In this contribution, we explore the possibilities of learning in large-scale, multimodal processing systems operating under real-world conditions. Using an instance of a large-sca...
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
We start by formulating the resource sharing in peer-to-peer (P2P) networks as a random-matching gift-giving game, where self-interested peers aim at maximizing their own long-ter...
Overall performance of the data mining process depends not just on the value of the induced knowledge but also on various costs of the process itself such as the cost of acquiring...
Diagnosing faults in aircraft gas turbine engines is a complex problem. It involves several tasks, including rapid and accurate interpretation of patterns in engine sensor data. W...