sona's library 125 articles Export

	Covariate Shift Adaptation by Importance Weighted Cross Validation [My Copy] Journal of Machine Learning Research, Vol. 8 (May 2007), pp. 985-1005. by Masashi Sugiyama, Matthias Krauledat, Klaus-Robert Müller posted to data-shift covariate-shift by sona on 2009-10-26 11:08:58 as along with 1 person shivak
	Virtual brain reading: A connectionist approach to understanding fMRI patterns [My Copy] In Proceedings of the Cognitive Science Society Annual Conference (CogSci) (2009) by Rosemary A. Cowell, David E. Huber, Garrison W. Cottrell posted to self-organizing-map neural_network mvpa fmri face_areas by sona on 2009-10-22 14:56:19 as along with 1 group LIBrain
	A Survey of Clustering Data Mining Techniques [My Copy] Grouping Multidimensional Data In Grouping Multidimensional Data (2006), pp. 25-71. by Pavel Berkhin posted to survey clustering by sona on 2009-10-02 10:34:36 as along with 4 people eddymier imrchen lillejul nklee
	REDUS: finding reducible subspaces in high dimensional data [My Copy] In Proc. of the ACM Conf. on Information and Knowledge Management (CIKM) (2008), pp. 961-970. by Xiang Zhang, Feng Pan, Wei Wang posted to reducibile_subspace high_dimensional_data feature_selection dimensionality_reduction by sona on 2009-10-02 10:16:20 as
	The random subspace method for constructing decision forests [My Copy] Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 20, No. 8. (06 August 1998), pp. 832-844. by Tin K. Ho posted to subspace_method random_subspace_method ensemble-methods decision_trees decision_forests bootstrapping by sona on 2009-09-29 10:15:02 as along with 4 people and 2 groups MRCBIRD jxl drivard yaroslavvb Random Subspace Method EC
	Active Learning for kNN Based on Bagging Features [My Copy] International Conference on Natural Computation In International Conference on Natural Computation, Vol. 7 (2008), pp. 61-64. by Shuo Shi, Yuhai Liu, Yuehua Huang, Shihua Zhu, Yong Liu posted to random-subspace-method knn bagging active-learning by sona on 2009-09-28 13:05:33 as
	Online clustering of parallel data streams [My Copy] Data Knowl. Eng., Vol. 58, No. 2. (August 2006), pp. 180-204. by Jürgen Beringer, Eyke Hüllermeier posted to time_series online-clustering data_streams clustering by sona on 2009-09-15 11:54:27 as along with 2 people arsyed Nightscape
	Neural network for graphs: a contextual constructive approach. [My Copy] IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council, Vol. 20, No. 3. (March 2009), pp. 498-511. by A. Micheli posted to contextual-processing neural-networks relational-neural-networks by sona on 2009-05-11 14:52:36 as
	Large Margin Taxonomy Embedding for Document Categorization [My Copy] In Neural Information Processing Systems (NIPS), Vol. 21 (2008) by Kilian Weinberger, Olivier Chapelle posted to document-classification hierarchical-classifier taxonomy by sona on 2009-05-11 14:46:09 as
	Enhanced hierarchical classification via isotonic smoothing [My Copy] In WWW '08: Proceeding of the 17th international conference on World Wide Web (2008), pp. 151-160. by Kunal Punera, Joydeep Ghosh posted to algorithm hierarchical-classifier regularization smoothing by sona on 2009-05-11 14:39:18 as
	Approximation algorithms for co-clustering [My Copy] In PODS '08: Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2008), pp. 201-210. by Aris Anagnostopoulos, Anirban Dasgupta, Ravi Kumar posted to clustering co-clustering by sona on 2009-05-11 14:34:58 as along with 2 people sukru Continuum
	Structured machine learning: the next ten years [My Copy] Machine Learning, Vol. 73, No. 1. (2008), pp. 3-23. by Thomas Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli posted to ilp open-problems relational-learning srl statistical-relational-learning survey by sona on 2009-02-25 18:17:59 as along with 8 people and 1 group jjrodriguez abvg danielkcook bcao EmreSevinc briordan mdreid AbnerCYH Statistical Machine Learning
