Toward foundation models for earth monitoring: Proposal for a climate change benchmark
A Lacoste, ED Sherwin, H Kerner, H Alemohammad, B Lütjens, J Irvin, ...
arXiv preprint arXiv:2112.00570, 2021
242021
ReforesTree: A dataset for estimating tropical forest carbon stock with deep learning and aerial imagery
G Reiersen, D Dao, B Lütjens, K Klemmer, K Amara, A Steinegger, ...
Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12119 …, 2022
222022
DataBright: A Data Curation Platform for Machine Learning based on Markets and Trusted Computation
D Dao, D Alistarh, C Musat, C Zhang
ICML Workshop: Game-Theoretic Mechanisms for Data and Information, 2018
19*2018
GainForest: Scaling Climate Finance for Forest Conservation using Interpretable Machine Learning on Satellite Imagery
D Dao, C Cang, C Fung, M Zhang, N Pawlowski, R Gonzales, N Beglinger, ...
ICML Climate Change AI workshop, 2019
182019
Ease. ml: A lifecycle management system for mldev and mlops
L Aguilar, D Dao, S Gan, NM Gurel, N Hollenstein, J Jiang, B Karlas, ...
Conference on Innovative Data Systems Research (CIDR 2021), 2021
92021
Tackling the overestimation of forest carbon with deep learning and aerial imagery
G Reiersen, D Dao, B Lütjens, K Klemmer, X Zhu, C Zhang
arXiv preprint arXiv:2107.11320, 2021
62021
Awful AI
D Dao
URL https://github. com/daviddao/awful-ai/releases/tag/v1. 0.0, 2021
62021
GeoLabels: Towards Efficient Ecosystem Monitoring using Data Programming on Geospatial Information
D Dao, J Rausch, C Zhang
Climate Change AI workshop, NeurIPS 2019, 2019
62019
TrueBranch: Robust Deep Learning-Based Verification of Forest Conservation Projects
S Santamaria*, D Dao*, B Lütjens*, C Zhang
Climate Change AI workshop, ICLR'20, 2020
5*2020
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