We present a design style and synthesis algorithm that encompasses both asynchronous and synchronous state machines. Our proposed design style not only supports generalized “bur...
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
Many real-world data mining tasks require the achievement of two distinct goals when applied to unseen data: first, to induce an accurate preference ranking, and second to give g...
Language comprehension in humans is significantly constrained by memory, yet rapid, highly incremental, and capable of utilizing a wide range of contextual information to resolve ...
Roger P. Levy, Florencia Reali, Thomas L. Griffith...
Random problem distributions have played a key role in the study and design of algorithms for constraint satisfaction and Boolean satisfiability, as well as in our understanding o...