Philip Greengard

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 16

Top Topics

Data Summarization

Expectation Propagation

Matrix Decomposition

Top Venues

Adv. Comput. Math.

Publications

Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim
LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. ICLR (2024)
Dan Biderman, Jose Javier Gonzalez Ortiz, Jacob Portes, Mansheej Paul, Philip Greengard, Connor Jennings, Daniel King, Sam Havens, Vitaliy Chiley, Jonathan Frankle, Cody Blakeney, John P. Cunningham
LoRA Learns Less and Forgets Less. CoRR (2024)
Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky, Rogério Feris, David Daniel Cox, Zhangyang Wang, Yoon Kim
Learning to Grow Pretrained Models for Efficient Transformer Training. CoRR (2023)
Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. ICLR (2023)
Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky, Rogério Feris, David Daniel Cox, Zhangyang Wang, Yoon Kim
Learning to Grow Pretrained Models for Efficient Transformer Training. ICLR (2023)
Alex H. Barnett, Philip Greengard, Manas Rachh
Uniform approximation of common Gaussian process kernels using equispaced Fourier grids. CoRR (2023)
Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. CoRR (2023)
Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim
LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. CoRR (2023)
Philip Greengard, Manas Rachh, Alex H. Barnett
Equispaced Fourier representations for efficient Gaussian process regression from a billion data points. CoRR (2022)
Philip Greengard, Michael O'Neil
Efficient reduced-rank methods for Gaussian processes with eigenfunction expansions. Stat. Comput. 32 (5) (2022)
Philip Greengard, Andrew Gelman, Aki Vehtari
A fast regression via SVD and marginalization. Comput. Stat. 37 (2) (2022)
Philip Greengard, Jeremy G. Hoskins, Nicholas F. Marshall, Amit Singer
On a linearization of quadratic Wasserstein distance. CoRR (2022)
Philip Greengard, Michael O'Neil
Efficient reduced-rank methods for Gaussian processes with eigenfunction expansions. CoRR (2021)
Philip Greengard
Efficient Fourier representations of families of Gaussian processes. CoRR (2021)
Philip Greengard, Andrew Gelman, Aki Vehtari
A Fast Linear Regression via SVD and Marginalization. CoRR (2020)
Philip Greengard, Vladimir Rokhlin
An algorithm for the evaluation of the incomplete gamma function. Adv. Comput. Math. 45 (1) (2019)