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Hai Do-Tu

dblp:83/1679 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1978
—ORCID · none

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

Systems, architecture and hardware · 1 · 1 first-author

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 · 67% Speech recognition and synthesis · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Learning theory
classification
0.011978
Learning Algorithms for Nonparametric Solution to the Minimum Error Classification Problem · IEEE Trans. Computers 1978
Natural language and speech › Speech recognition and synthesis › acoustic model training › discriminative training
minimum classification error training
0.011978
Learning Algorithms for Nonparametric Solution to the Minimum Error Classification Problem · IEEE Trans. Computers 1978

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

window function · 0.0mean-square-error algorithm · 0.0discriminant function · 0.0
YearPublicationVenuePosition
1978 Learning Algorithms for Nonparametric Solution to the Minimum Error Classification Problem
abstract
This paper discusses the two class classification problem using discriminant function solution that minimizes the probability of classification error. Learning algorithms using window function techniques are presented. The convergence rates are estimated and a particular strategy is proposed. Within this strategy it is recommended to use a triangular window function. The proposed algorithms are tested on several artificial pattern classification problems and their efficiency is proven. A comparison with the mean-square-error algorithm is also presented.
Hai Do-Tu, Michel Installe
IEEE Trans. Computers1