Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Richard Maclin"'
Publikováno v:
Journal of Aggression, Maltreatment & Trauma. 31:478-496
Though sexual violence is prevalent, formal reporting to police remains uncommon. Social media may provide a unique outlet for survivors of different forms of sexual violence, who might otherwise r...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb153d50e7fdcb2256dc49e3ba3d7077
https://doi.org/10.1080/10926771.2021.1912873
https://doi.org/10.1080/10926771.2021.1912873
Publikováno v:
KDD
Several prominent public health incidents that occurred at the beginning of this century due to adverse drug events (ADEs) have raised international awareness of governments and industries about pharmacovigilance (PhV), the science and activities to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e38976695c4f6ee5c51823f9914258b
https://europepmc.org/articles/PMC5945223/
https://europepmc.org/articles/PMC5945223/
Autor:
David W. Opitz, Richard Maclin
Publikováno v:
Journal of Artificial Intelligence Research. 11:169-198
An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c26e34a2490de0b87e5aa926ce86b919
https://doi.org/10.1613/jair.614
https://doi.org/10.1613/jair.614
Autor:
Richard Maclin, Jude W. Shavlik
Publikováno v:
Machine Learning. 22:251-281
Learning from reinforcements is a promising approach for creating intelligent agents. However, reinforcement learning usually requires a large number of training episodes. We present and evaluate a design that addresses this shortcoming by allowing a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce5ea2b407557d93f3ebf4b61695e0e8
https://doi.org/10.1007/bf00114730
https://doi.org/10.1007/bf00114730
Autor:
Sriraam Natarajan, Jude W. Shavlik, Trevor Walker, Gautam Kunapuli, Richard Maclin, Ciaran O'Reilly, David C. Page
Publikováno v:
Inductive Logic Programming ISBN: 9783642212949
ILP
ILP
Inductive Logic Programming (ILP) provides an effective method of learning logical theories given a set of positive examples, a set of negative examples, a corpus of background knowledge, and specification of a search space (e.g., via mode definition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dcbc09f9d9532913823d47eb1590f5c6
https://doi.org/10.1007/978-3-642-21295-6_28
https://doi.org/10.1007/978-3-642-21295-6_28
Autor:
Jude W. Shavlik, Richard Maclin
Publikováno v:
Machine Learning. 11:195-215
This article describes a connectionist method for refining algorithms represented as generalized finite-state automata. The method translates the rule-like knowledge in an automaton into a corresponding artificial neural network, and then refines the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1b932c0d3c995baa62972090a429ba9
https://doi.org/10.1007/bf00993077
https://doi.org/10.1007/bf00993077
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783642158827
ECML/PKDD (2)
ECML/PKDD (2)
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and then receive the correct label (and learn from that information). The goa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e382d14412d5f4c06864a6290e6be085
https://doi.org/10.1007/978-3-642-15883-4_10
https://doi.org/10.1007/978-3-642-15883-4_10
Publikováno v:
Advances in Machine Learning I ISBN: 9783642051760
Advances in Machine Learning I
Advances in Machine Learning I
The goal of transfer learning is to speed up learning in a new task by transferring knowledge from one or more related source tasks. We describe a transfer method in which a reinforcement learner analyzes its experience in the source task and learns
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::445e6bca1b1d93febfb5239d41bd2355
https://doi.org/10.1007/978-3-642-05177-7_7
https://doi.org/10.1007/978-3-642-05177-7_7
We propose a novel approach for incorporating prior knowledge into the perceptron. The goal is to update the hypothesis taking into account both label feedback and prior knowledge, in the form of soft polyhedral advice, so as to make increasingly acc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96dee54cee35cb50d6706e39e8211505
https://doi.org/10.1115/1.859599.paper80
https://doi.org/10.1115/1.859599.paper80
Publikováno v:
Inductive Logic Programming ISBN: 9783540784685
ILP
ILP
Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capacity to exploit the relational nature of the domain. Our algorithm, AMBIL, constru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05884dc751456d111bba142bbcc417a4
https://doi.org/10.1007/978-3-540-78469-2_27
https://doi.org/10.1007/978-3-540-78469-2_27