John Miller

Affiliations:
  • University of California, Berkeley, Department of Electrical Engineering and Computer Sciences , CA, USA
  • Baidu Research, Silicon Valley Artificial Intelligence Lab, Sunnyvale, CA, USA


According to our database1, John Miller authored at least 23 papers between 2015 and 2023.

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Bibliography

2023
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.
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Trans. Mach. Learn. Res., 2023

2022
Validity Challenges in Machine Learning Benchmarks
PhD thesis, 2022

Adversarial Scrutiny of Evidentiary Statistical Software.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
Retiring Adult: New Datasets for Fair Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Outside the Echo Chamber: Optimizing the Performative Risk.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts.
Proceedings of the 37th International Conference on Machine Learning, 2020

Strategic Classification is Causal Modeling in Disguise.
Proceedings of the 37th International Conference on Machine Learning, 2020

The Effect of Natural Distribution Shift on Question Answering Models.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Strategic Adaptation to Classifiers: A Causal Perspective.
CoRR, 2019

Test-Time Training for Out-of-Distribution Generalization.
CoRR, 2019

A Meta-Analysis of Overfitting in Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Model Similarity Mitigates Test Set Overuse.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stable Recurrent Models.
Proceedings of the 7th International Conference on Learning Representations, 2019

The Social Cost of Strategic Classification.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018
When Recurrent Models Don't Need To Be Recurrent.
CoRR, 2018

Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Deep Voice 3: 2000-Speaker Neural Text-to-Speech.
CoRR, 2017

Deep Voice: Real-time Neural Text-to-Speech.
CoRR, 2017

Deep Voice 2: Multi-Speaker Neural Text-to-Speech.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep Voice: Real-time Neural Text-to-Speech.
Proceedings of the 34th International Conference on Machine Learning, 2017

Globally Normalized Reader.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2015
Traversing Knowledge Graphs in Vector Space.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015


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