	A feature selection algorithm capable of handling extremely large data dimensionality [My Copy] In Proceedings of the 8th SIAM International Conference on Data Mining (2008), pp. 530-540. by Y. Sun, S. Todorovic, S. Goodison posted to feature_selection relief sparse-learning by sona on 2009-01-28 17:47:47 as
	Prediction and Interpretation of Distributed Neural Activity with Sparse Models [My Copy] NeuroImage, Vol. 44 (2009), pp. 112-122. by Melissa K. Carroll, Guillermo A. Cecchi, Irina Rish, Rahul Garg, A. Ravishankar Rao posted to feature_selection elastic-net lasso sparse-learning by sona on 2009-01-28 15:52:10 as along with 2 people librain eugeneduff
	Feature selection for high-dimensional data [My Copy] Computational Management Science, Vol. 6 (2009), pp. 25-40. by Augusto Destrero, Sofia Mosci, Christine De Mol, Alessandro Verri, Francesca Odone posted to gradient_descent feature_selection elastic-net feature-subsampling lasso ridge-regression subsampling by sona on 2009-01-28 14:49:26 as along with 1 person mdharsee
	Sparse principal component analysis [My Copy] Journal of Computational and Graphical Statistics, Vol. 15, No. 2. (2006), pp. 262-286. by H. Zou, T. Hastie, R. Tibshirani posted to elastic-net lasso pca sparse-learning spca by sona on 2009-01-28 11:40:08 as along with 1 person brianmc
	Penalized feature selection and classification in bioinformatics [My Copy] Brief Bioinform, Vol. 9, No. 5. (1 September 2008), pp. 392-403. by Shuangge Ma, Jian Huang posted to feature_selection elastic-net regularization survey by sona on 2009-01-27 17:32:34 as along with 7 people kshameer svozil bertelsen VGreiff jfr guhjy neils
	Feature selection, L1 vs. L2 regularization, and rotational invariance [My Copy] In ICML '04: Proceedings of the twenty-first international conference on Machine learning (2004), 78. by Andrew Y. Ng posted to feature_selection regularization sparse-learning by sona on 2009-01-27 13:53:02 as along with 6 people ajbattle maximzhao jessopher yaroslavvb bayesian mmunson
	A practical approach to feature selection [My Copy] In ML92: Proceedings of the ninth international workshop on Machine learning (1992), pp. 249-256. by Kenji Kira, Larry A. Rendell posted to feature-rating filter-feature-selection relief by sona on 2009-01-27 13:38:06 as along with 5 people awg2 ucbcjbm bedo eacosta h-chi
	Wrappers for Feature Subset Selection [My Copy] Artificial Intelligence, Vol. 97, No. 1-2. (1997), pp. 273-324. by Ron Kohavi, George H. John posted to feature_selection subsampling wrapper-feature-selection by sona on 2009-01-27 10:39:25 as along with 8 people andigoni tsoumakas bigga kutabar gkvas dimatura NinaG soleil_gurl
	Frustratingly Easy Domain Adaptation [My Copy] In Annual Meeting of the Association for Computational Linguistics (ACL), Vol. 1 (2007), pp. 256-263. by Hal Daume posted to adaptive-learning domain-adaptation by sona on 2009-01-26 13:27:39 as
	An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources [My Copy] IEEE Trans. on Knowl. and Data Eng., Vol. 15, No. 4. (2003), pp. 871-882. by Yuhua Li, Zuhair A. Bandar, David Mclean posted to semantic-similarity similarity wordnet by sona on 2009-01-22 11:06:22 as along with 1 person and 1 group dagmar dIEMoSIRIS
	Survey of clustering algorithms [My Copy] Neural Networks, IEEE Transactions on In Neural Networks, IEEE Transactions on, Vol. 16, No. 3. (2005), pp. 645-678. by Rui Xu, D. Wunsch posted to clustering measures metrics survey by sona on 2009-01-22 09:29:10 as along with 12 people and 1 group gavin1332 stharward thefillm pick600 qwermish jxl filippone seudonimo_falso amac theodora jcsilva jeojavi EC
