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dwf machinelearning [57 articles]

Recent papers added to dwf library classified by the tag machinelearning. You can also see everyone's machinelearning.
  • Sparse Gaussian Processes using Pseudo-inputs
    Neural Information Processing Systems 18 (2005)
    by E Snelson, Z Ghahramani
    posted to approximate gaussianprocess gp machinelearning sparse by dwf on 2008-01-28 17:58:24 as *** along with 2 people vlachmore daniel51
  • The properties of high-dimensional data spaces: implications for exploring gene and protein expression data
    Nat Rev Cancer, Vol. 8, No. 1. (January 2008), pp. 37-49.
    by Robert Clarke, Habtom W Ressom, Antai Wang, Jianhua Xuan, Minetta C Liu, Edmund A Gehan, Yue Wang
    posted to machinelearning microarray by dwf on 2007-12-24 10:27:01 as ** along with 8 people and 1 group brianb jyuh tmmurali frohike cjeans nedwards shikin blackm0k Bioinformatics
  • Learning overcomplete representations.
    Neural Comput, Vol. 12, No. 2. (February 2000), pp. 337-365.
    by MS Lewicki, TJ Sejnowski
    posted to learning machinelearning neuroscience overcomplete by dwf on 2007-12-17 05:20:36 as ** along with 1 person ganeshrnaik
  • Generative models for discovering sparse distributed representations
    Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 352, No. 1358. (1997), pp. 1177-1190.
    by Hinton, Z Ghahramani
    posted to bayesian generative machinelearning neuralnetwork sparse thesis by dwf on 2007-10-19 01:10:35 as **
  • Multiscale conditional random fields for image labeling
    Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, Vol. 2 (2004), pp. II-695-II-702 Vol.2.
    by Xuming He, RS Zemel, MA Carreira-Perpinan
    posted to crf labelling machinelearning objectrecognition thesis vision by dwf on 2007-10-19 01:09:31 as ** along with 2 people assad79 zeppe
  • Discriminative training for object recognition using image patches
    Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, Vol. 2 (2005), pp. 157-162 vol. 2.
    by T Deselaers, D Keysers, H Ney
    posted to discriminative machinelearning objectrecognition patches thesis by dwf on 2007-10-19 01:08:18 as ** along with 1 person xiangang
  • notes Generative versus discriminative methods for object recognition
    Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, Vol. 2 (2005), pp. 258-265 vol. 2.
    by I Ulusoy, CM Bishop
    posted to discriminative generative machinelearning objectrecognition review thesis by dwf on 2007-10-19 01:07:24 as read
  • Automated segmentation, classification, and tracking of cancer cell nuclei in time-lapse microscopy
    Biomedical Engineering, IEEE Transactions on, Vol. 53, No. 4. (2006), pp. 762-766.
    by Xiaowei Chen, Xiaobo Zhou, STC Wong
    posted to classification machinelearning microscopy segmentation subcellular thesis timeseries tracking video vision by dwf on 2007-09-25 01:24:23 as ** along with 1 person singhsh
  • A graphical model approach to automated classification of protein subcellular location patterns in multi-cell images.
    BMC Bioinformatics, Vol. 7 (2006)
    by SC Chen, RF Murphy
    posted to classification graphicalmodels machinelearning proteinlocalization thesis by dwf on 2007-09-25 01:19:07 as ** along with 1 person jyuh
  • Objective Evaluation of Differences in Protein Subcellular Distribution
    pp. 61-65.
    by EJS Roques, RF Murphy
    posted to machinelearning proteinlocalization subcellular thesis by dwf on 2007-09-25 01:06:48 as **
  • Robust classification of subcellular location patterns in fluorescence microscope images
    Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on (2002), pp. 67-76.
    by RF Murphy, M Velliste, G Porreca
    posted to classification machinelearning microscopy proteinlocalization subcellular thesis by dwf on 2007-09-25 01:04:47 as **
  • Feature reduction for improved recognition of subcellular location patterns in fluorescence microscope images
    Manipulation and Analysis of Biomolecules, Cells, and Tissues, Vol. 4962, No. 1. (2003), pp. 307-318.
