Publications

Proceedings – Book Chapters – Journals – Conferences - Patents

Edited Books and Proceedings

2.  D. Mery and L. Rueda. Advances in Image and Video Technology, Proceedings of the IEEE Pacific-Rim Symposium on Image and Video Technology (PSIVT 2007). Lecture Notes in Computer Science (LNCS), Vol. 4872, Springer, 2007.

1.  L. Rueda, D. Mery and J. Kittler. Progress in Pattern Recognition, Image Analysis and Applications, Proceedings of the 12th Iberoamerican Congress on Pattern Recognition (CIARP 2007), Lecture Notes in Computer Science (LNCS), Vol. 4756, Springer, 2007.

Book Chapters

4.  D. Rojas, L. Rueda, H. Urrutia, A. Ngom, and G. Carcamo, Automatic Segmentation Methods and Applications to Biofilm Image Analysis, Data Mining in Biomedical Signaling, Imaging and Systems, CRC Press, 2011.

3.  N. Subhani, L. Rueda, A. Ngom, On Clustering Gene Expression Time-series Signals, Data Mining in Biomedical Signaling, Imaging and Systems, CRC Press, 2011.

2.  B. John Oommen and L. Rueda, Stochastic Learning-based Weak Estimation of Multinomials and Its Applications to Pattern Recognition and Data Compression, Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches, IGI Global Publishers, ISBN 978-1-61692-811-7, 2010, pp. 1-29.

1.  L. Rueda and A. Bari, Clustering Time-series Gene Expression Data, Oligonucleotide Array Sequence Analysis, Nova Science Publishers, ISBN 978-1-60456-542-3, 2008, pp. 121-159.

Journals

29. Md. Aziz, M. Maleki, L. Rueda, M. Raza, S. Banerjee, Prediction of Biological Protein-protein Interactions using Atom-type and Amino Acid Properties, Proteomics, 2011, pp. 3802–3810, DOI: 10.1002/pmic.201100186.

28. L. Rueda, I. Rezaeian, A Fully Automatic Gridding Method for cDNA Microarray Images, BMC Bioinformatics, 2011, 12:113.

27. D. Rojas, L. Rueda, H. Urrutia, A. Ngom, G. Carcamo, Image Segmentation of Biofilm Structures Using Optimal Multi-Level Thresholding, International Journal of Data Mining and Bioinformatics, 2011, 5(3):266-286.

26. A. Ngom, L. Rueda, L. Wang, R. Gras, Selection Based Heuristics for the Non-Unique Oligonucleotide Probe Selection Problem in Microarray Design, Pattern Recognition Letters, 31(14): 2113-2125 (2010)..

25. N. Subhani, L. Rueda, A. Ngom, C. Burden, “Multiple Gene Expression Profile Alignment for Microarray Time-series Data Clustering”, Bioinformatics, 2010, 26(18):2281-2288.

24. L. Rueda, B. J. Oommen, C. Henriquez, Multi-class Pairwise Linear Dimensionality Reduction Using Heteroscedastic Schemes, Pattern Recognition, 43 (2010), pp. 2456-2465.

23. P. Jopia, N. Ruiz-Tagle, M. Villagrán, K. Sossa, S. Pantoja, L. Rueda, H. Urrutia, Biofilm Growth Kinetics of a Monomethylamine Producing Alphaproteobacteria Strain Isolated from an Anaerobic Reactor. Anaerobe, 16(2010), pp. 19-26.

22. L. Rueda and M. Herrera, A Theoretical Comparison of Two-class Fisher's and Heteroscedastic Linear Dimensionality Reduction Schemes, Pattern Recognition Letters, Vol. 29, 2008, pp. 2092-2098.

21. L. Wang, A. Ngom, L. Rueda, R. Gras, Selection Based Heuristics for the Non-Unique Oligonucleotide Probe Selection Problem, Springer Trans. on Computational Systems Biology, Springer, LNBI 5410, 2008, pp. 143-162.

