Abstract. A novel framework for the design and analysis of energy-aware algorithms is presented, centered around a deterministic Bit-level (Boltzmann) Random Access Machine or BRAM...
Abstract. We study the problem of learning partitions using equivalence constraints as input. This is a binary classification problem in the product space of pairs of datapoints. ...
Instead of relying completely on machine intelligence in anomaly event analysis and correlation, in this paper, we take one step back and investigate the possibility of a human-int...
Soon Tee Teoh, Kwan-Liu Ma, Shyhtsun Felix Wu, Dan...
Abstract. In this work we investigate several issues in order to improve the performance of probabilistic estimation trees (PETs). First, we derive a new probability smoothing that...
Abstract. Distributed heterogeneous search environments are an emerging phenomenon in Web search, in which topic-specific search engines provide search services, and metasearchers...