    by Kai Huang, Meel Velliste, Robert F Murphy
    edited by Dan V Nicolau, Joerg Enderlein, Robert C Leif, Daniel L Farkas
    posted to featureselection machinelearning microscopy proteinlocalization subcellular thesis by dwf on 2007-09-25 01:03:15 as **
  • Automated Recognition of Intracellular Organelles in Confocal Microscope Images
    Traffic, Vol. 3, No. 1. (2002), pp. 66-73.
    by A Danckaert, E Gonzalez-Couto, L Bollondi, N Thompson, B Hayes
    posted to machinelearning microscopy subcellular thesis by dwf on 2007-09-25 00:54:46 as **
  • Robust classification of subcellular location patterns in high resolution 3D fluorescence microscope images
    Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE, Vol. 1 (2004), pp. 1632-1635 Vol.3.
    by Xiang Chen, RF Murphy
    posted to 3d classification machinelearning microscopy proteinlocalization thesis by dwf on 2007-09-25 00:54:07 as **
  • Location proteomics: building subcellular location trees from high-resolution 3D fluorescence microscope images of randomly tagged proteins
    Manipulation and Analysis of Biomolecules, Cells, and Tissues, Vol. 4962, No. 1. (2003), pp. 298-306.
    by Xiang Chen, Meel Velliste, Shmuel Weinstein, Jonathan W Jarvik, Robert F Murphy
    edited by Dan V Nicolau, Joerg Enderlein, Robert C Leif, Daniel L Farkas
    posted to 3d machinelearning microscopy proteinlocalization thesis by dwf on 2007-09-25 00:51:05 as **
  • notes Automated recognition of patterns characteristic of subcellular structures in fluorescence microscopy images
    Cytometry, Vol. 33, No. 3. (1998), pp. 366-375.
    by Michael V Boland, Mia K Markey, Robert F Murphy
    posted to classification machinelearning microscopy subcellular thesis by dwf on 2007-09-25 00:47:48 as read
  • Classification of protein localization patterns obtained via fluorescence light microscopy
    Engineering in Medicine and Biology society, 1997. Proceedings of the 19th Annual International Conference of the IEEE, Vol. 2 (1997), pp. 594-597 vol.2.
    by MV Boland, MK Markey, RF Murphy
    posted to classifier machinelearning microscopy proteinlocalization thesis by dwf on 2007-09-25 00:28:34 as **
  • A neural network classifier capable of recognizing the patterns of all major subcellular structures in fluorescence microscope images of HeLa cells
    Bioinformatics, Vol. 17, No. 12. (1 December 2001), pp. 1213-1223.
    by Michael V Boland, Robert F Murphy
    posted to classifier machinelearning microscopy neuralnetwork subcellular thesis by dwf on 2007-09-25 00:26:55 as *** along with 1 person luispedro
  • notes Automatic identification of subcellular phenotypes on human cell arrays.
    Genome Res, Vol. 14, No. 6. (June 2004), pp. 1130-1136.
    by C Conrad, H Erfle, P Warnat, N Daigle, T Lörch, J Ellenberg, R Pepperkok, R Eils
    posted to machinelearning microscopy phenotyping thesis by dwf on 2007-09-19 01:49:26 as read
  • Automated epiluminescence microscopy--tissue counter analysis using CART and 1-NN in the diagnosis of Melanoma.
    Skin Res Technol, Vol. 9, No. 2. (May 2003), pp. 105-110.
    by A Gerger, R Pompl, J Smolle,
    posted to 1nn cart knn machinelearning microscopy thesis by dwf on 2007-09-19 01:49:04 as **
  • A multiresolution approach to automated classification of protein subcellular location images
    BMC Bioinformatics, Vol. 8 (19 June 2007), 210.
    by Amina Chebira, Yann Barbotin, Charles Jackson, Thomas Merryman, Gowri Srinivasa, Robert F Murphy, Jelena Kovacevic
    posted to machinelearning microscopy multiresolution protein thesis by dwf on 2007-09-19 01:43:01 as **
  • notes Automated interpretation of subcellular patterns from immunofluorescence microscopy.
