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Dami Choi
Dami Choi
Verified email at cs.toronto.edu
Title
Cited by
Cited by
Year
On empirical comparisons of optimizers for deep learning
D Choi, CJ Shallue, Z Nado, J Lee, CJ Maddison, GE Dahl
arXiv preprint arXiv:1910.05446, 2019
3292019
Backpropagation through the void: Optimizing control variates for black-box gradient estimation
W Grathwohl, D Choi, Y Wu, G Roeder, D Duvenaud
arXiv preprint arXiv:1711.00123, 2017
3072017
Guided evolutionary strategies: Augmenting random search with surrogate gradients
N Maheswaranathan, L Metz, G Tucker, D Choi, J Sohl-Dickstein
International Conference on Machine Learning, 4264-4273, 2019
942019
Gradient estimation with stochastic softmax tricks
M Paulus, D Choi, D Tarlow, A Krause, CJ Maddison
Advances in Neural Information Processing Systems 33, 5691-5704, 2020
712020
Faster neural network training with data echoing
D Choi, A Passos, CJ Shallue, GE Dahl
arXiv preprint arXiv:1907.05550, 2019
512019
Guided evolutionary strategies: escaping the curse of dimensionality in random search
N Maheswaranathan, L Metz, G Tucker, D Choi, J Sohl-Dickstein
202018
Self-tuning stochastic optimization with curvature-aware gradient filtering
RTQ Chen, D Choi, L Balles, D Duvenaud, P Hennig
PMLR, 2020
62020
Tools for Verifying Neural Models' Training Data
D Choi, Y Shavit, DK Duvenaud
Advances in Neural Information Processing Systems 36, 2024
42024
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning
D Choi, D Xin, H Dadkhahi, J Gilmer, A Garg, O Firat, CK Yeh, AM Dai, ...
Advances in Neural Information Processing Systems 36, 2024
2024
Systems and methods for reducing idleness in a machine-learning training system using data echoing
D Choi, AT Passos, CJ Shallue, GE Dahl
US Patent 11,537,949, 2022
2022
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Articles 1–10