20. L. Rueda, A. Bari, A. Ngom, Clustering Time-series Gene Expression Data with Unequal Time Intervals, Springer Trans. on Computational Systems Biology, Springer, LNBI 5410, 2008, pp. 100-123.

19. L. Rueda and B. John Oommen, An Efficient Compression Scheme for Data Communication which Uses a New Family of Self-Organizing Binary Search Trees, International Journal of Communication Systems, Vol. 21, 2008, pp. 1091-1120.

18. L. Rueda and M. Herrera, Linear Dimensionality Reduction by Maximizing the Chernoff Distance in the Transformed Space, Pattern Recognition, Vol. 41, Issue 10, 2008, pp. 3138-3152.

17. W. Yang, L. Rueda and A. Ngom, On Finding the Best Parameters of Fuzzy k-Means for Clustering Microarray Data, Multiple-Valued Logic and Soft-Computing Journal, 2007, Vol. 13, 2007, pp. 145-178.

16. B. Schell, M. Vargas Martin, P. Hung, and L. Rueda, Cyber Child Pornography: A Review Paper of the Social and Legal Issues and Remedies—and A Proposed Technological Solution, Aggression and Violent Behavior, Vol. 12, 2007, pp. 45-63.

15. L. Rueda and B. J. Oommen, Stochastic Automata-based Estimators for Adaptively Compressing Files with Non-Stationary Distributions. IEEE Transactions on System, Man and Cybernetics, Vol. 36, Issue 5, 2006, pp. 1196-1200.

14. A. Shupo, M. Vargas-Martin, L. Rueda, A. Bulkan, Y. Chen and P. Hung, Toward Efficient Detection of Child Pornography in the Network Infrastructure, IADIS International Journal on Computer Science and Information Systems, Vol. 1, No. 2, 2006, pp. 15-31.

13. L. Rueda and Y. Zhang, Geometric Visualization of Clusters Obtained from Fuzzy Clustering Algorithms. Pattern Recognition, Vol. 39, 2006, pp. 1415-1429.

12. L. Rueda and B. J. Oommen, A Fast and Efficient Nearly-Optimal Adaptive Fano Coding Scheme, Information Sciences, Vol. 276, 2006, pp. 1656–1683.

11. B. J. Oommen and L. Rueda, Stochastic Learning-based Weak Estimation of Multinomial Random Variables and Its Applications to Pattern Recognition in Non-stationary Environment, Pattern Recognition, Vol. 39, 2006, pp. 328-341.

10. L. Rueda and V. Vidyadharan, A Hill-climbing Approach for Automatic Gridding of cDNA Microarray Images. IEEE Transactions on Computational Biology and Bioinformatics, Vol. 3, No. 1, 2006, pp. 72-83.

  9. L. Qin, L. Rueda, A. Ali and A. Ngom, Spot Detection and Image Segmentation in DNA Microarray Data. Applied Bioinformatics, 2005, 4(1):1-12.

  8. L. Rueda, A One-dimensional Analysis for the Probability of Error of Linear Classifiers for Normally Distributed Classes. Pattern Recognition, Vol. 38, Issue 8, 2005, pp. 1197-1207.

  7. B. J. Oommen and L. Rueda, A Formal Analysis of Why Heuristics Work. Artificial Intelligence, Vol. 164, 2005, pp. 1-22.

  6. L. Rueda, Selecting the Best Hyperplane in the Framework of Optimal Pairwise Linear Classifiers. Pattern Recognition Letters, Vol. 25, Issue 1, 2004, pp. 49-62.

  5. L. Rueda, An Efficient Approach to Compute the Threshold for Multi-dimensional Linear Classifiers. Pattern Recognition, Vol. 37, Issue 4, April 2004, pp. 811-826.

