53 citations · 303 across the 27 of their papers we have counts for
6 papers · 1 filter
AdaptCL: Adaptive Continual Learning for Tackling Heterogeneity in Sequential Datasets
Yuqing Zhao, Divya Saxena, Jiannong Cao
Managing heterogeneous datasets that vary in complexity, size, and similarity in continual learning presents a significant challenge. Task-agnostic continual learning is necessary…
Time-aware Dynamic Graph Embedding for Asynchronous Structural Evolution
Yu Yang, Hongzhi Yin, Jiannong Cao +4
Dynamic graphs refer to graphs whose structure dynamically changes over time. Despite the benefits of learning vertex representations (i.e., embeddings) for dynamic graphs, existin…
Time Series Clustering for Human Behavior Pattern Mining
Rohan Kabra, Divya Saxena, Dhaval Patel +1
Human behavior modeling deals with learning and understanding behavior patterns inherent in humans' daily routines. Existing pattern mining techniques either assume human dynamics…
Generative Adversarial Networks (GANs Survey): Challenges, Solutions, and Future Directions
Divya Saxena, Jiannong Cao
Generative Adversarial Networks (GANs) is a novel class of deep generative models which has recently gained significant attention. GANs learns complex and high-dimensional distribu…
D-GAN: Deep Generative Adversarial Nets for Spatio-Temporal Prediction
Divya Saxena, Jiannong Cao
Spatio-temporal (ST) data for urban applications, such as taxi demand, traffic flow, regional rainfall is inherently stochastic and unpredictable. Recently, deep learning based ST…
Deep Learning for Spatio-Temporal Data Mining: A Survey
Senzhang Wang, Jiannong Cao, Philip S. Yu
With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly av…