13 citations · 23 across the 6 of their papers we have counts for
6 papers
A Decade of Deep Learning: A Survey on The Magnificent Seven
Dilshod Azizov, Muhammad Arslan Manzoor, Velibor Bojkovic +9
Deep learning has fundamentally reshaped the landscape of artificial intelligence over the past decade, enabling remarkable achievements across diverse domains. At the heart of the…
MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media
Muhammad Arslan Manzoor, Ruihong Zeng, Dilshod Azizov +2
In the current era of rapidly growing digital data, evaluating the political bias and factuality of news outlets has become more important for seeking reliable information online.…
Improving the Expressiveness of -hop Message-Passing GNNs by Injecting Contextualized Substructure Information
Tianjun Yao, Yiongxu Wang, Kun Zhang +1
Graph neural networks (GNNs) have become the \textit{de facto} standard for representational learning in graphs, and have achieved state-of-the-art performance in many graph-relate…
Weakly Supervised Deep Hyperspherical Quantization for Image Retrieval
Jinpeng Wang, Bin Chen, Qiang Zhang +3
Deep quantization methods have shown high efficiency on large-scale image retrieval. However, current models heavily rely on ground-truth information, hindering the application of…
Spectral GNN via Two-dimensional (2-D) Graph Convolution
Guoming Li, Jian Yang, Shangsong Liang +1
Spectral Graph Neural Networks (GNNs) have achieved tremendous success in graph learning. As an essential part of spectral GNNs, spectral graph convolution extracts crucial frequen…
Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation
Jiyong Li, Dilshod Azizov, Yang Li +1
Recently, because of the high-quality representations of contrastive learning methods, rehearsal-based contrastive continual learning has been proposed to explore how to continuall…