  4. L. Rueda and B. J. Oommen, A Nearly-Optimal Fano-Based Coding Algorithm. Information Processing & Management, Vol. 40, Issue 2, 2004, pp. 257-268.

  3. L. Rueda and B. J. Oommen, On Optimal Pairwise Linear Classifiers for Normal Distributions: The d-Dimensional Case. Pattern Recognition, Vol. 36, Issue 1, January 2003, pp. 13-23.

  2. B. J. Oommen and L. Rueda, The Efficiency of Modern-Day Histogram-Like Techniques for Query Optimization. The Computer Journal, Vol. 45, No. 5, 2002, pp. 494-510.

  1. L. Rueda and B. J. Oommen, On Optimal Pairwise Linear Classifiers for Normal Distributions: The Two-Dimensional Case. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 2, February 2002, pp. 274-280.

Conferences

67. A. Jafarian, A. Ngom, L. Rueda, A Novel Recursive Feature Subset Selection Algorithm, 11th  IEEE International Conference on Bioinformatics and Bioengineering (BIBE 2011),  Taichung, Taiwan, 2011, DOI 10.1109/BIBE.2011.19.

66. A. Jafarian, A. Ngom, L. Rueda, New Gene Subset Selection Approaches Based on Linear Separating Genes and Gene-Pairs, 6th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2011), Delft, The Netherlands, 2011, pp. 50-62.

65. L. Rueda, I. Rezaeian, Applications of Multilevel Thresholding Algorithms to Transcriptomics Data, 16th Iberoamerican Congress on Pattern Recognition, Pucón, Chile, 2011, LNCS 7042, PP. 26-37. Plenary talk.

64. L. Rueda, I. Rezaeian, Automatic Algorithms for Analysis of cDNA Microarray and Chip-seq Data, Microarray World Congress, San Francisco, USA, 2011. Invited talk.

63. M. Maleki, Md. Aziz, L. Rueda, Analysis of Obligate and Non-obligate Complexes using Desolvation Energies in Domain-domain Interactions, 10th International Workshop on Data Mining in Bioinformatics (BIOKDD 2011) in conjunction with ACM SIGKDD 2011, San Diego, USA, 2011, pp. 21-26.

62. I. Rezaeian, L. Rueda, Biological Assessment of Grid and Spot Detection in cDNA Microarray Images, ACM Conference on Bioinformatics, Computational Biology and Biomedicine, Chicago, USA, 2011. To be presented.

61. Y. Li, A. Ngom, L. Rueda, A Framework of Gene Subset Selection Using Multiobjective Evolutionary Algorithm, 2011 IEEE Congress on Evolutionary Computation, New Orleans, USA, 2011.

60. M. Maleki, Md. Aziz, L. Rueda, M. Raza, S. Banerjee, “Domain-domain Interactions in Transient and Obligate Protein-protein Complexes”, Systems Biology Symposium, Ann Arbor, MI, USA, 2011. Poster presentation.

59. I. Rezaeian, L. Rueda, A Parameterless Automatic Spot Detection Method for cDNA Microarray Images, 3rd IEEE International Conference on Bioinformatics & Biomedicine, Hong Kong, 2010, pp. 388-392.

58. L. Rueda, S. Banerjee, Md. Aziz, M. Raza, Protein-protein Interaction Prediction using Desolvation Energies and Interface Properties, 3rd IEEE International Conference on Bioinformatics & Biomedicine, Hong Kong, 2010, pp. 17-22.

57. I. Rezaeian, L. Rueda, Sub-grid and Spot Detection in DNA Microarray Images using Optimal Multi-level Thresholding, 5th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2010), Nijmegen, The Netherlands, 2010, pp. 277-288.

56. L. Rueda, C. Garate, S. Banerjee, Md. Mominul Aziz, Biological Protein-protein Interaction Prediction using Binding Free Energies and Linear Dimensionality Reduction, 5th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2010), Nijmegen, The Netherlands, 2010, pp. 383-394.

