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Robert J. Jannarone

dblp:97/4703 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 1988
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-authorSystems, architecture and hardware · 1Software engineering, systems software and programming languages · 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.

Artificial intelligence
1 paper
Learning theory · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Integrated circuit design · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Learning theory
statistical learning theory
0.011988
Multinomial Conjunctoid Statistical Learning Machines · ISCA 1988
Integrated circuit design › VLSI design
CMOS VLSI
0.011988
Multinomial Conjunctoid Statistical Learning Machines · ISCA 1988

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

statistical decision theory · 0.0
YearPublicationVenuePosition
1988 Multinomial Conjunctoid Statistical Learning Machines
abstract
A statistical learning model called the multinomial conjunctoid is reviewed. Multinomial conjunctoids are based on a well-developed, statistical-decision-theory framework, which guarantees that conjunctoid learning will converge to optimal states over learning trials and the learning will be fast during these trials. In addition, a prototype multinomial conjunctoid module based on CMOS VLSI technology is introduced.>
Yoshiyasu Takefuji, Robert J. Jannarone, Yong B. Cho, Tatung Chen
ISCA2
1988 Conjunctoids: Statistical learning modules for binary events
Robert J. Jannarone, Kai F. Yu, Yoshiyasu Takefuji
Neural Networks1
1988 Silicon Multinomial Conjunctoid Statistical Learning Modules
Yoshiyasu Takefuji, Robert J. Jannarone, Tatung Chen, Yong B. Cho
Neural Networks2