PROJECT TITLE : Unsupervised Spectral Feature Selection with Dynamic Hyper-graph Learning ABSTRACT: In order to produce interpretable and discriminative results from unsupervised spectral feature selection (USFS) methods, an embedding
PROJECT TITLE : GloDyNE: Global Topology Preserving Dynamic Network Embedding ABSTRACT: Due to the time-evolving nature of many real-world networks, learning low-dimensional topological representations of networks in dynamic environments
PROJECT TITLE : Fully Dynamic kk-Center Clustering With Improved Memory Efficiency ABSTRACT: Any machine learning library worth its salt will include both static and dynamic clustering algorithms as core components. The sliding
PROJECT TITLE : Exploring Temporal Information for Dynamic Network Embedding ABSTRACT: The task of analyzing complex networks is a challenging one that is attracting an increasing amount of attention. One way to make the analysis
PROJECT TITLE : MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers ABSTRACT: Two of the most significant challenges for effective resource management in large-scale