55. Y. Li, N. Subhani, A. Ngom, L. Rueda, Alignment-based versus Variation-based Transformation Methods for Clustering Microarray Time-Series Data, 2010 ACM International Conference on Bioinformatics and Computational Biology (ACM-BCB 2010), Niagara Falls, USA, 2010, pp. 53-61. 

54. N. Subhani, Y. Li, A. Ngom, L. Rueda, Alignment versus Variation Methods for Clustering Microarray Time-Series Data, 2010 IEEE World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain, 2010, pp. 818-825.

53. Y. Li, A. Ngom, L. Rueda, Missing Value Imputation Methods for Gene-Sample-Time Microarray Data Analysis, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2010), Montreal, Canada, 2010, pp. 183-189.

52. N. Subhani, L. Rueda, A. Ngom, C. Burden, New Approaches to Clustering Microarray Time-Series Data Using Multiple Expression Profile Alignment, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2010), Montreal, Canada, 2010, pp. 170-176.

51. N. Subhani, A. Ngom, L. Rueda, C. Burden, Clustering Microarray Time-series Data using Expectation Maximization and Multiple Profile Alignment, Applications of Machine Learning in Bioinformatics Workshop (held at BIBM 2009), Washington, D.C., USA, 2009, pp. 2-7.

50. D. Rojas, L. Rueda, A. Ngom, H. Urrutia, G. Carcamo, Biofilm Image Segmentation Using Optimal Multi-Level Thresholding, IEEE International Conference on Bioinformatics & Biomedicine (BIBM 2009), Washington, D.C., USA, 2009, pp. 185-190.

49. L. Rueda, J. Rojas, A Pattern Classification Approach to DNA Microarray Image Segmentation, 4th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), Sheffield, UK, Springer, 2009, LNCS 5780, pp. 319-330.

48. D. Rojas, L. Rueda, H. Urrutia, A. Ngom, Efficient Optimal Multi-Level Thresholding for Biofilm Image Segmentation, 4th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), Sheffield, UK, 2009, LNCS 5780, 2009, pp. 307-318.

47. N. Subhani, A. Ngom, L. Rueda, C. Burden, Microarray Time-Series Data Clustering via Multiple Alignment of Gene Expression Profiles, 4th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), Sheffield, UK, 2009, LNCS 5780, 2009, pp. 377-390.

46. M. Pinninghoff, R. Contreras, L. Rueda, An Evolutionary Approach for Correcting Random Amplified Polymorphism DNA Images, 3rd International Work Conference on the Interplay between Natural and Artificial Computation (IWINAC 2009), Santiago de Compostela, Spain, LNCS 5602, 2009, pp. 469-477.

45. V.A. Gallardo, H. Urrutia, N. Ruiz-Tagle, C. Espinoza, L. Rueda, A. Ngom, C. Monsalve, A. Fonseca, J. Gutierrez, S. Rojas and L. Abarzua, High Throughput Sequencing to Assess Benthic Bacteria Biodiversity off Central Chile, Census of Marine Life Synthesis Workshop, (CoML 2009), February 1-5, Long Beach, California, 2009.

44. L. Rueda, An Efficient Algorithm for Optimal Multilevel Thresholding of Irregularly Sampled Histograms, 7th International Workshop on Statistical Pattern Recognition (S+SSPR 2008), Orlando, Florida, USA, Springer, LNCS 5432, 2008, pp. 612-621.

43. A. Bari, L. Rueda, A. Ngom,  “Microarray Time-Series Data Classification via Multiple Alignment of Gene Expression Profiles”, Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2008), Melbourne, Australia, Supplementary Proceedings, ISBN 978-0-7326-2226-8, 2008, pp. 25-36.

42  X. Li, A. Ngom and L. Rueda, Minimal siRNA Set Cover Heuristic for Gene Family Knockdown, Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2008), Melbourne, Australia, Supplementary Proceedings, ISBN 978-0-7326-2226-8, 2008, pp. 37-48.

