activity
20162019
most citedKernel Method for Detecting Higher Order Interactions in multi-view Data: An Application to Imaging, Genetics, and Epigenetics

2 citations · 2 across the 3 of their papers we have counts for

collaborators

6 papers

q-bio.NC2019

Brain Maturation Study during Adolescence Using Graph Laplacian Learning Based Fourier Transform

Junqi Wang, Li Xiao, Tony W. Wilson +3

Objective: Longitudinal neuroimaging studies have demonstrated that adolescence is the crucial developmental epoch of continued brain growth and change. A large number of researche…

stat.ML20172 cited

Kernel Method for Detecting Higher Order Interactions in multi-view Data: An Application to Imaging, Genetics, and Epigenetics

Md. Ashad Alam, Hui-Yi Lin, Vince Calhoun +1

In this study, we tested the interaction effect of multimodal datasets using a novel method called the kernel method for detecting higher order interactions among biologically rele…

stat.ML2017

Influence Function and Robust Variant of Kernel Canonical Correlation Analysis

Md. Ashad Alam, Kenji Fukumizu, Yu-Ping Wang

Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CC…

stat.ML2016

Gene-Gene association for Imaging Genetics Data using Robust Kernel Canonical Correlation Analysis

Md ashad Alam, Osamu Komori, Yu-Ping Wang

In genome-wide interaction studies, to detect gene-gene interactions, most methods are divided into two folds: single nucleotide polymorphisms (SNP) based and gene-based methods. B…

stat.ML2016

Identifying Outliers using Influence Function of Multiple Kernel Canonical Correlation Analysis

Md Ashad Alam, Yu-Ping Wang

Imaging genetic research has essentially focused on discovering unique and co-association effects, but typically ignoring to identify outliers or atypical objects in genetic as wel…

stat.ML2016

Robust Kernel (Cross-) Covariance Operators in Reproducing Kernel Hilbert Space toward Kernel Methods

Md. Ashad Alam, Kenji Fukumizu, Yu-Ping Wang

To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depe…