Tag machine-learning [at least 200 articles] Export

Recent papers classified by the tag machine-learning.

	Top 10 algorithms in data mining [My Copy] Knowledge and Information Systems, Vol. 14, No. 1. (20 January 2008), pp. 1-37. by Xindong Wu, Vipin Kumar, Ross, et al.Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey Mclachlan, Angus Ng, Bing Liu, Philip Yu, Zhi-Hua Zhou, Michael Steinbach, David Hand, Dan Steinberg posted to review machine-learning by singhsh on 2009-11-22 03:43:07 as along with 17 people mzabidi pprett karipuf guhjy aviad_work rsantana yuju imrchen EmreSevinc votis haiyeong dquercia pmendes udamahan akastrin Mohan-S eddymier
	Learning sparse metrics via linear programming [My Copy] In KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006), pp. 367-373. by Rómer Rosales, Glenn Fung posted to machine-learning by stharward on 2009-11-19 22:19:05 as along with 1 person sdvillal
	Toward Integrating Feature Selection Algorithms for Classification and Clustering [My Copy] IEEE Transactions on Knowledge and Data Engineering, Vol. 17, No. 4. (April 2005), pp. 491-502. by Huan Liu, Lei Yu posted to machine-learning feature-selection cluster-analysis by stharward on 2009-11-19 21:43:32 as along with 6 people Jaldert sona sdvillal javo_eupla amargoli zhengzhong
	Novel Unsupervised Feature Filtering of Biological Data [My Copy] Bioinformatics, Vol. 22, No. 14. (15 July 2006), pp. e507-513. by Roy Varshavsky, Assaf Gottlieb, Michal Linial, David Horn posted to machine-learning feature-selection by stharward on 2009-11-19 21:41:10 as along with 3 people VGreiff bertelsen jfr
	HHsvm: fast and accurate classification of profile-profile matches identified by HHsearch [My Copy] Bioinformatics, Vol. 25, No. 23. (1 December 2009), pp. 3071-3076. by Mensur Dlakic posted to svm pssm machine-learning by kshameer on 2009-11-18 04:03:18 as along with 1 person and 1 group ppgardne Journal picks
	SVMotif: A Machine Learning Motif Algorithm [My Copy] Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on (15 December 2007), pp. 573-580. by M. Kon, Yue Fan, D. Holloway, C. DeLisi posted to suport_vector_machine motif machine-learning by Dulce on 2009-11-17 10:06:12 as
	Programming Collective Intelligence: Building Smart Web 2.0 Applications [My Copy] (16 August 2007) by Toby Segaran posted to machine-learning ai by longtop on 2009-11-13 00:43:13 as along with 23 people and 3 groups mxro Gargunzola pezi pacianca3 thegoose2 ilyashl mboehmer Adso mikejedw fmatthes germoglio pprett ianturton tdrycker G-J gunv koles mircea dquercia sjc fly51fly tharris pthimon Information Integration Architecture FebraceV Catalysts Bookshelf
	Improved base calling for the Illumina Genome Analyzer using machine learning strategies [My Copy] Genome Biology, Vol. 10, No. 8. (14 August 2009), R83. by Martin Kircher, Udo Stenzel, Janet Kelso posted to machine-learning illumina by seb1 on 2009-11-12 21:09:04 as along with 7 people and 1 group djkt reyez fpattyn danmaclean ppgardne n00c druvus Journal picks
	Handwritten digit recognition: benchmarking of state-of-the-art techniques [My Copy] Pattern Recognition, Vol. 36, No. 10. (October 2003), pp. 2271-2285. by C. Liu posted to machine-learning by pingmei on 2009-11-12 04:44:44 as along with 2 people yaroslavvb jdu
	Pattern Recognition and Machine Learning (Information Science and Statistics) [My Copy] (01 October 2007) by Christopher M. Bishop posted to machine-learning by pingmei on 2009-11-11 22:21:23 as along with 53 people and 6 groups pjmaybank emailhy bklynbam gavin1332 ecome psychorav mircea longtop resilla bertelsen ocs sugarexpletive bgibson tkf mthomure emre haiyeong h-chi brian sbarthelme bayes mboehmer paulclinger thefillm stibor ppeeling yaroslavvb sdvillal nojhan gkvas paulinus ajylha helsley hawkes zeppe poluxmoon librain kohei-h brianmc napvasconcelos teesid robotact Hoertnagl matjes eddymier delip markusd filippone singhsh ssomani pprett rwilliamson Dukhat Tracking Methods EvolutionaryComputation Metaheuristics Optimization contact-id MuSAMA
