In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Abstract. We present a new technique called Monotonic Partial Order Reduction (MPOR) that effectively combines dynamic partial order reduction with symbolic state space exploration...
Abstract. Dynamic Pushdown Networks (DPNs) are a model for parallel programs with (recursive) procedures and process creation. The goal of this paper is to develop generic techniqu...
This paper presents a highly efficient processor design methodology based on the LISA 2.0 language. Typically the architecture design phase is dominated by an iterative processor ...
Andreas Hoffmann, Frank Fiedler, Achim Nohl, Suren...
Estimating frequency moments and Lp distances are well studied problems in the adversarial data stream model and tight space bounds are known for these two problems. There has been...