activity
20162022
most citedA robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery

4 citations · 7 across the 5 of their papers we have counts for

collaborators

7 papers

stat.ML2020

A generalized kernel machine approach to identify higher-order composite effects in multi-view datasets

Md Ashad Alam, Chuan Qiu, Hui Shen +2

In recent years, a comprehensive study of multi-view datasets (e.g., multi-omics and imaging scans) has been a focus and forefront in biomedical research. State-of-the-art biomedic…

stat.ML20181 cited

Ecological Data Analysis Based on Machine Learning Algorithms

Md. Siraj-Ud-Doula, Md. Ashad Alam

Classification is an important supervised machine learning method, which is necessary and challenging issue for ecological research. It offers a way to classify a dataset into subs…

stat.ML2018

Gene Shaving using influence function of a kernel method

Md. Ashad Alam, Mohammad Shahjama, Md. Ferdush Rahman

Identifying significant subsets of the genes, gene shaving is an essential and challenging issue for biomedical research for a huge number of genes and the complex nature of biolog…

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…