—In the crash-recovery failure model of asynchronous distributed systems, processes can temporarily stop to execute steps and later restart their computation from a predefined l...
Felix C. Freiling, Christian Lambertz, Mila E. Maj...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Data coming from complex simulation models reach easily dimensions much greater than available computational resources. Visualization of such data still represents the most intuit...
We aim to make sense of a perplexing human experience (fun) as it occurs in a recently discovered place for sociotechnical study (the home). Our toolkit includes technology probes...
Sonja Pedell, Tim Miller, Frank Vetere, Leon Sterl...
This paper approaches statistical optimization by examining gate delay variation models and optimization objectives. Most previous work on statistical optimization has focused exc...
Matthew R. Guthaus, Natesan Venkateswaran, Vladimi...