41. L. Wang, A. Ngom, L. Rueda, Sequential Forward Selection Approach to the Non-Unique Oligonucleotide Probe Selection Problem, Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2008), Melbourne, Australia, 2008, Springer, LNBI 5265, pp. 262-275.

40. L. Rueda, C. Henriquez, B. J. Oommen, Chernoff-Based Multi-class Pairwise Linear Dimensionality Reduction, Proceedings of the 13th Iberoamerican Congress on Pattern Recognition (CIARP 2007), Havana, Cuba, 2008, LNCS 5197, pp. 301-308.

39. L. Wang, A. Ngom, R. Gras, L. Rueda, Evolution Strategy with Greedy Probe Selection Heuristics for the Non-Unique Oligonucleotide Probe Selection Problem, 5th Conference on Computational Intelligence in Bioinformatics and Bioengineering (CIBCB 2008), Sun Valley, Idaho, USA, 2008, pp. 54-61. Recognized for the Overall Best Paper Award.

38. V. Gallardo, A. Teske, J. L. Nielsen, H. Urrutia, N. Ruiz-Tagle, C. Espinoza, L. Abarzua, D. Andrades, L. Rueda, C. Monsalve, 16S Ribosomal RNA Gene Sequence Analysis of Sediment Macrobacteria from the Central Chile Oxygen Minimum Zone, 12th Biennial Symposium on Microbial Ecology (ISME-12), Cairns, Australia, 2008. Poster presentation.

37. L. Rueda, Sub-grid Detection in DNA Microarray Images, Proceedings of the IEEE Pacific-RIM Symposium on Image and Video Technology, Santiago, Chile, 2007, LNCS 4872, pp. 248-259.

36. L. Rueda and A. Bari, Clustering Temporal Gene Expression Data with Unequal Time Intervals, Proceedings of the 2nd International Conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS 2007), Bioinformatics Track. Budapest, Hungary, 2007, ICST 978-963-9799-11-0.

35. L. Rueda and B.J. Oommen, A New Approach to Adaptive Encoding Data using Self-organizing Data Structures, Proceedings of the 22nd International Symposium on Computer and Information Sciences, Ankara, Turkey, 2007, pp.15-20.

34. L. Rueda, O. Uyarte, S. Valenzuela and J. Rodriguez, Processing Random Amplified Polymorphysm DNA Images Using the Radon Transform and Mathematical Morphology, Proc. of the 4th International Conference on Image Analysis and Recognition, Montreal, Canada, 2007, LNCS 4633, pp. 1071-1081.

33. T. Gutierrez, L. Rueda,  J. Martinez, M. Bunster, “Finding Discriminant Features in Interaction Sites for Identifying Transient and Obligate Protein-protein Complexes”, Bioinformatics 2007, Joint Collaborative Workshop of the European Molecular Biology Network (EMBnet) and the Iberoamerican Bioinformatics Network (RIBIO), Malaga, Spain, 2007. Poster presentation.

32. L. Rueda and M. Herrera, A New Approach to Multi-class Linear Dimensionality Reduction, Proc. of the 11th Iberoamerican Congress on Pattern Recognition, Cancun, Mexico, 2006, LNCS 4225, pp. 634-643.

31. L. Rueda and M. Herrera, A Theoretical Comparison of Two Linear Dimensionality Reduction Techniques, Proc. of the 11th Iberoamerican Congress on Pattern Recognition, Cancun, Mexico, 2006, LNCS 4225, pp. 624-633.

30. L. Rueda and M. Herrera, A New Linear Dimensionality Reduction Technique based on Chernoff Distance, Proc. of the 10th Ibero-American Conference on Artificial Intelligence, Ribeirao Preto, Brazil, 2006, LNAI 4140, pp. 299-308.