	Feature subset selection bias for classification learning [My Copy] In Proc. of the Int. Conf. on Machine learning (ICML) (2006), pp. 849-856. by Surendra K. Singhi, Huan Liu posted to feature_selection by sona on 2008-11-14 12:38:15 as along with 2 people BrianTomasik 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 feature_selection survey by sona on 2008-11-14 12:32:40 as along with 5 people Jaldert sdvillal javo_eupla amargoli zhengzhong
	Computational Methods of Feature Selection [My Copy] (29 October 2007) edited by Huan Liu, Hiroshi Motoda posted to feature_selection elastic-net embedded-feature-selection feature-ranking feature-rating filter-feature-selection forward-selection random-subspace-method survey weighting-feature-selection wrapper-feature-selection by sona on 2008-11-14 12:01:42 as along with 5 people robert85 jdu gabriprat sdvillal stefanmeissner
	Regularization and variable selection via the Elastic Net [My Copy] Journal of the Royal Statistical Society B, Vol. 67 (2005), pp. 301-320. by Hui Zou, Trevor Hastie posted to feature_selection elastic-net lars lasso by sona on 2008-11-13 17:27:47 as along with 1 person ajbattle
	Regression shrinkage and selection via the lasso [My Copy] J. Roy. Statist. Soc. Ser. B, Vol. 58, No. 1. (1996), pp. 267-288. by Robert Tibshirani posted to feature_selection lasso regression ridge-regression shrinkage by sona on 2008-11-13 17:23:13 as along with 3 people dragonrez mukundn sbarthelme
	Least angle regression [My Copy] Annals of Statistics, Vol. 32 (2004), pp. 407-499. by Bradley Efron, Trevor Hastie, Lain Johnstone, Robert Tibshirani posted to feature_selection forward-selection lars lasso by sona on 2008-11-13 17:15:10 as along with 2 people and 1 group flieder vertikalist BTS-PT-AS-CS
	the Lasso and its dual [My Copy] (1998) by M. Osborne, B. Presnell, B. Turlach posted to lasso shrinkage by sona on 2008-09-12 10:51:05 as along with 1 person mukundn
	A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics. [My Copy] Statistical applications in genetics and molecular biology, Vol. 4 (2005) by J. Schäfer, K. Strimmer posted to shrinkage by sona on 2008-09-12 10:44:01 as along with 3 people tonamswish capitall mayercd
	Improving text classification by shrinkage in a hierarchy of classes [My Copy] In Proceedings of ICML-98, 15th International Conference on Machine Learning (1998), pp. 359-367. by Andrew K. Mccallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng edited by Jude W. Shavlik posted to shrinkage by sona on 2008-09-12 10:42:38 as along with 1 person marymcglo
	Estimation of the Mean by Shrinkage to a Point [My Copy] Journal of the American Statistical Association, Vol. 66, No. 333. (1971), pp. 86-90. by J. S. Mehta, R. Srinivasan posted to shrinkage by sona on 2008-09-12 10:40:55 as along with 1 person and 1 group abrentnall QFRMC_ConsumerCredit
	Some Shrinkage Techniques for Estimating the Mean [My Copy] Journal of the American Statistical Association, Vol. 63, No. 321. (1968), pp. 113-122. by James R. Thompson posted to shrinkage by sona on 2008-09-12 10:37:43 as along with 1 person and 1 group abrentnall QFRMC_ConsumerCredit
	Preventing "Overfitting" of Cross-Validation Data [My Copy] In ICML '97: Proceedings of the Fourteenth International Conference on Machine Learning (1997), pp. 245-253. by Andrew Y. Ng posted to cross-validation by sona on 2008-08-22 12:16:25 as
	Small Sample Statistics for Classification Error rates II: Confidence Intervals and Significance Tests [My Copy] (1996) by Kent J. Martin, D. S. Hirschberg posted to bootstrapping confidence-intervals cross-validation error-estimation leave-one-out subsampling test-significance by sona on 2008-08-21 15:40:00 as
