5 citations · 5 across the 7 of their papers we have counts for
3 papers · 1 filter
HyperINF: Unleashing the HyperPower of the Schulz's Method for Data Influence Estimation
Xinyu Zhou, Simin Fan, Martin Jaggi
Influence functions provide a principled method to assess the contribution of individual training samples to a specific target. Yet, their high computational costs limit their appl…
XNN: Paradigm Shift in Mitigating Identity Leakage within Cloud-Enabled Deep Learning
Kaixin Liu, Huixin Xiong, Bingyu Duan +4
In the domain of cloud-based deep learning, the imperative for external computational resources coexists with acute privacy concerns, particularly identity leakage. To address this…
LoGAH: Predicting 774-Million-Parameter Transformers using Graph HyperNetworks with 1/100 Parameters
Xinyu Zhou, Boris Knyazev, Alexia Jolicoeur-Martineau +1
A good initialization of deep learning models is essential since it can help them converge better and faster. However, pretraining large models is unaffordable for many researchers…