29. M. Ali, L. Rueda, and M. Herrera, On the Performance of Chernoff-distance-based Linear Dimensionality Reduction Techniques, Proc. of the 19th Canadian Conference on Artificial Intelligence, Quebec, Canada, 2006, Springer, LNAI 4013, pp. 469-480.

28. A. Bari and L. Rueda, A New Profile Alignment Method for Clustering Gene Expression Data, Proc. of the 19th Canadian Conference on Artificial Intelligence, Quebec, Canada, 2006, Springer, LNAI 4013, pp. 86-97.

27. M. Chopra, M. Vargas Martin, L. Rueda, P.C.K. Hung. Toward New Paradigms to Combating Internet Child Pornography. Proc. of the IEEE Canadian Conference on Electrical and Computing Engineering (CCECE '06), Ottawa, Canada, 2006, pp. 471-474.

26. M. Chopra, M. Vargas-Martin, L. Rueda and P. Hung, A Source Address Reputation System to Combating Child Pornography at the Network Level, Proc. of the IADIS International Conference on Applied Computing, San Sebastian, Spain, 2006, pp. 472-477.

25. L. Rueda and Y. Zhang, A Geometric Framework to Visualize Fuzzy-clustered Data, Proc. of the XXV International Conference of the Chilean Computer Science Society, Valdivia, Chile, 2005, pp. 13-20.

24. W. Yang, L. Rueda, and A. Ngom, A Simulated Annealing Approach to Find the Optimal Parameters for Fuzzy Clustering Microarray Data, Proc. the XXV International Conference of the Chilean Computer Science Society, Valdivia, Chile, 2005, pp. 45-54.

23. L. Rueda and B. J. Oommen, Efficient Adaptive Data Compression using Fano Binary Search Trees. Proc. of the 20th International Symposium on Computer and Information Sciences, Istanbul, Turkey, 2005, Springer, LNCS 3733, pp.768-779.

22. B. J. Oommen and L. Rueda, On Utilizing Stochastic Learning Weak Estimators for Training and Classification of Patterns with Non-Stationary Distributions. Proc. of the 28th German Conference on Artificial Intelligence (KI 2005), Koblenz, Germany, 2005, Springer, LNAI 3698, pp. 107-120.

21. L. Rueda and L. Qin, A New Method for DNA Microarray Image Segmentation. Proc. of the International Conference on Image Analysis and Recognition, Toronto, Canada, 2005, Springer, LNCS 3656, pp. 886-893.

20. L. Rueda and V. Vidyadharan, A New Approach to Automatically Detecting Grids in DNA Microarray Images. Proc. of the International Conference on Image Analysis and Recognition, Toronto, Canada, 2005, Springer, LNCS 3656, pp. 982-989.

19. L. French, A. Ngom and L. Rueda, Fast Protein Superfamily Classification using Principal Component Null Space Analysis. Proc. of the 18th Canadian Conference on Artificial Intelligence, Victoria, Canada, 2005, LNCS 3501, Springer, pp. 158-169.

18. L. Rueda and L. Qin, An Unsupervised Learning Scheme for DNA Microarray Image Spot Detection. Proc. of the First International Conference on Complex Medical Engineering, Takamatsu, Japan, 2005, pp. 996-1000.

17. L. Rueda and Y. Zhang, A New Approach for Visualizing Fuzzy-clustered Microarray Data. Proc. of the 6th International Conference on Mathematics and Computers in Biology and Chemistry, Buenos Aires, Argentina, 2005, track No. 503-118.

16. L. Rueda and V. Vidyadharan, A New Approach to Automatically Detecting Grids in DNA Microarray Images, International Conference on Bioinformatics and its Applications (ICBA’04), Fort Laurerdale, Florida, 2004. Poster presentation.

15. L. Rueda, New Bounds and Approximations for the Error of Linear Classifiers, Proc. of the 8th Iberoamerican Congress on Pattern Recognition, Puebla, Mexico, 2004, LNCS 3287, pp. 342-349.