	Small Sample Statistics for Classification Error rates I: Error Rate Measurement [My Copy] (1996) by Kent J. Martin, D. S. Hirschberg posted to bootstrapping cross-validation error-estimation leave-one-out subsampling by sona on 2008-08-21 15:13:30 as
	Stability of Randomized Learning Algorithms [My Copy] Journal of Machine Learning Research, Vol. 6 (January 2005), pp. 55-79. by Andre Elisseeff, Theodoros Evgeniou, Massimiliano Pontil posted to bagging bootstrapping randomized-algorithm sensitivity-analysis stability by sona on 2008-08-21 13:06:37 as
	Bootstrap - Inspired Techniques in Computation Intelligence [My Copy] Signal Processing Magazine, IEEE In Signal Processing Magazine, IEEE, Vol. 24, No. 4. (2007), pp. 59-72. by R. Polikar posted to adaboost bagging boosting data-fusion incremental-learning missing-feature mixture-of-experts by sona on 2008-07-18 13:51:20 as
	Random subspace method for multivariate feature selection [My Copy] Pattern Recognition Letters, Vol. 27, No. 10. (15 July 2006), pp. 1067-1076. by Carmen Lai, Marcel J. Reinders, Lodewyk Wessels posted to high_dimensional_data feature_selection boosting feature-ranking random-subspace-method small-sample-size-problem weighting-feature-selection by sona on 2008-07-18 13:43:26 as along with 2 people and 2 groups jjrodriguez librain Random Subspace Method LIBrain
	Feature ranking methods based on information entropy with Parzen windows [My Copy] International Conference on Research in Electrotechnology and Applied Informatics (REI'05) In Proceedings of the 9th International Conference on Research in Electrotechnology and Applied Informatics (REI'05) (2005), pp. 109-119. by J. Biesiada, W. Duch, A. Kachel, K. Maczka, S. Palucha posted to artificial-data feature-ranking real-data survey by sona on 2008-06-11 21:48:59 as
	Ensemble Feature Ranking [My Copy] Knowledge Discovery in Databases: PKDD 2004 In Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD) (2004), pp. 267-278. by Kees Jong, Jérémie Mary, Antoine Cornuéjols, Elena Marchiori, Michèle Sebag posted to ensemble-methods feature-ranking filter-feature-selection by sona on 2008-06-11 21:44:13 as
	Semi-Supervised Learning Literature Survey [My Copy] Vol. Tech. Rep. No. 1530 (December 2007) by Xiaojin Zhu posted to semi-supervised survey by sona on 2008-05-14 15:22:59 as along with 1 person pigfly
	On kernel methods for relational learning [My Copy] International Conference on Machine Learning (ICML) In Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003), Washington DC. (2003), pp. 107-114. by Chad Cumby, Dan Roth posted to composite-kernel kernel-methods relational-learning svm by sona on 2008-04-28 13:40:14 as along with 1 person julianpan
	A composite kernel to extract relations between entities with both flat and structured features [My Copy] International Conference on Computational Linguistics and the annual meeting of the ACL In ACL '06: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL (2006), pp. 825-832. by Min Zhang, Jie Zhang, Jian Su, Guodong Zhou posted to composite-kernel kernel-methods structured-input supervised svm by sona on 2008-04-28 13:24:51 as along with 1 person julianpan
	Bagging Predictors [My Copy] Machine Learning, Vol. 24, No. 2. (1996), pp. 123-140. by Leo Breiman posted to bagging survey by sona on 2008-04-09 19:02:00 as along with 8 people gabriprat mthomure santi515 jdu kliger ngarera maheshj drivard
	Bagging neural network sensitivity analysis for feature reduction for in-silico drug design [My Copy] International Joint Conference on Neural Networks (IJCNN) In Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on, Vol. 4 (2001), pp. 2478-2482 vol.4. by M. J. Embrechts, F. Arciniegas, M. Ozdemir, C. M. Breneman, K. Bennett, L. Lockwood posted to feature_selection embedded-feature-selection neural-networks sensitivity-analysis by sona on 2008-04-09 18:02:12 as
