Dami Choi

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 15

Top Topics

Principal Curvatures

Gradient Estimation

Stochastic Optimization

Top Venues

Publications

Johannes Treutlein, Dami Choi, Jan Betley, Cem Anil, Samuel Marks, Roger Baker Grosse, Owain Evans
Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data. CoRR (2024)
James Requeima, John Bronskill, Dami Choi, Richard E. Turner, David Duvenaud
LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language. CoRR (2024)
Dami Choi, Derrick Xin, Hamid Dadkhahi, Justin Gilmer, Ankush Garg, Orhan Firat, Chih-Kuan Yeh, Andrew M. Dai, Behrooz Ghorbani
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning. NeurIPS (2023)
Dami Choi, Derrick Xin, Hamid Dadkhahi, Justin Gilmer, Ankush Garg, Orhan Firat, Chih-Kuan Yeh, Andrew M. Dai, Behrooz Ghorbani
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning. CoRR (2023)
Dami Choi, Yonadav Shavit, David Kristjanson Duvenaud
Tools for Verifying Neural Models' Training Data. NeurIPS (2023)
Dami Choi, Yonadav Shavit, David Duvenaud
Tools for Verifying Neural Models' Training Data. CoRR (2023)
Ricky T. Q. Chen, Dami Choi, Lukas Balles, David Duvenaud, Philipp Hennig
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering. ICBINB@NeurIPS (2020)
Ricky T. Q. Chen, Dami Choi, Lukas Balles, David Duvenaud, Philipp Hennig
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering. CoRR (2020)
Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison
Gradient Estimation with Stochastic Softmax Tricks. CoRR (2020)
Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison
Gradient Estimation with Stochastic Softmax Tricks. NeurIPS (2020)
Dami Choi, Alexandre Passos, Christopher J. Shallue, George E. Dahl
Faster Neural Network Training with Data Echoing. CoRR (2019)
Niru Maheswaranathan, Luke Metz, George Tucker, Dami Choi, Jascha Sohl-Dickstein
Guided evolutionary strategies: augmenting random search with surrogate gradients. ICML (2019)
Dami Choi, Christopher J. Shallue, Zachary Nado, Jaehoon Lee, Chris J. Maddison, George E. Dahl
On Empirical Comparisons of Optimizers for Deep Learning. CoRR (2019)
Will Grathwohl, Dami Choi, Yuhuai Wu, Geoffrey Roeder, David Duvenaud
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation. ICLR (Poster) (2018)
Will Grathwohl, Dami Choi, Yuhuai Wu, Geoffrey Roeder, David Duvenaud
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation. CoRR (2017)