    J Immunol Methods, Vol. 290, No. 1-2. (July 2004), pp. 93-105.
    by Y Hu, RF Murphy
    posted to machinelearning microscopy thesis by dwf on 2007-09-19 01:40:57 as read
  • notes Toward automatic phenotyping of developing embryos from videos.
    IEEE Trans Image Process, Vol. 14, No. 9. (September 2005), pp. 1360-1371.
    by F Ning, D Delhomme, Y LeCun, F Piano, L Bottou, PE Barbano
    posted to convolutional embryo machinelearning neuralnetwork thesis video by dwf on 2007-09-19 01:15:45 as read
  • notes Machine learning for detection and diagnosis of disease.
    Annu Rev Biomed Eng, Vol. 8 (2006), pp. 537-565.
    by P Sajda
    posted to diagnosis machinelearning review thesis by dwf on 2007-09-19 01:13:41 as read
  • notes Location proteomics: a systems approach to subcellular location.
    Biochem Soc Trans, Vol. 33, No. Pt 3. (June 2005), pp. 535-538.
    by RF Murphy
    posted to imaging machinelearning protein proteinlocalization thesis by dwf on 2007-09-19 01:12:04 as read
  • High-throughput analysis of multispectral images of breast cancer tissue.
    IEEE Trans Image Process, Vol. 15, No. 8. (August 2006), pp. 2259-2268.
    by U Adiga, R Malladi, R Fernandez-Gonzalez, C Ortiz de Solorzano
    posted to breastcancer highthroughput machinelearning thesis vision by dwf on 2007-09-10 20:32:24 as **
  • Prostate cancer multi-feature analysis using trans-rectal ultrasound images.
    Phys Med Biol, Vol. 50, No. 15. (7 August 2005)
    by SS Mohamed, MM Salama, M Kamel, EF El-Saadany, K Rizkalla, J Chin
    posted to featureselection machinelearning prostatecancer thesis ultrasound by dwf on 2007-09-10 20:29:52 as **
  • Coarse-to-Fine vision-based localization by indexing scale-invariant features.
    IEEE Trans Syst Man Cybern B Cybern, Vol. 36, No. 2. (April 2006), pp. 413-422.
    by J Wang, H Zha, R Cipolla
    posted to featureselection machinelearning objectrecognition scaleinvariant thesis vision by dwf on 2007-09-10 20:28:34 as **
  • Model-based automated extraction of microtubules from electron tomography volume.
    IEEE Trans Inf Technol Biomed, Vol. 10, No. 3. (July 2006), pp. 608-617.
    by M Jiang, Q Ji, BF McEwen
    posted to electrontomography machinelearning thesis by dwf on 2007-09-10 20:27:23 as **
  • Automated extraction of fine features of kinetochore microtubules and plus-ends from electron tomography volume.
    IEEE Trans Image Process, Vol. 15, No. 7. (July 2006), pp. 2035-2048.
    by M Jiang, Q Ji, BF McEwen
    posted to electrontomography featureselection machinelearning microscopy thesis by dwf on 2007-09-10 20:24:40 as **
  • Automated recognition of patterns characteristic of subcellular structures in fluorescence microscopy images.
    Cytometry, Vol. 33, No. 3. (1 November 1998), pp. 366-375.
    by MV Boland, MK Markey, RF Murphy
    posted to machinelearning microscopy thesis by dwf on 2007-09-10 20:23:30 as read
  • Kernel-based distance metric learning for microarray data classification
    BMC Bioinformatics, Vol. 7 (14 June 2006), 299.
    by Huilin Xiong, Xue-Wen Chen
    posted to classification kernel machinelearning microarray by dwf on 2007-09-10 20:22:53 as ** along with 3 people jccaicedo jfr papamicd
  • A hybrid machine-learning approach for segmentation of protein localization data.
