Md. Ashad Alam

According to our database, Md. Ashad Alam authored at least 19 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

RoBERTa-BiLSTM: A Context-Aware Hybrid Model for Sentiment Analysis.

Md. Mostafizer Rahman, Ariful Islam Shiplu, Yutaka Watanobe, Md. Ashad Alam

CoRR, 2024

2022

Weighted Scaling Approach for Metabolomics Data Analysis.

Biplab Biswas, Nishith Kumar, Md. Aminul Hoque, Md. Ashad Alam

CoRR, 2022

A robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery.

Md. Ashad Alam, Hui Shen, Hong-Wen Deng

CoRR, 2022

2021

IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations.

Md. Mehedi Hasan, Md. Ashad Alam, Watshara Shoombuatong, Hiroyuki Kurata

J. Comput. Aided Mol. Des., 2021

A generalized kernel machine approach to identify higher-order composite effects in multi-view datasets, with application to adolescent brain development and osteoporosis.

Md. Ashad Alam, Chuan Qiu, Hui Shen, Yu-Ping Wang, Hong-Wen Deng

J. Biomed. Informatics, 2021

NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning.

Md. Mehedi Hasan, Md. Ashad Alam, Watshara Shoombuatong, Hong-Wen Deng, Balachandran Manavalan, Hiroyuki Kurata

Briefings Bioinform., 2021

2020

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

Md. Ashad Alam, Chuan Qiu, Hui Shen, Yu-Ping Wang, Hong-Wen Deng

CoRR, 2020

2019

Robust kernel canonical correlation analysis to detect gene-gene co-associations: A case study in genetics.

Md. Ashad Alam, Osamu Komori, Hong-Wen Deng, Vince D. Calhoun, Yu-Ping Wang

J. Bioinform. Comput. Biol., 2019

2018

Influence function and robust variant of kernel canonical correlation analysis.

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

Neurocomputing, 2018

Identifying outliers using multiple kernel canonical correlation analysis with application to imaging genetics.

Md. Ashad Alam, Vince D. Calhoun, Yu-Ping Wang

Comput. Stat. Data Anal., 2018

Ecological Data Analysis Based on Machine Learning Algorithms.

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

CoRR, 2018

Gene Shaving using influence function of a kernel method.

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

CoRR, 2018

2016

Learning schizophrenia imaging genetics data via Multiple Kernel Canonical Correlation Analysis.

Owen Richfield, Md. Ashad Alam, Vince D. Calhoun, Yu-Ping Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

Robust Kernel Canonical Correlation Analysis to Detect Gene-Gene Interaction for Imaging Genetics Data.

Md. Ashad Alam, Osamu Komori, Vince D. Calhoun, Yu-Ping Wang

Proceedings of the 7th ACM International Conference on Bioinformatics, 2016

Influence Function of Multiple Kernel Canonical Analysis to Identify Outliers in Imaging Genetics Data.

Md. Ashad Alam, Vince D. Calhoun, Yu-Ping Wang

Proceedings of the 7th ACM International Conference on Bioinformatics, 2016

2015

Higher-Order Regularized Kernel Canonical Correlation Analysis.

Md. Ashad Alam, Kenji Fukumizu

Int. J. Pattern Recognit. Artif. Intell., 2015

2014

Hyperparameter Selection in Kernel Principal Component Analysis.

Md. Ashad Alam, Kenji Fukumizu

J. Comput. Sci., 2014

2013

Higher-Order Regularized Kernel CCA.

Md. Ashad Alam, Kenji Fukumizu

Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

2010

A Comparative Study of Kernel and Robust Canonical Correlation Analysis.

Md. Ashad Alam, Mohammed Nasser, Kenji Fukumizu

J. Multim., 2010