	Nonlinear Dimensionality Reduction by Locally Linear Embedding [My Copy] Science, Vol. 290, No. 5500. (22 December 2000), pp. 2323-2326. by Sam T. Roweis, Lawrence K. Saul posted to machine-learning ma by pingmei on 2009-11-11 22:10:57 as along with 35 people and 4 groups Cavadini akuhn singhsh caicai tfx klmoravec jzujovic rramirezp Scis0000002 ajbattle shpigi thefillm jtbassic babakap qwermish briordan weiweiguo egozi yaroslavvb gangli yas yama_tah filippone tag sdvillal dgront walkking jguinney kenji4569 DavidSchulz mdramirez mctor amargoli matjes eddymier tulip T_lab metric_embeddings Computer_Graphics
	A Global Geometric Framework for Nonlinear Dimensionality Reduction [My Copy] Science, Vol. 290, No. 5500. (22 December 2000), pp. 2319-2323. by J. B. Tenenbaum posted to machine-learning by pingmei on 2009-11-11 22:09:41 as along with 30 people and 4 groups seb1 Cavadini akuhn banus caicai klmoravec weiweiguo rramirezp babakap dcoates thefillm christofseiler qwermish egozi aufrank k12u yas metamerist yama_tah tag mthomure sdvillal dgront voiklis dwf DavidSchulz teesid jung_dalglish mctor matjes ur-cls T_lab metric_embeddings ColDyn
	Kernel principal component analysis [My Copy] Advances in kernel methods: support vector learning (1999), pp. 327-352. by Bernhard Schlkopf, Alexander J. Smola, Klaus R. Müller posted to machine-learning by pingmei on 2009-11-11 18:43:06 as along with 4 people m8j mahler rramirezp atbrew
	mGene: accurate SVM-based gene finding with an application to nematode genomes. [My Copy] Genome research, Vol. 19, No. 11. (29 November 2009), pp. 2133-2143. by Gabriele Schweikert, Alexander Zien, Georg Zeller, et al.Jonas Behr, Christoph Dieterich, Cheng Soon S. Ong, Petra Philips, Fabio De Bona, Lisa Hartmann, Anja Bohlen, Nina Krüger, Sören Sonnenburg, Gunnar Rätsch posted to machine-learning gene-finding by dakelley on 2009-11-11 18:04:20 as along with 4 people rshe kshameer natstreet farhat
	The Hugin Tool for Learning Bayesian Networks [My Copy] Symbolic and Quantitative Approaches to Reasoning with Uncertainty (2003), pp. 594-605. by Anders L. Madsen, Michael Lang, Uffe B. Kjærulff, Frank Jensen posted to machine-learning bayesian-net by rockelegancy on 2009-11-11 11:00:46 as
	Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization [My Copy] Journal of Machine Learning Research, Vol. 10 (October 2009), pp. 2157-2192. by Vojtěch Franc, Sören Sonnenburg posted to svm solver optimisation machine-learning cutting-plane by bedo on 2009-11-09 21:57:50 as
	Supervised reconstruction of biological networks with local models [My Copy] Bioinformatics, Vol. 23, No. 13. (1 July 2007), pp. i57-65. by Kevin Bleakley, Gerard Biau, Jean-Philippe Vert posted to vert svm supervised-machine-learning reconstruction machine-learning graph by seb1 on 2009-11-07 22:17:42 as along with 3 people ptrobajo anf shigepong
	Reducing the Dimensionality of Data with Neural Networks [My Copy] Science, Vol. 313, No. 5786. (28 July 2006), pp. 504-507. by G. E. Hinton, R. R. Salakhutdinov posted to neural-networks machine-learning dimensionality-reduction by mthomure on 2009-11-07 22:15:50 as along with 26 people and 9 groups pascanur jdoconnell __andy__ euclid austincarp babakap dakelley zheaton brian pdlug ana barry garyfeng mrkrause yama_tah neilh sdvillal dwf jwdietrich rgb mp4man josepe marcusfrean robincha ygarb ancechu structural_bioinformatics ReadingLab MathBio Bioinformatics Cybernetics pileWorks S-Lab Biomedical_Cybernetics AQUA-FONTIS-Study
	An Introduction to MCMC for Machine Learning [My Copy] Machine Learning, Vol. 50, No. 1. (1 January 2003), pp. 5-43. by Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan posted to mcmc machine-learning by mthomure on 2009-11-07 22:14:49 as along with 14 people and 1 group hgfernan xuzhe83 pqnga phil511 pdlug ldietz mshafiei wasteland93 bhaddow dowlingj markusd kozaki robotact delip Forest inventory and monitoring
	On spectral clustering: Analysis and an algorithm [My Copy] (2001) by A. Ng, M. Jordan, Y. Weiss posted to machine-learning linear-algebra clustering by mthomure on 2009-11-07 21:03:11 as along with 12 people and 1 group jrodriguez mbregman ajay81 pdlug walkking albher dimatura kohei-h alanzhaocs delip varming ecome Computer_Graphics
	Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data [My Copy] In Proc. 18th International Conf. on Machine Learning (2001), pp. 282-289. by John Lafferty, Andrew Mccallum, Fernando Pereira posted to machine-learning graphical-model by mthomure on 2009-11-07 21:02:27 as along with 5 people nlarusso pdlug ldietz g000nz0 zeppe
	Introduction to Machine Learning: Class Notes 67577 [My Copy] (23 Apr 2009) by Amnon Shashua posted to tutorial machine-learning by mthomure on 2009-11-07 20:09:16 as along with 8 people and 1 group dpf mdreid christiand belion ansobol Thermaneutist pdlug ima Statistical Machine Learning
	Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods [My Copy] BMC Bioinformatics, Vol. 10, No. 1. (30 October 2009), 365. by Stefano Lise, Cedric Archambeau, Massimiliano Pontil, David Jones posted to svm protein-protein-interaction machine-learning by kshameer on 2009-11-06 08:43:08 as along with 6 people and 1 group sillitoe apaydin zwang phoenixzxl higueruelo neils Orengo Group Journal Picks
	Kernel ellipsoidal trimming [My Copy] Computational Statistics & Data Analysis, Vol. 52, No. 1. (15 September 2007), pp. 309-324. by A. Dolia, C. Harris, J. Shawetaylor, D. Titterington posted to robust_statistics machine-learning by fabgoos on 2009-11-03 15:42:53 as along with 1 person daniel51
	Robust fitting of mixtures using the trimmed likelihood estimator [My Copy] Computational Statistics & Data Analysis, Vol. 52, No. 1. (15 September 2007), pp. 299-308. by N. Neykov, P. Filzmoser, R. Dimova, P. Neytchev posted to robust_statistics machine-learning gaussian-mixtures by fabgoos on 2009-11-03 15:38:09 as along with 1 person dgarcia
	Machine Learning and Robust Data Mining [My Copy] Computational Statistics & Data Analysis, Vol. 52, No. 1. (15 September 2007), pp. 151-154. by C. Croux, E. Gallopoulos, S. Vanaelst, H. Zha posted to robust_statistics machine-learning by fabgoos on 2009-11-03 15:11:57 as
	Learning the parts of objects by non-negative matrix factorization [My Copy] Nature, Vol. 401, No. 6755. (21 October 1999), pp. 788-791. by Daniel D. Lee, Sebastian H. Seung posted to nonnegative-matrix-factorization machine-learning by fabgoos on 2009-10-28 16:39:17 as along with 9 people svozil briordan vlachmore dragonrez bcao giorgos phlow noa kenji4569
	Document clustering based on non-negative matrix factorization [My Copy] In SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval (2003), pp. 267-273. by Wei Xu, Xin Liu, Yihong Gong posted to nonnegative-matrix-factorization machine-learning clustering by fabgoos on 2009-10-28 16:35:05 as along with 2 people apmonet pprett
	Convex and Semi-Nonnegative Matrix Factorizations [My Copy] Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 32, No. 1. (21 November 2008), pp. 45-55. by Chris H. Q. Ding, Tao Li, Michael I. Jordan posted to spectral-clustering nonnegative-matrix-factorization machine-learning kernels by fabgoos on 2009-10-26 19:04:04 as along with 1 person frohike
	Nonnegative matrix factorization and probabilistic latent semantic indexing: equivalence, chi-square statistic, and a hybrid method [My Copy] In AAAI'06: Proceedings of the 21st national conference on Artificial intelligence (2006), pp. 342-347. by Chris Ding, Tao Li, Wei Peng posted to nonnegative-matrix-factorization machine-learning latent-semantic by fabgoos on 2009-10-26 19:01:59 as
	Non-negative Matrix Factorization on Kernels [My Copy] PRICAI 2006: Trends in Artificial Intelligence (2006), pp. 404-412. by Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen posted to nonnegative-matrix-factorization machine-learning kernels by fabgoos on 2009-10-26 18:56:30 as along with 1 person camargoj
	Principled Hybrids of Generative and Discriminative Models [My Copy] Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on In CVPR '06: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 1 (05 July 2006), pp. 87-94. by J. A. Lasserre, C. M. Bishop, T. P. Minka posted to machine-learning by rockelegancy on 2009-10-26 12:34:49 as along with 2 people ppeeling ldietz
	Identifying the Intent of a User Query Using Support Vector Machines [My Copy] In SPIRE '09: Proceedings of the 16th International Symposium on String Processing and Information Retrieval (2009), pp. 131-142. by Marcelo Mendoza, Juan Zamora posted to query machine-learning ir intent 2get by ctl on 2009-10-24 21:56:50 as
