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sdvillal's library [879 articles]

Recent papers added to sdvillal's library ordered by importance.
  • An evaluation of dimension reduction techniques for one-class classification
    Artificial Intelligence Review
    by Santiago Villalba, Pádraig Cunningham
  • How to present a paper in theoretical computer science: a speaker's guide for students
    SIGACT News, Vol. 31, No. 1. (March 2000), pp. 77-86.
    by Ian Parberry
  • Introduction to the Theory of Computation, Second Edition
    (15 February 2005)
    by Michael Sipser
  • Algorithmics: The Spirit of Computing (3rd Edition)
    (11 June 2004)
    by David Harel, Yishai Feldman
    posted to theoretical-computer-science complexity automata algorithmics by sdvillal on 2008-09-17 14:27:15 as **
  • Elements of the Theory of Computation (2nd Edition)
    (17 August 1997)
    by Harry R Lewis, Christos H Papadimitriou
    posted to theoretical-computer-science complexity automata algorithmics by sdvillal on 2008-09-17 14:22:53 as **
  • Introduction to Automata Theory, Languages, and Computation (2nd Edition)
    (14 November 2000)
    by John E Hopcroft, Rajeev Motwani, Jeffrey D Ullman
  • Domain described support vector classifier for multi-classification problems
    Pattern Recognition, Vol. 40, No. 1. (January 2007), pp. 41-51.
    by Daewon Lee, Jaewook Lee
    posted to occ-support-vector occ-to-multiclass by sdvillal on 2008-08-27 10:34:56 as **
  • Feature extraction for one-class classification problems: Enhancements to biased discriminant analysis
    Pattern Recognition, Vol. In Press, Corrected Proof
    by Nojun Kwak, Jiyong Oh
  • Multi-class pattern classification using neural networks
    Pattern Recognition, Vol. 40, No. 1. (January 2007), pp. 4-18.
    by Guobin Ou, Yi L Murphey
    posted to multiclass by sdvillal on 2008-08-27 10:19:50 as **
  • Get Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers
    (2008)
    by Victor Sheng, Foster Provost, Panagiotis G Ipeirotis
    posted to active-learning multilabel by sdvillal on 2008-08-21 14:42:09 as **
  • Active Sampling for Class Probability Estimation and Ranking
    Machine Learning, Vol. 54, No. 2. (February 2004), pp. 153-178.
  • The Synergy Between PAV and AdaBoost
    Machine Learning, Vol. 61, No. 1-3. (November 2005), pp. 71-103.
    by W Wilbur, Lana Yeganova, Won Kim
    posted to boosting calibration ensembles by sdvillal on 2008-08-17 07:58:45 as **
  • PAV and the ROC convex hull
    Machine Learning, Vol. 68, No. 1. (24 July 2007), pp. 97-106.
    by Tom Fawcett, Alexandru Niculescu-Mizil
    posted to calibration roc by sdvillal on 2008-08-15 12:43:42 as **
  • Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
    (1999), pp. 61-74.
    by John C Platt
    posted to calibration by sdvillal on 2008-08-13 16:50:41 as ** along with 1 person asterix77
  • A note on Platt’s probabilistic outputs for support vector machines
    Machine Learning, Vol. 68, No. 3. (23 October 2007), pp. 267-276.
    by Hsuan-Tien Lin, Chih-Jen Lin, Ruby Weng
    posted to calibration by sdvillal on 2008-08-13 16:29:45 as ** along with 2 people alexn Mohan-S
  • Predicting good probabilities with supervised learning
    (2005), pp. 625-632.
    by Alexandru Niculescu-Mizil, Rich Caruana
    posted to calibration by sdvillal on 2008-08-13 10:17:14 as ** along with 2 people rwm101 poluxmoon
  • Probabilistic score estimation with piecewise logistic regression
    (2004)
    by Jian Zhang, Yiming Yang
    posted to calibration by sdvillal on 2008-08-13 10:14:49 as ** along with 1 person Vezhnick
  • An empirical evaluation of supervised learning in high dimensions
    (2008), pp. 96-103.
    by Rich Caruana, Nikos Karampatziakis, Ainur Yessenalina
    posted to calibration evaluation-methodology high-dimensionality by sdvillal on 2008-08-13 09:53:38 as **
  • Properties and benefits of calibrated classifiers
    (2004), pp. 125-136.
    by Ira Cohen, Moises Goldszmidt
    posted to calibration by sdvillal on 2008-08-12 20:01:31 as **
  • Putting Things in Order: On the Fundamental Role of Ranking in Classification and Probability Estimation
    Knowledge Discovery in Databases: PKDD 2007 (2007), pp. 2-3.
    by Peter Flach
    posted to calibration ml-foundations ranking by sdvillal on 2008-08-12 20:00:42 as **
  • Explaining Classifications For Individual Instances
    Knowledge and Data Engineering, IEEE Transactions on, Vol. 20, No. 5. (2008), pp. 589-600.
    posted to interpretability by sdvillal on 2008-08-12 19:14:38 as ** along with 1 person jjrodriguez
  • Weighted One-Against-All
    (2005), pp. 720-725.
    by Alina Beygelzimer, John Langford, Bianca Zadrozny
    edited by Manuela M Veloso, Subbarao Kambhampati, Manuela M Veloso, Subbarao Kambhampati
    posted to multiclass multilabel by sdvillal on 2008-08-12 18:31:10 as **
  • Policy Mining: Learning Decision Policies from Fixed Sets of Data
    (2003)
    by Bianca Zadrozny
    posted to active-learning calibration cost-sensitive by sdvillal on 2008-08-12 18:13:25 as **
  • Performance thresholding in practical text classification
    (2006), pp. 662-671.
