Max-flow has been adopted for semi-supervised data modelling, yet existing algorithms
were derived only for the learning from static data. This paper proposes an online max-flow …

The max-flow problem (MFP) is one of the most explored problems in the area of
combinatorial optimization and it has a wide variety of potential applications in computer …

This paper presents an augmenting path based online max-flow algorithm. The proposed
algorithm handles graph changes in chunk manner, updating residual graph in response to …

Incremental and parallel are two capabilities for machine learning algorithms to
accommodate data from real world applications. Incremental learning addresses streaming …

In a common machine learning methods to classification, one can only make use of a
labeled set from training the classifier. The problem with the labeled instances is those can …

A congestion-aware cloud-based monitoring system is presented. The proposed system is
capable of continually accommodating its upload paths and adjusting its frame rate in …