Artikel dengan mandat akses publik - Ameet TalwalkarPelajari lebih lanjut
Tersedia di suatu tempat: 37
Federated optimization in heterogeneous networks
T Li, AK Sahu, M Zaheer, M Sanjabi, A Talwalkar, V Smith
Proceedings of Machine learning and systems 2, 429-450, 2020
Mandat: US National Science Foundation, US Department of Defense
Mllib: Machine learning in apache spark
X Meng, J Bradley, B Yavuz, E Sparks, S Venkataraman, D Liu, ...
Journal of Machine Learning Research 17 (34), 1-7, 2016
Mandat: National Natural Science Foundation of China
A large-scale evaluation of computational protein function prediction
P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, ...
Nature methods 10 (3), 221-227, 2013
Mandat: US National Institutes of Health
Random search and reproducibility for neural architecture search
L Li, A Talwalkar
Uncertainty in artificial intelligence, 367-377, 2020
Mandat: US National Science Foundation, US Department of Defense
Adaptive gradient-based meta-learning methods
M Khodak, MFF Balcan, AS Talwalkar
Advances in Neural Information Processing Systems 32, 2019
Mandat: US National Science Foundation, US Department of Defense
Model agnostic supervised local explanations
G Plumb, D Molitor, AS Talwalkar
Advances in neural information processing systems 31, 2018
Mandat: US National Science Foundation, US Department of Defense
Provable guarantees for gradient-based meta-learning
MF Balcan, M Khodak, A Talwalkar
International Conference on Machine Learning, 424-433, 2019
Mandat: US National Science Foundation, US Department of Defense
Federated hyperparameter tuning: Challenges, baselines, and connections to weight-sharing
M Khodak, R Tu, T Li, L Li, MFF Balcan, V Smith, A Talwalkar
Advances in Neural Information Processing Systems 34, 19184-19197, 2021
Mandat: US National Science Foundation, US Department of Defense
Fact: A diagnostic for group fairness trade-offs
JS Kim, J Chen, A Talwalkar
International Conference on Machine Learning, 5264-5274, 2020
Mandat: US National Science Foundation, US Department of Defense
Regularizing black-box models for improved interpretability
G Plumb, M Al-Shedivat, ÁA Cabrera, A Perer, E Xing, A Talwalkar
Advances in Neural Information Processing Systems 33, 10526-10536, 2020
Mandat: US National Science Foundation, US Department of Defense
SM a SH: a benchmarking toolkit for human genome variant calling
A Talwalkar, J Liptrap, J Newcomb, C Hartl, J Terhorst, K Curtis, M Bresler, ...
Bioinformatics 30 (19), 2787-2795, 2014
Mandat: US National Institutes of Health
NAS-bench-360: Benchmarking neural architecture search on diverse tasks
R Tu, N Roberts, M Khodak, J Shen, F Sala, A Talwalkar
Advances in Neural Information Processing Systems 35, 12380-12394, 2022
Mandat: US National Science Foundation, US Department of Defense
Cross-modal fine-tuning: Align then refine
J Shen, L Li, LM Dery, C Staten, M Khodak, G Neubig, A Talwalkar
International Conference on Machine Learning, 31030-31056, 2023
Mandat: US National Science Foundation
Zeno: An interactive framework for behavioral evaluation of machine learning
ÁA Cabrera, E Fu, D Bertucci, K Holstein, A Talwalkar, JI Hong, A Perer
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems …, 2023
Mandat: US National Science Foundation
Efficient architecture search for diverse tasks
J Shen, M Khodak, A Talwalkar
Advances in Neural Information Processing Systems 35, 16151-16164, 2022
Mandat: US National Science Foundation, US Department of Defense
Learning fair representations for kernel models
Z Tan, S Yeom, M Fredrikson, A Talwalkar
International Conference on Artificial Intelligence and Statistics, 155-166, 2020
Mandat: US National Science Foundation, US Department of Defense
Supervised neighborhoods for distributed nonparametric regression
A Bloniarz, A Talwalkar, B Yu, C Wu
Artificial Intelligence and Statistics, 1450-1459, 2016
Mandat: US National Science Foundation
On data efficiency of meta-learning
M Al-Shedivat, L Li, E Xing, A Talwalkar
International Conference on Artificial Intelligence and Statistics, 1369-1377, 2021
Mandat: US National Science Foundation, US Department of Defense
Rethinking neural operations for diverse tasks
N Roberts, M Khodak, T Dao, L Li, C Ré, A Talwalkar
Advances in Neural Information Processing Systems 34, 15855-15869, 2021
Mandat: US National Science Foundation, US Department of Defense, US National …
Learning predictions for algorithms with predictions
M Khodak, MFF Balcan, A Talwalkar, S Vassilvitskii
Advances in Neural Information Processing Systems 35, 3542-3555, 2022
Mandat: US National Science Foundation, US Department of Defense
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