	Efficient streaming text clustering☆ [My Copy] Neural Networks, Vol. 18, No. 5-6. (July 2005), pp. 790-798. by S. Zhong posted to stream-mining on_line_learning machine-learning clustering by fabgoos on 2009-10-21 22:16:25 as along with 6 people and 1 group chrisd surajitray kamotaku78 irenas scis0000001 jread82 dbk-lab
	A Framework for Clustering Uncertain Data Streams [My Copy] Data Engineering, 2008. ICDE 2008. IEEE 24th International Conference on In ICDE '08: Proceedings of the 2008 IEEE 24th International Conference on Data Engineering (2008), pp. 150-159. by Charu C. Aggarwal, Philip S. Yu posted to stream-mining spectral-clustering on_line_learning machine-learning clustering by fabgoos on 2009-10-21 22:09:11 as along with 1 person kallberg
	Using automatically labelled examples to classify rhetorical relations: an assessment [My Copy] Natural Language Engineering, Vol. 14, No. 03. (2008), pp. 369-416. by R. Caroline Sporlede, S. Alex Lascaride posted to rhetorical-relations machine-learning discourse by henk-cul on 2009-10-21 19:53:28 as
	Temporal-Relational Classifiers for Prediction in Evolving Domains [My Copy] Data Mining, IEEE International Conference on, Vol. 0 (2008), pp. 540-549. by Umang Sharan, Jennifer Neville posted to temporal_dimension social_networks relational_models protein_networks machine-learning dynamicnetworks by krisl on 2009-10-20 20:36:58 as along with 2 people nliu82 RafG
	Unsupervised prediction of citation influences [My Copy] In ICML '07: Proceedings of the 24th international conference on Machine learning (2007), pp. 233-240. by Laura Dietz, Steffen Bickel, Tobias Scheffer posted to prediction machine-learning influence citations by krisl on 2009-10-20 19:46:35 as along with 1 person jeonhyuk
	Machine Learning [My Copy] (01 March 1997) by Tom M. Mitchell posted to pac machine-learning by gagliol on 2009-10-18 17:00:18 as along with 40 people and 4 groups gavin1332 pinventado q_w_e_r_t_y librain gabriprat gokopal fiacobelli bgibson zhanwei agogoh3 ogenex imrchen gr650 ianwelch frohike misovalko harperf lrozo pdlug yaroslavvb jelsas kmregan carueda jounih buescher76 mthomure hansjoergmueller brunomelo cerkut jvangael ajylha girschick zchen teesid dquercia robotact jdu sfeige bundschu markusd TKU_CS DB Lab AI RiSE contact-id
	The Elements of Statistical Learning [My Copy] (30 July 2003) by T. Hastie, R. Tibshirani, J. H. Friedman posted to machine-learning lasso dimension-reduction book by abellogin on 2009-10-17 01:44:36 as along with 59 people and 11 groups azhdari emailhy donnachie singhsh mahmoodr lop idlebrain makrehchi awarlau gabriprat gokopal alexeigor liamtoh333 amsantos minrmw brian eddymier roys akastrin robotact thefillm ansobol pdlug yaroslavvb bigga jelsas davidr gyuli garyfeng aufrank neteler leidner chad_davis jekky balajis Jaykul balicea sdvillal donade bigbossman sbarthelme bedo AbnerCYH nojhan bamberg kgajos raiyar deysandeep petrposik dbgrant nmdang alfirk brianmc jung_dalglish dquercia blueskies Repton quianominorleo jaonary LDA and dimension reduction techniques CMU-HCII Blog_and_Wiki_Research automatic_summarization ReadingLab ur-cls ASR EvolutionaryComputation Metaheuristics Optimization CSBBGraphTheory
	Content-based image retrieval at the end of the early years [My Copy] Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 22, No. 12. (06 August 2002), pp. 1349-1380. by A. W. M. Smeulders, M. Worring, S. Santini, A. Gupta, R. Jain posted to pattern-recognition machine-learning by gregdavisfromnj on 2009-10-15 15:45:58 as along with 12 people and 1 group sirdjsmith brothers paulovn autrusseau-f jccaicedo gyuli mthomure dvallet vitalaswp3 vitalaswp4 zeppe suzannelittle NETS-UAM
	Online large-margin training of dependency parsers [My Copy] In In Proc. ACL (2005), pp. 91-98. by Ryan Mcdonald, Koby Crammer, Fernando Pereira posted to nlp-parser machine-learning by kwoodsend on 2009-10-15 13:00:30 as
	Varying-Coefficient Models [My Copy] Journal of the Royal Statistical Society. Series B (Methodological), Vol. 55, No. 4. (1993), pp. 757-796. by Trevor Hastie, Robert Tibshirani posted to stream-mining statistics on_line_learning machine-learning by fabgoos on 2009-10-14 17:05:47 as along with 1 person reconnie
