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Ehsan Amid
Ehsan Amid
Research Scientist at Google DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805, 2023
22362023
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ...
arXiv preprint arXiv:2403.05530, 2024
7202024
Efficiently identifying task groupings for multi-task learning
C Fifty, E Amid, Z Zhao, T Yu, R Anil, C Finn
Advances in Neural Information Processing Systems 34, 27503-27516, 2021
2702021
Robust bi-tempered logistic loss based on bregman divergences
E Amid, MK Warmuth, R Anil, T Koren
Advances in Neural Information Processing Systems 32 pre-proceedings …, 2019
1422019
TriMap: Large-scale dimensionality reduction using triplets
E Amid, MK Warmuth
arXiv preprint arXiv:1910.00204, 2019
1342019
Multiview triplet embedding: Learning attributes in multiple maps
E Amid, A Ukkonen
International Conference on Machine Learning, 1472-1480, 2015
852015
Public data-assisted mirror descent for private model training
E Amid, A Ganesh, R Mathews, S Ramaswamy, S Song, T Steinke, ...
International Conference on Machine Learning, 517-535, 2022
552022
A fast method of steel surface defect detection using decision trees applied to LBP based features
SR Aghdam, E Amid, MF Imani
2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA …, 2012
492012
Reparameterizing Mirror Descent as Gradient Descent
E Amid, MK Warmuth
Advances in Neural Information Processing Systems 33 pre-proceedings …, 2020
432020
Winnowing with Gradient Descent
E Amid, MK Warmuth
Conference on Learning Theory (COLT), 2020
362020
To aggregate or not? learning with separate noisy labels
J Wei, Z Zhu, T Luo, E Amid, A Kumar, Y Liu
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
312023
Two-temperature logistic regression based on the Tsallis divergence
E Amid, MK Warmuth, S Srinivasan
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
292019
Enhanced performance for support vector machines as multiclass classifiers in steel surface defect detection
E Amid, SR Aghdam, H Amindavar
International Journal of Electrical and Computer Engineering 6 (7), 693-697, 2012
292012
A kernel-learning approach to semi-supervised clustering with relative distance comparisons
E Amid, A Gionis, A Ukkonen
European Conference on Machine Learning and Principles and Practice of …, 2015
272015
Locoprop: Enhancing backprop via local loss optimization
E Amid, R Anil, M Warmuth
International Conference on Artificial Intelligence and Statistics, 9626-9642, 2022
232022
Constrained instance and class reweighting for robust learning under label noise
A Kumar, E Amid
arXiv preprint arXiv:2111.05428, 2021
212021
Benchmarking neural network training algorithms
GE Dahl, F Schneider, Z Nado, N Agarwal, CS Sastry, P Hennig, ...
arXiv preprint arXiv:2306.07179, 2023
202023
Distributionally Robust Post-hoc Classifiers under Prior Shifts
J Wei, H Narasimhan, E Amid, WS Chu, Y Liu, A Kumar
International Conference on Learning Representations, 2023
202023
A more globally accurate dimensionality reduction method using triplets
E Amid, MK Warmuth
arXiv preprint arXiv:1803.00854, 2018
182018
Learning from randomly initialized neural network features
E Amid, R Anil, W Kotłowski, MK Warmuth
arXiv preprint arXiv:2202.06438, 2022
162022
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