    Bioinformatics, Vol. 21, No. 19. (1 October 2005), pp. 3778-3786.
    by PM Kasson, JB Huppa, MM Davis, AT Brunger
    posted to machinelearning microscopy proteinlocalization segmentation thesis by dwf on 2007-09-10 20:17:43 as **
  • Automated segmentation, classification, and tracking of cancer cell nuclei in time-lapse microscopy.
    IEEE Trans Biomed Eng, Vol. 53, No. 4. (April 2006), pp. 762-766.
    by X Chen, X Zhou, ST Wong
    posted to cancer classification machinelearning microscopy segmentation thesis timeseries tracking by dwf on 2007-09-10 20:16:04 as **
  • notes Context based mixture model for cell phase identification in automated fluorescence microscopy
    BMC Bioinformatics, Vol. 8 (30 January 2007), 32.
    by Meng Wang, Xiaobo Zhou, Randy W King, Stephen TC Wong
    posted to machinelearning microscopy thesis by dwf on 2007-09-10 20:08:15 as *** along with 1 person kvjanos
  • An in situ probe for on-line monitoring of cell density and viability on the basis of dark field microscopy in conjunction with image processing and supervised machine learning.
    Biotechnol Bioeng, Vol. 97, No. 6. (15 August 2007), pp. 1489-1500.
    by N Wei, J You, K Friehs, E Flaschel, TW Nattkemper
    posted to imageprocessing machinelearning microscopy supervised thesis by dwf on 2007-09-10 20:07:32 as **
  • A fast learning algorithm for deep belief nets
    Neural Computation, Vol. 18, No. 7. (1 July 2006), pp. 1527-1554.
    by Geoffrey E Hinton, Simon Osindero, Yee-Whye Teh
    posted to deepbeliefnets generative machinelearning neuralnetwork rbm supervised thesis unsupervised by dwf on 2007-09-09 22:39:59 as read along with 6 people and 1 group garyfeng Borelli haidai markcrowley marcusfrean whym ReadingLab
  • An introduction to ROC analysis
    Pattern Recognition Letters, Vol. 27, No. 8. (June 2006), pp. 861-874.
    by Tom Fawcett
    posted to classification machinelearning roc supervised by dwf on 2007-08-26 15:38:20 as read along with 21 people and 6 groups jyuh isimpson AbnerCYH ldietz vavi dquest sdvillal xiaoyan2006 camu schlauchi vmoa drivard nklee imrchen kmdaily gsiwo tgyork idonaldson napvasconcelos cdeane haiyeong Bioinformatics Crypto VT_DLRL Randomness LIVIA BergmanLab
  • Nightmare at test time: robust learning by feature deletion
    (2006), pp. 353-360.
    by Amir Globerson, Sam Roweis
    posted to featureselection machinelearning minimax regularization robustness supervised by dwf on 2007-08-03 21:14:50 as read along with 1 person sdvillal
  • notes A Unifying Review of Linear Gaussian Models
    (1997)
    by Sam Roweis, Zoubin Ghahramani
    posted to em factoranalysis gaussian lds linear machinelearning pca review tutorial unsupervised by dwf on 2007-08-03 16:56:19 as read along with 9 people and 2 groups noel wnpx tag ecome sbarthelme bamberg sugarexpletive daniel51 assad79 metric_embeddings LTN
  • Information Theory, Inference & Learning Algorithms
    (15 June 2002)
    by David JC Mackay
    posted to bayesian infotheory machinelearning theory by dwf on 2007-08-03 16:55:48 as *** along with 40 people and 5 groups luispedro matjes delip lop ekatsyrk quianominorleo markusd A_Olympia ansobol yaroslavvb JoSeK ingo jrw rpadams gyuli dariusb simonjudge leidner bayesian BarrosH wnpx filippone marcosmuller danielaugot zielaj daveh spirit_of_numenor sbarthelme anon_pl petrijooste wowbagger nrubens chrisc rsantana fishtank rwilliamson poluxmoon robertoalamino brianmc robotact Philosophy_of_Information Blog_and_Wiki_Research AssistiveTechnology inference-group ComplexAdaptiveSystems
  • An overview of statistical learning theory
    Neural Networks, IEEE Transactions on, Vol. 10, No. 5. (1999), pp. 988-999.
