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In this paper we consider the k-clustering problem for a set S of n points p i = (x i) in the d-dimensional space with variance-based errors as clustering criteria, motivated from the color quantization problem of computing a color lookup table for frame buuer display. As the inter-cluster criterion to minimize, the sum of intra-cluster errors over every(More)
In this paper we consider the<italic>k</italic>-clustering problem for a set <italic>S</italic> of <italic>n</italic> points <inline-equation><f><inf>i</inf>=<fen lp="par"><b>x<inf>i</inf></b><rp post="par"> </fen></f> </inline-equation> in the<italic>d</italic>-dimensional space with variance-based errors as clustering criteria, motivated from the color(More)
Most state-of-the-art satisfiability (SAT) solvers are capable of solving large application instances with efficient branching heuristics. The VSIDS heuristic is widely used because of its robustness. This paper focuses on the inherent ties in VSIDS and proposes a new branching heuristic called TBVSIDS, which attempts to break the ties with the(More)
<lb>Hybrid mathematical principles were introduced to large-scale electronic structure theories and<lb>realized one-hundred-million atom (100-nm-scale) calculations on the K computer. Novel<lb>linear-algebraic theories were constructed as Krylov-subspace solvers for generalized shifted<lb>linear equations ((zS-H)x=b) and were implemented in our order-N(More)