	Dimensionality reduction via sparse support vector machines [My Copy] Journal of Machine Learning Research, Vol. 3 (2003), pp. 1229-1243. by Jinbo Bi, Kristin Bennett, Mark Embrechts, Curt Breneman, Minghu Song posted to feature_selection embedded-feature-selection kernel-methods regularization sparse-learning svm by sona on 2008-04-09 17:36:34 as along with 2 people sdvillal KaraNagai
	Selection of relevant features and examples in machine learning [My Copy] Artificial Intelligence, Vol. 97, No. 1-2. (December 1997), pp. 245-271. by A. Blum posted to feature_selection embedded-feature-selection filter-feature-selection survey weighting-feature-selection wrapper-feature-selection by sona on 2008-04-09 17:22:18 as along with 7 people stharward gr650 sirandreus misovalko yaroslavvb sdvillal srp33
	Location estimation in wireless networks: a Bayesian approach [My Copy] Statistica Sinica, Vol. 16, No. 2. (2006), pp. 495-522. by David Madigan, Wen-Hua Ju, P. Krishnan, A. S. Krishnakumar, Ivan Zorych posted to bayesian-networks graphical-models localization monte-carlo sensor-networks by sona on 2008-04-09 16:36:28 as

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bibtex-import	24
feature_selection	18
semi-supervised	14
survey	13
unsupervised	13
neural-networks	12
relational-learning	12
supervised	10
shrinkage	8
hierarchical-classifier	7
lasso	7
probabilistic	7
svm	7
elastic-net	6
regularization	6
sparse-learning	6
kernel-methods	5
k-means	5
linked-input	5
structured-input	5
structured-output	5
bagging	4
bootstrapping	4
cascade-correlation	4
clustering	4
contextual-processing	4
embedded-feature-selection	4
feature-ranking	4
filter-feature-selection	4
recurrent-neural-networks	4
subsampling	4
text-classification	4
active-learning	3
cross-validation	3
high_dimensional_data	3
random-subspace-method	3
relational-neural-networks	3
sensitivity-analysis	3
taxonomy	3
time_series	3
top-down	3
weighting-feature-selection	3
wrapper-feature-selection	3
bayesian-networks	2
boosting	2
bpts	2
chemistry	2
composite-kernel	2
ensemble-methods	2
error-estimation	2
feature-rating	2
fmri	2
forward-selection	2
gradient_descent	2
lars	2
learning-algorithms	2
leave-one-out	2
mixture-of-experts	2
multi-label	2
naive-bayes	2
real-dataset	2
relief	2
ridge-regression	2
self-organizing-map	2
adaboost	1
adaptive-learning	1
algorithm	1
artificial-data	1
bottom-up	1
centroid-based	1
co-clustering	1
cognitive-states	1
complete-link-clustering	1
confidence-intervals	1
covariate-shift	1
data-fusion	1
data-shift	1
data_streams	1
decision_forests	1
decision_trees	1
digits-recognition	1
dimensionality_reduction	1
document-classification	1
document-mining	1
domain-adaptation	1
editorial	1
evolutionary-learning	1
face_areas	1
fast-learning	1
feature-subsampling	1
graphical-models	1
hidden-markov-random-fields	1
hierarchical-measures	1
ilp	1
incremental-learning	1
james-stein	1
knn	1
localization	1
measures	1
metrics	1
missing-feature	1
monte-carlo	1
mvpa	1
neural_network	1
online-clustering	1
open-problems	1
pca	1
probabilistic-logical	1
random-field	1
random-forest	1
randomized-algorithm	1
random_subspace_method	1
real-data	1
recursive-neural-networks	1
reducibile_subspace	1
regression	1
semantic-similarity	1
sensor-networks	1
sequences	1
similarity	1
small-sample-size-problem	1
smoothing	1
spca	1
srl	1
stability	1
statistical-relational-learning	1
stein-paradox	1
structured-prediction	1
subspace_method	1
tangent-distance	1
test-significance	1
topic-pagerank	1
t-statistic	1
wordnet	1

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