In iterative learning control schemes for linear discrete time systems, conditions to guarantee the monotonic convergence of the tracking9 error norms are derived. By using the Ma...
Let f be a function on Rd that is monotonic in every variable. There are 2d possible assignments to the directions of monotonicity (two per variable). We provide sufficient condit...
We prove that monotone circuits computing the perfect matching function on n-vertex graphs require (n) depth. This implies an exponential gap between the depth of monotone and non...
In this paper we analyze the PAC learning abilities of several simple iterative algorithms for learning linear threshold functions, obtaining both positive and negative results. W...