Articles by George E. Dahl

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George E. Dahl

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Adaptive Gradient Methods at the Edge of Stability

15 April 2024 by Jeremy Cohen and others

Machine Learning

Benchmarking Neural Network Training Algorithms

12 June 2023 by George Dahl and others

Machine Learning

Pre-training helps Bayesian optimization too

7 July 2022 by Zi Wang and others

Machine Learning, Artificial Intelligence

AI system for fetal ultrasound in low-resource settings

18 March 2022 by Ryan Gomes and others

Machine Learning, Artificial Intelligence

Bad priors, their threats to Bayesian optimization and some remedies via prior learning

19 February 2022 by Zi Wang and others

Machine Learning

Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach

16 December 2021 by Setareh Ariafar and others

Machine Learning

What Will it Take to Fix Benchmarking in Natural Language Understanding?

10 April 2021 by Samuel Bowman and George Dahl

Computation and Language

A Large Batch Optimizer Reality Check: Traditional, Generic Optimizers Suffice Across Batch Sizes

16 February 2021 by Zachary Nado and others

Machine Learning

Large scale distributed neural network training through online distillation

20 August 2020 by Rohan Anil and others

Machine Learning, Artificial Intelligence

Faster Neural Network Training with Data Echoing

4 January 2020 by Dami Choi and others

Machine Learning

On Empirical Comparisons of Optimizers for Deep Learning

4 January 2020 by Dami Choi and others

Machine Learning

Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model

28 October 2019 by Guodong Zhang and others

Machine Learning

Measuring the Effects of Data Parallelism on Neural Network Training

21 November 2018 by Christopher Shallue and others

Machine Learning

The Importance of Generation Order in Language Modeling

23 August 2018 by Nicolas Ford and others

Machine Learning, Computation and Language

Motivating the Rules of the Game for Adversarial Example Research

20 July 2018 by Justin Gilmer and others

Machine Learning

Embedding Text in Hyperbolic Spaces

12 June 2018 by Bhuwan Dhingra and others

Computation and Language, Machine Learning

Parallel Architecture and Hyperparameter Search via Successive Halving and Classification

25 May 2018 by Manoj Kumar and others

Computer Vision and Pattern Recognition, Artificial Intelligence

Neural Message Passing for Quantum Chemistry

12 June 2017 by Justin Gilmer and others

Machine Learning

Machine learning prediction errors better than DFT accuracy

4 June 2017 by Felix Faber and others

Chemical Physics

Detecting Cancer Metastases on Gigapixel Pathology Images

8 March 2017 by Yun Liu and others

Computer Vision and Pattern Recognition

Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes

9 August 2014 by Ryan Prescott Adams and others

Machine Learning

Multi-task Neural Networks for QSAR Predictions

4 June 2014 by George Dahl and others

Machine Learning, Neural and Evolutionary Computing

Improvements to deep convolutional neural networks for LVCSR

11 September 2013 by Tara Sainath and others

Machine Learning, Computation and Language

Training Restricted Boltzmann Machines on Word Observations

5 July 2012 by George Dahl and others

Machine Learning

Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes

25 March 2010 by Ryan Prescott Adams and others

Machine Learning

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Machine Learning Artificial Intelligence Computation and Language Computer Vision and Pattern Recognition Neural and Evolutionary Computing Image and Video Processing Chemical Physics Optimization and Control