Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Srinivasa, Rakshith S"'
In many practical applications including remote sensing, multi-task learning, and multi-spectrum imaging, data are described as a set of matrices sharing a common column space. We consider the joint estimation of such matrices from their noisy linear
Externí odkaz:
http://arxiv.org/abs/2210.07077
Autor:
Srinivasa, Rakshith S, Qian, Cheng, Theodorou, Brandon, Spaeder, Jeffrey, Xiao, Cao, Glass, Lucas, Sun, Jimeng
The ongoing pandemic has highlighted the importance of reliable and efficient clinical trials in healthcare. Trial sites, where the trials are conducted, are chosen mainly based on feasibility in terms of medical expertise and access to a large group
Externí odkaz:
http://arxiv.org/abs/2204.06501
Tensor completion aims at imputing missing entries from a partially observed tensor. Existing tensor completion methods often assume either multi-linear or nonlinear relationships between latent components. However, real-world tensors have much more
Externí odkaz:
http://arxiv.org/abs/2202.00071
The attention mechanism has demonstrated superior performance for inference over nodes in graph neural networks (GNNs), however, they result in a high computational burden during both training and inference. We propose FastGAT, a method to make atten
Externí odkaz:
http://arxiv.org/abs/2006.08796
We consider sketched approximate matrix multiplication and ridge regression in the novel setting of localized sketching, where at any given point, only part of the data matrix is available. This corresponds to a block diagonal structure on the sketch
Externí odkaz:
http://arxiv.org/abs/2003.09097