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Ken'ichi Hatanaka

dblp:59/1230 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Coding theory · 30% Computational complexity · 30% Mathematical optimization · 30%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory
boolean functions
0.011999
Horn Extensions of a Partially Defined Boolean Function · SIAM J. Comput. 1999
Computational complexity › learning theory
boolean function learning
0.011999
Horn Extensions of a Partially Defined Boolean Function · SIAM J. Comput. 1999
Mathematical optimization › continuous optimization › convex optimization
membership oracle
0.011999
Horn Extensions of a Partially Defined Boolean Function · SIAM J. Comput. 1999

Methods — techniques the papers use, named apart from their topics

polynomial-time algorithm · 0.0membership oracle · 0.0
YearPublicationVenuePosition
2006 Pedestrian Recognition in Far-Infrared Images by Combining Boosting-Based Detection and Skeleton-Based Stochastic Tracking
Ryusuke Miyamoto, Hiroki Sugano, Hiroshi Tsutsui, Hiroyuki Ochi, Ken'ichi Hatanaka, Yukihiro Nakamura
PSIVT6
1999 Horn Extensions of a Partially Defined Boolean Function
abstract
Given a partially defined Boolean function (pdBf) (T,F), we investigate in thispaper how to find a Horn extension $f: \{0,1\}^n \mapsto \{0,1\}$, which is consistent with (T,F), where $T \subseteq \{0,1\}^n$ denotes a set of true Boolean vectors (or positive examples) and $F \subseteq \{0,1\}^n$ denotes a set of false Boolean vectors (or negative examples). Given a pdBf (T,F), it is known that the existence of a Horn extension can be checked in polynomial time. As there are many Horn extensions, however, we consider those extensions f which have maximal and minimal sets T(f) of the true vectors of f, respectively. For a pdBf (T,F), there always exists the unique maximal (i.e., maximum) Horn extension, but there are in general many minimal Horn extensions. We first show that a polynomial time membership oracle can be constructed for the maximum extension, even if its disjunctive normal form (DNF) can be very long. Our main contribution is to show that checking if a given Horn DNF represents a minimal extension and generating a Horn DNF of a minimal Horn extension can both be done in polynomial time. We also can check in polynomial time if a pdBf (T,F) has the unique minimal Horn extension. However, the problems of finding a Horn extension f with the smallest |T(f)| and of obtaining a Horn DNF, whose number of literals is smallest, are both NP-hard.
Kazuhisa Makino, Ken'ichi Hatanaka, Toshihide Ibaraki
SIAM J. Comput.2