    by VN Vapnik
    posted to machinelearning maxmargin svm theory vapnik vc by dwf on 2007-08-03 16:55:04 as ** along with 16 people and 9 groups fredguilloux sourada A_Olympia yaroslavvb anoopsarkar gangli eme garyfeng arsyed yish sdvillal gane5h atbrew d_burfoot rsantana balduzzi Philosophy_of_Information Blog_and_Wiki_Research tulip ReadingLab astro mathgamespatterns dtl vds-arg eni
  • Reducing the Dimensionality of Data with Neural Networks
    Science, Vol. 313, No. 5786. (28 July 2006), pp. 504-507.
    by GE Hinton, RR Salakhutdinov
    posted to autoencoder deepbeliefnets dimensionalityreduction machinelearning neuralnetwork unsupervised by dwf on 2007-08-03 16:54:01 as read along with 16 people and 9 groups brian pdlug ana barry garyfeng mrkrause yama_tah neilh sdvillal jwdietrich rgb mp4man josepe marcusfrean robincha ygarb structural_bioinformatics ReadingLab MathBio Bioinformatics Cybernetics pileWorks S-Lab Biomedical_Cybernetics AQUA-FONTIS-Study
  • A theory of the learnable
    Commun. ACM, Vol. 27, No. 11. (November 1984), pp. 1134-1142.
    by LG Valiant
    posted to machinelearning theory by dwf on 2007-08-03 16:48:47 as ** along with 5 people mthomure sdvillal AbnerCYH mangesh bsilverthorn
  • Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
    (2001), pp. 282-289.
    by John Lafferty, Andrew Mccallum, Fernando Pereira
    posted to crf machinelearning sequence statistics timeseries by dwf on 2006-11-03 19:18:47 as ** along with 20 people and 4 groups idornescu jmackay davidr halacsy unnonouno balajis buescher76 wcohen sids j3xucite knmnyn student_t bundschu johnkork koji_matsuda mkolar markusd vlachmore kohei-h oyen WLV-RGCL Statistical Machine Learning oktave-labs generif_paper
  • Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods
    (1999), pp. 61-74.
    by JC Platt
    edited by A Smola, P Bartlett, B Schölkopf, D Schuurmans
    posted to logistic machinelearning probabilistic svm by dwf on 2006-08-29 23:01:24 as **** along with 1 person thorgal
  • Bayesian parameter estimation via variational methods
    Statistics and Computing, Vol. 10, No. 1. (January 2000), pp. 25-37.
    by T Jaakkola, M Jordan
    posted to bayesian machinelearning parametric variational by dwf on 2006-07-09 20:54:04 as *** along with 3 people ecome wnpx daniel51
  • Factor Graphs and the Sum-Product Algorithm
    IEEETIT: IEEE Transactions on Information Theory, Vol. 47 (2001)
    by F Kschischang, BJ Frey, HA Loeliger
    posted to factorgraphs graphicalmodels machinelearning by dwf on 2006-06-12 20:44:48 as ** along with 6 people and 2 groups jiny torch feasel rsantana markusd roys unc_cs_eve UNC-FPM
  • Approximating discrete probability distributions with dependence trees
    Information Theory, IEEE Transactions on, Vol. 14, No. 3. (1968), pp. 462-467.
    by C Chow, C Liu
    posted to graphicalmodels machinelearning trees by dwf on 2006-05-31 16:52:35 as *** along with 7 people and 1 group tkollar pcarbo bpacker pliz craigtalbert chechetka roys vision-ng
  • An empirical study of the naive Bayes classifier
    Proceedings of IJCAI-01 workshop on Empirical Methods in AI (2001), pp. 41-46.
    posted to empirical machinelearning naivebayes by dwf on 2006-05-24 16:20:52 as **
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