Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Asela Gunawardana"'
Autor:
Guy Shani, Asela Gunawardana
Publikováno v:
AI Communications. 26:225-236
Recommendation systems are now widely used in many commercial applications. This tutorial focuses on the evaluation of such systems, from an application-oriented view. The tutorial recommends best practices, suggests a protocol for the evaluation pro
Publikováno v:
Intelligent Data Analysis. 15:483-501
Segmentation, the task of splitting a long sequence of symbols into chunks, can provide important information about the nature of the sequence that is understandable to humans. We focus on unsupervised segmentation, where the algorithm never sees exa
Autor:
Asela Gunawardana, Guy Shani
Publikováno v:
Recommender Systems Handbook ISBN: 9781489976369
Recommender Systems Handbook
Recommender Systems Handbook
Recommender systems are now popular both commercially and in the research community, where many approaches have been suggested for providing recommendations. In many cases a system designer that wishes to employ a recommendater system must choose bet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80f24652eba1746afc7c14f33f72264c
https://doi.org/10.1007/978-1-4899-7637-6_8
https://doi.org/10.1007/978-1-4899-7637-6_8
Publikováno v:
SLT
Traditional spoken dialog systems are usually based on a centralized architecture, in which the number of domains is predefined, and the provider is fixed for a given domain and intent. The spoken language understanding (SLU) component is responsible
Autor:
Asela Gunawardana, William Byrne
Publikováno v:
William Byrne
The widely used maximum likelihood linear regression speaker adaptation procedure suffers from overtraining when used for rapid adaptation tasks in which the amount of adaptation data is severely limited. This is a well known difficulty associated wi
Autor:
Asela Gunawardana, William Byrne
Publikováno v:
IEEE Transactions on Speech and Audio Processing. 8:751-754
The paper entitled "Efficient training algorithms for HMMs using incremental estimation" by Gotoh et al. (IEEE Trans. Speech Audio Processing, vol.6, p.539-48, Nov. 1998) investigated expectation maximization (EM) procedures that increase training sp
Publikováno v:
Recommender Systems Handbook ISBN: 9781071621967
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91083059288ed8f2e8f0f83b4a0f57b7
https://doi.org/10.1007/978-1-0716-2197-4_15
https://doi.org/10.1007/978-1-0716-2197-4_15
Autor:
Andrew Dougherty, Asela Gunawardana
Publikováno v:
Physical Review E. 50:1349-1352
The mean shape of free dendrites of pivalic acid growing from solution is determined. For a three-dimensional axisymmetric needle crystal, the mean width w\ifmmode\bar\else\textasciimacron\fi{} of the dendrites would scale with distance z from the ti
Publikováno v:
ASRU
We address the memory problem of maximum entropy language models(MELM) with very large feature sets. Randomized techniques are employed to remove all large, exact data structures in MELM implementations. To avoid the dictionary structure that maps ea
Autor:
Asela Gunawardana, Guy Shani
Publikováno v:
Recommender Systems Handbook ISBN: 9780387858197
Recommender Systems Handbook
Recommender Systems Handbook
Recommender systems are now popular both commercially and in the research community, where many approaches have been suggested for providing recommendations. In many cases a system designer that wishes to employ a recommendation system must choose be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::062cc667345a3f0646e8f82624266d75
https://doi.org/10.1007/978-0-387-85820-3_8
https://doi.org/10.1007/978-0-387-85820-3_8