Feynman T. Liang

According to our database, Feynman T. Liang authored at least 8 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

A Heavy-Tailed Algebra for Probabilistic Programming.

Feynman T. Liang, Liam Hodgkinson, Michael W. Mahoney

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows.

Feynman T. Liang, Michael W. Mahoney, Liam Hodgkinson

Proceedings of the International Conference on Machine Learning, 2022

2021

Accelerating Metropolis-Hastings with Lightweight Inference Compilation.

Feynman T. Liang, Nimar S. Arora, Nazanin Khosravani Tehrani, Yucen Lily Li, Michael Tingley, Erik Meijer

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Exact expressions for double descent and implicit regularization via surrogate random design.

Michal Derezinski, Feynman T. Liang, Michael W. Mahoney

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Precise expressions for random projections: Low-rank approximation and randomized Newton.

Michal Derezinski, Feynman T. Liang, Zhenyu Liao, Michael W. Mahoney

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Bayesian experimental design using regularized determinantal point processes.

Michal Derezinski, Feynman T. Liang, Michael W. Mahoney

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2017

Automatic Stylistic Composition of Bach Chorales with Deep LSTM.

Feynman T. Liang, Mark Gotham, Matthew Johnson, Jamie Shotton

Proceedings of the 18th International Society for Music Information Retrieval Conference, 2017

2016

Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale.

Firas Abuzaid, Joseph K. Bradley, Feynman T. Liang, Andrew Feng, Lee Yang, Matei Zaharia, Ameet Talwalkar

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016