	Dynamic Generalized Linear Models and Bayesian Forecasting [My Copy] Journal of the American Statistical Association, Vol. 80, No. 389. (1985), pp. 73-83. by Mike West, P. Jeff Harrison, Helio S. Migon posted to stream-mining statistics on_line_learning machine-learning by fabgoos on 2009-10-14 16:36:35 as
	Neural Networks: A Comprehensive Foundation [My Copy] (16 July 1998) by Simon Haykin posted to prototype-learning machine-learning by mthomure on 2009-10-12 22:57:06 as along with 14 people fernandohbc sdonatti matteodefelice tomsharp beete Viperus ngiann gatsoulis gr650 paaen napvasconcelos MarkVanHeeswijk thefillm agunduz
	Multiagent Systems: A Survey from a Machine Learning Perspective [My Copy] Autonomous Robots, Vol. 8, No. 3. (1 June 2000), pp. 345-383. by Peter Stone, Manuela Veloso posted to reinforcement-learning multi-agent machine-learning dai cooperation ai 2000 by ddahlem on 2009-10-09 22:45:13 as along with 3 people christiand pthimon Bc91
	Learning and Leveraging the Relationship between Architecture-Level Measurements and Individual User Satisfaction [My Copy] Computer Architecture, 2008. ISCA '08. 35th International Symposium on (15 July 2008), pp. 427-438. by A. Shye, B. Ozisikyilmaz, A. Mallik, et al.G. Memik, P. A. Dinda, R. P. Dick, A. N. Choudhary posted to machine-learning-in-architecture machine-learning by mamadoudiao on 2009-10-06 02:30:08 as
	Content-based book recommending using learning for text categorization [My Copy] In DL '00: Proceedings of the fifth ACM conference on Digital libraries (2000), pp. 195-204. by Raymond J. Mooney, Loriene Roy posted to recommender machine-learning explanation content-based collaborative-filtering by abellogin on 2009-10-05 17:05:54 as along with 3 people and 1 group asli2021 imrchen cpcreed Adaptive-Web
	Singular value decomposition and least squares solutions [My Copy] Numerische Mathematik, Vol. 14, No. 5. (29 April 1970), pp. 403-420. by G. Golub, C. Reinsch posted to svd machine-learning journal by abellogin on 2009-10-04 20:08:09 as along with 1 person fer
	Mining Association Rules between Sets of Items in Large Databases [My Copy] In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data (FebruaryJune--FebruaryAugust~ 1993), pp. 207-216. by Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami edited by Peter Buneman, Sushil Jajodia posted to rules machine-learning internship-09 by abellogin on 2009-10-04 02:42:40 as along with 14 people jdu michaelmampaey radical bigga tetsus tvdbulck dolhani abonchen pollaeng amsantos imrchen conley gvdh Yanno

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classification	71
metaheuristic	52
data-mining	45
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evolutionary-computation	41
support-vector-machine	41
ai	37
clustering	34
classifier	32
kernel	29
nlp	29
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learning	21
optimization	21
probability	21
feature-selection	20
concept-drift	19
information-theory	19
review	18
bayesian	17
book	17
cross-validation	17
graphical-models	17
prediction	17
protein	17
reinforcement-learning	17
continuous	16
pattern-recognition	16
ensemble	15
markov	15
one-class	15
collaborative-filtering	14
ecology	14
neural-networks	14
robot	14
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artificial-intelligence	12
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ir	10
kernel-methods	10
path	10
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survey	10
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cart	9
computational-linguistics	9
function	9
image-processing	9
information-extraction	9
kernels	9
microarray	9
ml	9
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multi-agent-systems	9
parsing	9
proteomics	9
statistic	9
applied-math	8
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decision-tree	8
evaluation	8
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information-retrieval	8
kullback	8
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maximum-entropy	8
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probabilistic-model	8
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semi-supervised	7
text-mining	7
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