Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Sean P. Engelson"'
Autor:
Dana Angluin, Thomas Dean, Leslie Pack Kaelbling, Oded Maron, Evangelos Kokkevis, Kenneth Basye, Sean P. Engelson
Publikováno v:
AAAI
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exploration. In addition, robots, like people, make occasional errors in p
Autor:
Ido Dagan, Sean P. Engelson
Publikováno v:
ACL
Corpus-based methods for natural language processing often use supervised training, requiring expensive manual annotation of training corpora. This paper investigates methods for reducing annotation cost by {\it sample selection}. In this approach, d
Autor:
Sean P. Engelson, Ido Dagan
Publikováno v:
Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing ISBN: 9783540609254
Learning for Natural Language Processing
Learning for Natural Language Processing
Many corpus-based methods for natural language processing are based on supervised training, requiring expensive manual annotation of training corpora. This paper investigates reducing annotation cost by sample selection. In this approach, the learner
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87b88e8a07e5ce7c65ec613656307ec0
https://doi.org/10.1007/3-540-60925-3_50
https://doi.org/10.1007/3-540-60925-3_50
Autor:
Sean P. Engelson, Moshe Koppel
Publikováno v:
ICML
Suppose a domain expert gives us a domain theory which is meant to classify examples as positive or negative examples of some concept. Now suppose, as is often the case, that the expert specifies parts of the theory which might be in need of repair,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::404d618cb36754bcae7ddbb4eb153267
https://doi.org/10.1016/b978-1-55860-377-6.50035-9
https://doi.org/10.1016/b978-1-55860-377-6.50035-9
Autor:
Ido Dagan, Sean P. Engelson
Publikováno v:
ICML
In many real-world learning tasks, it is expensive to acquire a sufficient number of labeled examples for training. This paper proposes a general method for efficiently training probabilistic classifiers, by selecting for training only the more infor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a83462c911b8c776edcdb13e649c16c
https://doi.org/10.1016/b978-1-55860-377-6.50027-x
https://doi.org/10.1016/b978-1-55860-377-6.50027-x
Autor:
Sean P. Engelson
Publikováno v:
SPIE Proceedings.
For reliable navigation, a mobile robot needs to be able to recognize where it is in the world. We previously described an efficient and effective image-based representation of perceptual information for place recognition. Each place is associated wi
Autor:
Sean P. Engelson, Drew McDermott
Publikováno v:
SPIE Proceedings.
For reliable navigation, a mobile robot needs to be able to recognize where it is in the world. We describe an efficient and effective image-based representation of perceptual information for place recognition. Each place is associated with a set of
Conference
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Conference
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Conference
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