Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Zakria Hussain"'
Publikováno v:
Neurocomputing. 124:13-21
Representing manifolds using fewer examples has the advantages of eliminating the influence of outliers and noisy points and simultaneously accelerating the evaluation of predictors learned from the manifolds. In this paper, we give the definition of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4564ab18d2f68391c47349ecabe2e83d
https://doi.org/10.1016/j.neucom.2012.08.070
https://doi.org/10.1016/j.neucom.2012.08.070
Publikováno v:
IEEE Transactions on Information Theory. 57:5326-5341
We derive generalization error (loss) bounds for orthogonal matching pursuit algorithms, starting with kernel matching pursuit and sparse kernel principal components analysis. We propose (to the best of our knowledge) the first loss bound for kernel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2b6c66daca96080eb2397bedba2a82f
https://doi.org/10.1109/tit.2011.2158880
https://doi.org/10.1109/tit.2011.2158880
Autor:
Peter Auer, Zakria Hussain, Samuel Kaski, Arto Klami, Jussi Kujala, Jorma Laaksonen, Po Leung, Kitsuchart Pasupa, John Shawe-Taylor
Publikováno v:
Montanuniversität Leoben
This paper describes PinView, a content-based image retrieval system that exploits implicit relevance feedback collected during a search session. PinView contains several novel methods to infer the intent of the user. From relevance feedback, such as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49108e40d0663538a65441d34ddbd35c
We investigate the issue of model selection and the use of the nonconformity (strangeness) measure in batch learning. Using the nonconformity measure we propose a new training algorithm that helps avoid the need for Cross-Validation or Leave-One-Out
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e9681e2f52f86aeeb479a366ab37b75
https://doi.org/10.1016/b978-0-12-398537-8.00007-9
https://doi.org/10.1016/b978-0-12-398537-8.00007-9
Publikováno v:
BIBE
We apply Elastic-net Multiple Kernel Learning (MKL) to the MDL Drug Data Report (MDDR) database for the problem of drug screening. We show that combining a set of kernels constructed from fingerprint descriptors, can significantly improve the accurac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ac483180f21a01d721458696e4b3b21
https://doi.org/10.1109/bibe.2013.6701529
https://doi.org/10.1109/bibe.2013.6701529
Publikováno v:
ETRA
In this paper we predict the relevance of images based on a lowdimensional feature space found using several users’ eye movements. Each user is given an image-based search task, during which their eye movements are extracted using a Tobii eye track
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68c4d4f65f8b64c69f144234e54416bd
http://dl.acm.org/citation.cfm?id=1743711
http://dl.acm.org/citation.cfm?id=1743711
Publikováno v:
University of Bristol-PURE
This paper presents a study of how the Analogue to Digital Converter (ADC) sampling rate in a digital radar can be reduced-without reduction in waveform bandwidth-through the use of Compressed Sampling (CS). Real radar data is used to show that throu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbe54d54f22f0042c7baeaabab38e7b1
https://doi.org/10.1109/radar.2010.5494496
https://doi.org/10.1109/radar.2010.5494496
Autor:
David R. Hardoon, Peter Auer, Alex Po Leung, Kitsuchart Pasupa, Zakria Hussain, John Shawe-Taylor
Publikováno v:
Montanuniversität Leoben
Machine Learning and Knowledge Discovery in Databases ISBN: 9783642158797
ECML/PKDD (1)
Machine Learning and Knowledge Discovery in Databases ISBN: 9783642158797
ECML/PKDD (1)
In content-based image retrieval (CBIR) with relevance feedback we would like to retrieve relevant images based on their content features and the feedback given by users. In this paper we view CBIR as an Exploration-Exploitation problem and apply a k
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d923fdd88dc75a22fedffc675b8d25ba
Publikováno v:
Annals of Information Systems ISBN: 9781441912794
Data Mining
Data Mining
Support vector machines (SVMs) carry out binary classification by constructing a maximal margin hyperplane between the two classes of observed (training) examples and then classifying test points according to the half-spaces in which they reside (irr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac1200a1bda7f8731cb5e1be4e57e841
https://doi.org/10.1007/978-1-4419-1280-0_7
https://doi.org/10.1007/978-1-4419-1280-0_7
Autor:
John Shawe-Taylor, Zakria Hussain
Publikováno v:
Neural Information Processing ISBN: 9783540691549
ICONIP (1)
ICONIP (1)
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider a sub-optimal greedy heuristic algorithm termed the bound set coverin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a3a1ff6cb2b8e9fd7bc57f6c776c522
https://doi.org/10.1007/978-3-540-69158-7_28
https://doi.org/10.1007/978-3-540-69158-7_28