Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
In search for “realistic” bio-inspired computing models, we consider asynchronous spiking neural P systems, in the hope to get a class of computing devices with decidable prope...
Abstract--Digital control for embedded systems often requires low-power, hard real-time computation to satisfy high control-loop bandwidth, low latency, and low-power requirements....
Embedded computing systems are space and cost sensitive; memory is one of the most restricted resources, posing serious constraints on program size. Code compression, which is a s...
With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can ...