Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
We present the MBRAM model for static evaluation of the performance of memory-bound programs. The MBRAM model predicts the actual running time of a memory-bound program directly fr...
Boolean satisfiability (SAT) is the canonical NP-complete problem that plays an important role in AI and has many practical applications in Computer Science in general. Boolean n...
Similarity search in time series databases is an important research direction. Several methods have been proposed in order to provide algorithms for efficient query processing in t...
Maria Kontaki, Apostolos Papadopoulos, Yannis Mano...
— This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...