14. L. Rueda and B. John Oommen, On Families of New Adaptive Compression Algorithms Suitable for Time-varying Source Data, Proc. of the Third Biennial International Conference on Advances in Information Systems, Izmir, Turkey, 2004, LNCS 3261, Springer, pp. 234-244.

13. L. Rueda and L. Qin, An Improved Clustering-based Approach for DNA Microarray Image Segmentation, Proc. of the International Conference on Image Analysis and Recognition, Porto, Portugal, September 2004, LNCS 3138, Springer, pp. 644-652.

12. B. J. Oommen and L. Rueda, A New Family of Weak Estimators for Training in Non-Stationary Distributions, Proc. of the Joint IAPR International Workshop on Statistical Pattern Recognition, Lisbon, Portugal, 2004, pp. 644-652.

11. L. Rueda and A. Ngom, An Empirical Evaluation of the Classification Error of Two Thresholding Methods for Fisher's Classifier, Proc. of the 2004 International Conference on Machine Learning, Model, Technology and its Applications, Las Vegas, Nevada, USA, 2004, pp. 837-842.

10. L. Rueda, A New Approach that Selects a Single Hyperplane from the Optimal Pairwise Linear Classifier. Proc. of the 8th Iberoamerican Congress on Pattern Recognition, Havana, Cuba, November 26-29, 2003, LNCS 2905, Springer, pp. 521-528.

  9. L. Rueda, Two Schemes for Computing Thresholds in Linear Classifiers. Proc. of the 2003 International Conference on Natural Language Processing and Knowledge Engineering, Beijing, China, October 2003, Track No. A24-05.

  8. L. Rueda, An Empirical Analysis of Traditional and Optimal Pairwise Linear Classifiers on Standard Benchmarks. Proc. of the 3rd International Workshop on Pattern Recognition in Information Systems, Angers, France, April 2003, pp. 88-95.

  7. B. J. Oommen and L. Rueda, Using Pattern Recognition Techniques to Derive a Formal Analysis of Why Heuristic Functions Work, Proc. of the 2nd International Workshop on Pattern Recognition in Information Systems, Alicante, Spain, April 2002, pp. 45-58.

  6. L. Rueda and B.J. Oommen, Greedy Adaptive Fano Coding, Proc. of the 2002 IEEE Aerospace Conference, BigSky, MT, USA, Track 10, March 2002.

  5. L. Rueda and B. J. Oommen, Resolving Minsky's Paradox : The d-Dimensional Normal Distribution Case, Proc. of The 14th Australian Joint Conference on Artificial Intelligence (AI’01), Adelaide, Australia, December 2001, pp. 25-36.

  4. L. Rueda and B.J. Oommen, Enhanced Static Fano Coding, Proc. of the IEEE Conference on Systems, Man and Cybernetics, Tucson, Arizona, USA, October 2001, pp. 2163-2169.

  3. B.J. Oommen and L. Rueda, Histogram Methods in Query Optimization : The Relation between Accuracy and Optimality, 7th International Conference on Database Systems for Advanced Applications, Hong Kong, April 2001, pp. 320-326. 

  2. B.J. Oommen and L. Rueda, An Empirical Comparison of Histogram-like Techniques for Query Optimization, Proc of the 2nd International Conference on Enterprise Information Systems (ICEIS), Stafford, UK, 2000, pp. 71-78.

  1. L. Rueda and B.J. Oommen, The Foundational Theory of Optimal Bayesian Pairwise Linear Classifiers, Proc. of the Joint IAPR International Workshops SSPR'2000 and SPR'2000, Alicante, Spain, 2000, pp. 581-590.

Patents

1.  Encryption Possessing Statistical Perfect Secrecy and Stealth, B.J. Oommen and L. Rueda. Click here for an overview.