Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
Since Findler and Felleisen [2002] introduced higher-order contracts, many variants have been proposed. Broadly, these fall into two groups: some follow Findler and Felleisen in u...
Benjamin C. Pierce, Michael Greenberg, Stephanie W...
The method of logical relations is a classic technique for proving the equivalence of higher-order programs that implement the same observable behavior but employ different intern...
Derek Dreyer, Georg Neis, Andreas Rossberg, Lars B...
We consider the computational complexity of pure Nash equilibria in graphical games. It is known that the problem is NP-complete in general, but tractable (i.e., in P) for special...