14.5.1 Learning, General Non-Vision Learning Issues

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Learning. Some papers included because they are part of larger collections, most are not computer vision related, or even computer learning. BibRef 7700

Grim, J.[Jirí], Somol, P.[Petr], Pudil, P.[Pavel],
Probabilistic neural network playing and learning Tic-Tac-Toe,
PRL(26), No. 12, September 2005, pp. 1866-1873.
Elsevier DOI 0508
BibRef

Xing, X.L.[Xiang-Lei], Wang, K.[Kejun], Lv, Z.W.[Zhuo-Wen], Zhou, Y.[Yu], Du, S.[Sidan],
Fusion of Local Manifold Learning Methods,
SPLetters(22), No. 4, April 2015, pp. 395-399.
IEEE DOI 1411
learning (artificial intelligence) BibRef

Yukawa, M., Müller, K.R.,
Why Does a Hilbertian Metric Work Efficiently in Online Learning With Kernels?,
SPLetters(23), No. 10, October 2016, pp. 1424-1428.
IEEE DOI 1610
Hilbert spaces BibRef

Zhang, Y.S.[Yong-Shan], Wu, J.[Jia], Zhou, C.[Chuan], Cai, Z.H.[Zhi-Hua],
Instance cloned extreme learning machine,
PR(68), No. 1, 2017, pp. 52-65.
Elsevier DOI 1704
Extreme Learning Machine BibRef

Cao, X., Liu, K.J.R.,
A Graphical Evolutionary Game Approach to Social Learning,
SPLetters(24), No. 6, June 2017, pp. 765-769.
IEEE DOI 1705
behavioural sciences, game theory, graph theory, benchmark centralized detector, communication complexity, game-theoretic learning method, graphical evolutionary game approach, mean field approximations, networked system, novel distributed graphical evolutionary game-theoretic learning method, private signals, social learning, Detectors, Game theory, Games, Learning systems, Sociology, Statistics, Steady-state, Distributed decision making, distributed detection, evolutionary game theory, social, learning BibRef


Sun, J.[Jimeng], Sow, D.[Daby], Hu, J.Y.[Jian-Ying], Ebadollahi, S.[Shahram],
Localized Supervised Metric Learning on Temporal Physiological Data,
ICPR10(4149-4152).
IEEE DOI 1008
BibRef

Fausser, S.[Stefan], Schwenker, F.[Friedhelm],
Learning a Strategy with Neural Approximated Temporal-Difference Methods in English Draughts,
ICPR10(2925-2928).
IEEE DOI 1008
Game BibRef

Joko, M.[Masao], Kawahara, Y.[Yoshinobu], Yairi, T.[Takehisa],
Learning Non-linear Dynamical Systems by Alignment of Local Linear Models,
ICPR10(1084-1087).
IEEE DOI 1008
BibRef

Shamili, A.S.[Ashkan Sharifi], Bauckhage, C.[Christian], Alpcan, T.[Tansu],
Malware Detection on Mobile Devices Using Distributed Machine Learning,
ICPR10(4348-4351).
IEEE DOI 1008
BibRef

Khalili, A.H.[Amir Hossein], Wu, C.[Chen], Aghajan, H.[Hamid],
Hierarchical preference learning for light control from user feedback,
CVPR4HB10(56-62).
IEEE DOI 1006
BibRef

Masri, M.[Mazyrah], Ahmad, W.F.B.W.[Wan Fatimah Bt Wan], Nordin, S.M.[Shahrina M.], Sulaiman, S.[Suziah],
The Effect of Visual of a Courseware towards Pre-University Students' Learning in Literature,
IVIC09(822-831).
Springer DOI 0911
BibRef

Shafie, A.B.[Afza Bt], Janier, J.B.[Josefina Barnachea], Ahmad, W.F.B.W.[Wan Fatimah Bt Wan],
Visual Learning in Application of Integration,
IVIC09(832-843).
Springer DOI 0911
BibRef

Zainuddin, N.M.M.[Norziha Megat Mohammed], Zaman, H.B.[Halimah Badioze], Ahmad, A.[Azlina],
Learning Science Using AR Book: A Preliminary Study on Visual Needs of Deaf Learners,
IVIC09(844-855).
Springer DOI 0911
BibRef

Cardellach, E., Oliveras, S., Rius, A.,
GNSS Signal Interference Classified by Means of a Supervised Learning Method Applied in the Time-Frequency Domain,
CISP09(1-5).
IEEE DOI 0910
Global Navigation Satellite System. BibRef

Liu, H.Y.[Hong-Yu], Liu, X.F.[Xiao-Feng],
Adaptive Piecewise Linear Predistorter Based on PSO and Indirect Learning Architecture,
CISP09(1-3).
IEEE DOI 0910
BibRef

Ning, H.Z.[Hua-Zhong], Xu, W.[Wei], Zhou, Y.[Yue], Gong, Y.H.[Yi-Hong], Huang, T.S.[Thomas S.],
Temporal difference learning to detect unsafe system states,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Murthy, C.A., Das, M.[Mouli], De, R.K.[Rajat K.], Mukhopadhyay, S.[Subhasis],
Determination of optimal metabolic pathways through a new learning algorithm,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Learning, General Surveys, Overviews .


Last update:Nov 17, 2018 at 09:12:27