Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Graduates of computer science degree programs are increasingly being asked to maintain large, multi-threaded software systems; however, the maintenance of such systems is typicall...
Scott D. Fleming, Eileen Kraemer, R. E. Kurt Stire...
Dynamically discovering likely program invariants from concrete test executions has emerged as a highly promising software engineering technique. Dynamic invariant inference has t...
Christoph Csallner, Nikolai Tillmann, Yannis Smara...