levels of abstraction. Lacking well-established technologies and models for representing and accessing program dynamics, tools must use ad-hoc mechanisms. This limits reuse and int...
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
A high-level understanding of how an application executes and which performance characteristics it exhibits is essential in many areas of high performance computing, such as applic...
Distributed-system observation tools require an efficient data structure to store and query the partial-order of execution. Such data structures typically use vector timestamps to...
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...