    by Hinrich Schütze, Emre Velipasaoglu, Jan O Pedersen
  • Support Vector Machine Active Learning with Applications to Text Classification
    Journal of Machine Learning Research, Vol. 2 (November 2001), pp. 45-66.
    by Simon Tong, Daphne Koller
  • Less is More: Active Learning with Support Vector Machines
    (2000), pp. 839-846.
    by Greg Schohn, David Cohn
    posted to active-learning kernel-machines by sdvillal on 2008-08-04 20:23:15 as ** along with 1 person kgajos
  • Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
    (2005), pp. 330-337.
    by Thomas Osugi, Deng Kun, Stephen Scott
    posted to active-learning by sdvillal on 2008-08-02 11:29:46 as ** along with 1 person Mohan-S
  • Online Choice of Active Learning Algorithms
    Journal of Machine Learning Research, Vol. 5 (March 2004), pp. 255-291.
    by Yoram Baram, Ran E Yaniv, Kobi Luz
  • Comments on real-valued negative selection vs. real-valued positive selection and one-class SVM
    Evolutionary Computation, 2007. CEC 2007. IEEE Congress on (2007), pp. 3727-3734.
    by T Stibor, J Timmis
    posted to negative-example-selection occ-others by sdvillal on 2008-07-30 12:20:24 as **
  • Growing a multi-class classifier with a reject option
    Pattern Recognition Letters, Vol. 29, No. 10. (15 July 2008), pp. 1565-1570.
    by DMJ Tax, RPW Duin
  • The Curse of Highly Variable Functions for Local Kernel Machines
    (2005)
    by Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux
    posted to dimension-reduction kernel-machines locality by sdvillal on 2008-07-15 16:09:15 as **
  • An information-theoretic perspective of tf-idf measures
    Information Processing & Management, Vol. 39, No. 1. (January 2003), pp. 45-65.
    by Akiko Aizawa
  • Modeling word burstiness using the Dirichlet distribution
    (2005), pp. 545-552.
    by Rasmus E Madsen, David Kauchak, Charles Elkan
    posted to dirichlet text-classification by sdvillal on 2008-06-11 16:03:24 as **
  • Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution
    (2006), pp. 289-296.
    by Charles Elkan
    posted to dirichlet text-classification by sdvillal on 2008-06-11 16:02:18 as **
  • Building Text Classifiers Using Positive and Unlabeled Examples
    (2003)
    by Bing Liu, Yang Dai, Xiaoli Li, Wee S Lee, Philip S Yu
  • Addressing the curse of imbalanced training sets: one-sided selection
    (1997), pp. 179-186.
    by Miroslav Kubat, Stan Matwin
  • A practical method for the software fault-prediction
    Information Reuse and Integration, 2007. IRI 2007. IEEE International Conference on (2007), pp. 659-666.
    by Zhan Li, M Reformat
    posted to boosting imbalanced by sdvillal on 2008-06-03 06:42:12 as **
  • Generalization from Observed to Unobserved Features by Clustering
    Journal of Machine Learning Research, Vol. 9 (March 2008), pp. 339-370.
    by Eyal Krupka, Naftali Tishby
  • Max-margin Classification of Data with Absent Features
    Journal of Machine Learning Research, Vol. 9 (January 2008), pp. 1-21.
    by Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller
    posted to structured-domains unobserved-features by sdvillal on 2008-06-02 10:30:47 as **
  • Computational Methods of Feature Selection (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)
    (29 October 2007)
  • The Pyramid Match Kernel: Efficient Learning with Sets of Features
    Journal of Machine Learning Research, Vol. 8 (April 2007), pp. 725-760.
    by Kristen Grauman, Trevor Darrell
  • Feature selection for text categorization on imbalanced data
    SIGKDD Explor. Newsl., Vol. 6, No. 1. (June 2004), pp. 80-89.
    by Zhaohui Zheng, Xiaoyun Wu, Rohini Srihari
  • An Extensive Empirical Study of Feature Selection Metrics for Text Classification
    Journal of Machine Learning Research, Vol. 3 (March 2003), pp. 1289-1305.
    by George Forman
  • Phase transitions and the search problem
    Artificial Intelligence, Vol. 81, No. 1-2. (March 1996), pp. 1-15.
    by Tad Hogg, Bernardo A Huberman, Colin P Williams
    posted to phase-transition by sdvillal on 2008-05-14 14:39:31 as **
  • The Design and Analysis of an Algorithm Portfolio for SAT
    Principles and Practice of Constraint Programming (2007), pp. 712-727.
    by Lin Xu, Frank Hutter, Holger Hoos, Kevin Leyton-Brown
    posted to algorithm-portfolio data-mining-general meta-learning sat by sdvillal on 2008-05-13 09:12:42 as **
  • Off-the-peg and bespoke classifiers for fraud detection
    Computational Statistics & Data Analysis, Vol. 52, No. 9. (15 May 2008), pp. 4521-4532.
    by Piotr Juszczak, Niall M Adams, David J Hand, Christopher Whitrow, David J Weston
  • Variational Extensions to EM and Multinomial PCA
    (2002), pp. 23-34.
    by Wray L Buntine
  • Scale-sensitive dimensions, uniform convergence, and learnability
    J. ACM, Vol. 44, No. 4. (July 1997), pp. 615-631.
    by Noga Alon, Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler
  • Reliable Reasoning: Induction and Statistical Learning Theory (Jean Nicod Lectures)
    (01 May 2007)
    by Gilbert Harman, Sanjeev Kulkarni
  • Tutorial on Practical Prediction Theory for Classification
    Journal of Machine Learning Research, Vol. 6 (March 2005), pp. 273-306.
    by John Langford
    posted to error-estimation learning-bounds ml-foundations by sdvillal on 2008-04-24 12:37:12 as **
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