most citedA new selection strategy for selective cluster ensemble based on Diversity and Independency

17 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ML20163 cited

Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains

Muhammad Yousefnezhad, Daoqiang Zhang

Multivariate Pattern (MVP) classification holds enormous potential for decoding visual stimuli in the human brain by employing task-based fMRI data sets. There is a wide range of c…

stat.ML2016

WoCE: a framework for clustering ensemble by exploiting the wisdom of Crowds theory

Muhammad Yousefnezhad, Sheng-Jun Huang, Daoqiang Zhang

The Wisdom of Crowds (WOC), as a theory in the social science, gets a new paradigm in computer science. The WOC theory explains that the aggregate decision made by a group is often…

stat.ML2016

Local Discriminant Hyperalignment for multi-subject fMRI data alignment

Muhammad Yousefnezhad, Daoqiang Zhang

Multivariate Pattern (MVP) classification can map different cognitive states to the brain tasks. One of the main challenges in MVP analysis is validating the generated results acro…

stat.ML201617 cited

A new selection strategy for selective cluster ensemble based on Diversity and Independency

Muhammad Yousefnezhad, Ali Reihanian, Daoqiang Zhang +1

This research introduces a new strategy in cluster ensemble selection by using Independency and Diversity metrics. In recent years, Diversity and Quality, which are two metrics in…

stat.ML20161 cited

Decoding visual stimuli in human brain by using Anatomical Pattern Analysis on fMRI images

Muhammad Yousefnezhad, Daoqiang Zhang

A universal unanswered question in neuroscience and machine learning is whether computers can decode the patterns of the human brain. Multi-Voxels Pattern Analysis (MVPA) is a crit…