Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
Interpolation is an important technique in verification and static analysis of programs. In particular, interpolants extracted from proofs of various properties are used in invar...
Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
The performance of most embedded systems is critically dependent on the memory hierarchy performance. In particular, higher cache hit rate can provide significant performance boos...
Excessive power consumption is becoming a major barrier to extracting the maximum performance from high-performance parallel systems. Therefore, techniques oriented towards reduci...