48 citations · 52 across the 7 of their papers we have counts for
6 papers · 1 filter
ORDSIM: Ordinal Regression for E-Commerce Query Similarity Prediction
Md. Ahsanul Kabir, Mohammad Al Hasan, Aritra Mandal +2
Query similarity prediction task is generally solved by regression based models with square loss. Such a model is agnostic of absolute similarity values and it penalizes the regres…
Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision
Jun Zhuang, Mohammad Al Hasan
In recent years, plentiful evidence illustrates that Graph Convolutional Networks (GCNs) achieve extraordinary accomplishments on the node classification task. However, GCNs may be…
Non-Exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks
Jun Zhuang, Mohammad Al Hasan
Supervised learning, while deployed in real-life scenarios, often encounters instances of unknown classes. Conventional algorithms for training a supervised learning model do not p…
Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding
Vachik S. Dave, Baichuan Zhang, Pin-Yu Chen +1
Network embedding methodologies, which learn a distributed vector representation for each vertex in a network, have attracted considerable interest in recent years. Existing works…
Incremental Eigenpair Computation for Graph Laplacian Matrices: Theory and Applications
Pin-Yu Chen, Baichuan Zhang, Mohammad Al Hasan
The smallest eigenvalues and the associated eigenvectors (i.e., eigenpairs) of a graph Laplacian matrix have been widely used in spectral clustering and community detection. Howeve…
Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs
Baichuan Zhang, Sutanay Choudhury, Mohammad Al Hasan +4
Link prediction, or predicting the likelihood of a link in a knowledge graph based on its existing state is a key research task. It differs from a traditional link prediction task…