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- Mary Inaba, Naoki Katohy, Hiroshi Imai
- 2009

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)

- Mary Inaba, Naoki Katoh, Hiroshi Imai
- Symposium on Computational Geometry
- 1994

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)

- Seongsoo Moon, Mary Inaba
- SOCS
- 2017

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)

- Seongsoo Moon, Mary Inaba
- LION
- 2016

- Kaneharu Nishino, Mary Inaba
- AAAI
- 2016

<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)

- Kenichi Koizumi, Mary Inaba, Kei Hiraki
- MEMOCODE
- 2015

- Kaneharu Nishino, Mary Inaba
- ICONIP
- 2015

- Tomohiro Sonobe, Shuya Kondoh, Mary Inaba
- SAT
- 2014

- Tomohiro Sonobe, Mary Inaba
- LION
- 2013