15 citations · 48 across the 14 of their papers we have counts for
16 papers
Multi-Objective Aligned Small Language Model Framework for SUD Patient Dialogue Generation
Thushara Manjari Naduvilakandy, Hyeju Jang, Mohammad Al Hasan
Substance Use Disorder (SUD) counseling requires patient responses that reflect underlying cognitive states such as beliefs, coping strategies, and readiness for change. Although l…
SLT: Robust Quantum Neural Networks for Noisy-Label Medical Image Classification via Supermartingale-based Label Transition
Jun Zhuang, Mohammad Al Hasan, Yiyu Shi +1
Noisy-label learning in small-scale medical image classification is challenging and hinders the superiority of deep neural networks. Recent studies suggest that quantum neural netw…
Supervised Link Prediction in Co-Authorship Networks Based on Author Node-Based Features
Doaa Hassan, Mohammad Al Hasan
Predicting the emergence of future research collaborations between authors in academic social networks (SNs) is a very effective example that demonstrates the link prediction probl…
Binder: Hierarchical Concept Representation through Order Embedding of Binary Vectors
Croix Gyurek, Niloy Talukder, Mohammad Al Hasan
For natural language understanding and generation, embedding concepts using an order-based representation is an essential task. Unlike traditional point vector based representation…
Robust Node Representation Learning via Graph Variational Diffusion Networks
Jun Zhuang, Mohammad Al Hasan
Node representation learning by using Graph Neural Networks (GNNs) has been widely explored. However, in recent years, compelling evidence has revealed that GNN-based node represen…
Force-directed graph embedding with hops distance
Hamidreza Lotfalizadeh, Mohammad Al Hasan
Graph embedding has become an increasingly important technique for analyzing graph-structured data. By representing nodes in a graph as vectors in a low-dimensional space, graph em…
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation
Jun Zhuang, Mohammad Al Hasan
Node classification using Graph Neural Networks (GNNs) has been widely applied in various real-world scenarios. However, in recent years, compelling evidence emerges that the perfo…
Informative Causality Extraction from Medical Literature via Dependency-tree based Patterns
Md. Ahsanul Kabir, AlJohara Almulhim, Xiao Luo +1
Extracting cause-effect entities from medical literature is an important task in medical information retrieval. A solution for solving this task can be used for compilation of vari…
Deperturbation of Online Social Networks via Bayesian Label Transition
Jun Zhuang, Mohammad Al Hasan
Online social networks (OSNs) classify users into different categories based on their online activities and interests, a task which is referred as a node classification task. Such…
Redditors in Recovery: Text Mining Reddit to Investigate Transitions into Drug Addiction
John Lu, Sumati Sridhar, Ritika Pandey +2
Increasing rates of opioid drug abuse and heightened prevalence of online support communities underscore the necessity of employing data mining techniques to better understand drug…
Name Disambiguation in Anonymized Graphs using Network Embedding
Baichuan Zhang, Mohammad Al Hasan
In real-world, our DNA is unique but many people share names. This phenomenon often causes erroneous aggregation of documents of multiple persons who are namesake of one another. S…
Bayesian Non-Exhaustive Classification A Case Study: Online Name Disambiguation using Temporal Record Streams
Baichuan Zhang, Murat Dundar, Mohammad Al Hasan
The name entity disambiguation task aims to partition the records of multiple real-life persons so that each partition contains records pertaining to a unique person. Most of the e…
TopCom: Index for Shortest Distance Query in Directed Graph
Vachik S. Dave, Mohammad Al Hasan
Finding shortest distance between two vertices in a graph is an important problem due to its numerous applications in diverse domains, including geo-spatial databases, social netwo…
Incremental Method for Spectral Clustering of Increasing Orders
Pin-Yu Chen, Baichuan Zhang, Mohammad Al Hasan +1
The smallest eigenvalues and the associated eigenvectors (i.e., eigenpairs) of a graph Laplacian matrix have been widely used for spectral clustering and community detection. Howev…
Feature Selection for Classification under Anonymity Constraint
Baichuan Zhang, Noman Mohammed, Vachik Dave +1
Over the last decade, proliferation of various online platforms and their increasing adoption by billions of users have heightened the privacy risk of a user enormously. In fact, s…
MIRAGE: An Iterative MapReduce based FrequentSubgraph Mining Algorithm
Mansurul A Bhuiyan, Mohammad Al Hasan
Frequent subgraph mining (FSM) is an important task for exploratory data analysis on graph data. Over the years, many algorithms have been proposed to solve this task. These algori…