Publications - by Research Category

• Transductive Learning • Sequence Prediction • Online Learning • Ensemble Methods • Active Learning • Unsupervised Learning/Clustering • Feature Selection/Generation • Text Categorization • Portfolio Selection and Trading • Computational Finance • Competitive Analysis • Texture Analysis • Fault Tolerant Distributed Computation • Bioinformatics • Medical Diagnosis • Single-Class Classification • Multi-Class Classification • Compression • Other •

Transductive Learning

• R. El-Yaniv and D. Pechyony. Stable Transductive Learning.. In Proceedings of the 19th Annual Conference on Computational Learning Theory (COLT), pp. 35–49, 2006.
  Download:  
• R. El-Yaniv and L. Gerzon. Effective Transductive Learning via Objective Model Selection. Pattern Recognition Letters, 26(13):2104–2115, 2005.
  Download:    
• P. Derbeko, R. El-Yaniv and R. Meir. Explicit Learning Curves for Transductive Learning and Application to Clustering and Compression Algorithms. Journal of Artificial Intelligence Research (JAIR), 22:117–142, 2004.
  Download:      
• R. El-Yaniv and L. Gerzon. Effective Transductive Learning via PAC-Bayesian Model Selection. Technical Report CS-2004-05, Technion - Israel Institute of Technology, 2004.
  Download:      
• P. Derbeko, R. El-Yaniv and R. Meir. Error Bounds for Transductive Learning via Compression and Clustering. In Advances in Neural Information Processing Systems (NIPS) 16, pp. 1085–1092, MIT Press, Cambridge, MA, 2003.
  Download:      
• R. El-Yaniv and O. Souroujon. Iterative Double Clustering for Unsupervised and Semi-Supervised Learning. In Advances in Neural Information Processing Systems (NIPS) 14, pp. 1025–1032, MIT Press, Cambridge, MA, 2001.
  Download:      

Sequence Prediction

• R. Begleiter and R. El-Yaniv. Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition. Journal of Machine Learning Research, 7:379–411, 2006.
  Download:  
• R. Begleiter and R. El-Yaniv. Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition. Technical Report CS-2005-13, Technion - Israel Institute of Technology, 2005.
  Download:      
• R. Begleiter, R. El-Yaniv and G. Yona. On Prediction Using Variable Order Markov Models. Journal of Artificial Intelligence Research (JAIR), 22:385–421, 2004.
  Download:      
• R. Yaroshinsky, R. El-Yaniv and S. Seiden. How to Better Use Expert Advice. Machine Learning, 55(3):271–309, June 2004.
  Download:      
• M. Nisenson, I. Yariv, R. El-Yaniv and R. Meir. Towards Behaviometric Security Systems: Learning to Identify a Typist. In Proceedings of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp. 363–374, 2003.
  Download:  
• R. Bachrach, R. El-Yaniv and M. Reinstaedtler. On the Competitive Theory and Practice of List Accessing Algorithms. Algorithmica, 32:201–246, 2002.
  Download:      
• R. El-Yaniv, A. Fiat, R.M. Karp and G. Turpin. Optimal Search and One-Way Trading Online Algorithms. Algorithmica, 30(1):101–139, 2001.
  Download:    
• A. Borodin, R. El-Yaniv and V. Gogan. On the Competitive Theory and Practice of Portfolio Selection (Extended Abstract). In Proceedings of the 4th Latin American Symposium on Theoretical Informatics (LATIN'00), pp. 173–196, 2000.
  Download:    
• R. Bachrach and R. El-Yaniv. Online list Accessing Algorithms and Their Applications: Recent Empirical Evidence. In Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms (SODA), pp. 53–62, 1997.
  Download:    
• R. El-Yaniv, S. Fine and N. Tishby. Agnostic Classification of Markovian sequences. In Proceedings of Neural Information Processing Systems (NIPS), pp. 465–471, MIT Press, 1997.
  Download:    
• R. El-Yaniv, A. Fiat, R.M. Karp and G. Turpin. Competitive Analysis of Financial Games. In IEEE Symposium on Foundations of Computer Science (FOCS), pp. 327–333, 1992.
  Download:    

Online Learning

• Y. Baram, R. El-Yaniv and K. Luz. Online Choice of Active Learning Algorithms. Journal of Machine Learning Research, 5:255–291, March 2004.
  Download:      
• A. Borodin, R. El-Yaniv and V. Gogan. Can We Learn to Beat the Best Stock. Journal of Artificial Intelligence Research, 21:579–594, May 2004.
  Download:  
• R. Yaroshinsky, R. El-Yaniv and S. Seiden. How to Better Use Expert Advice. Machine Learning, 55(3):271–309, June 2004.
  Download:      
• Y. Baram, R. El-Yaniv and K. Luz. Online Choice of Active Learning Algorithms. In Proceedings of the Twentieth International Conference on Machine Learning (ICML), pp. 19–26, 2003.
  Download:  
• A. Borodin, R. El-Yaniv and V. Gogan. Can We Learn to Beat the Best Stock. In Advances in Neural Information Processing Systems (NIPS) 16, pp. 345–352, MIT Press, Cambridge, MA, 2003.
  Download:      
• Z. Nevo and R. El-Yaniv. On Online Learning of Decision Lists. Journal of Machine Learning Research (JMLR), 3:271–301, October 2002.
  Download:      

Ensemble Methods

• P. Derbeko, R. El-Yaniv and R. Meir. Variance Optimized Bagging. In Proceedings of the 13th European Conference on Machine Learning (ECML), pp. 60–71, 2002.
  Download:      
• R. Meir, R. El-Yaniv and S. Ben-David. Localized Boosting. In Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT), pp. 190–199, 2000.
  Download:    

Active Learning

• Y. Baram, R. El-Yaniv and K. Luz. Online Choice of Active Learning Algorithms. Journal of Machine Learning Research, 5:255–291, March 2004.
  Download:      
• Y. Baram, R. El-Yaniv and K. Luz. Online Choice of Active Learning Algorithms. In Proceedings of the Twentieth International Conference on Machine Learning (ICML), pp. 19–26, 2003.
  Download:  

Unsupervised Learning/Clustering

• R. Bekkerman, R. El-Yaniv and A. McCallum. Multi-Way Distributional Clustering via Pairwise Interactions. In Proceedings of the 22nd International Conference on Machine Learning (ICML), pp. 41–48, 2005.
  Download:      
• R. Bekkerman, R. El-Yaniv, N. Tishby and Y. Winter. Distributional Word Clusters vs. Words for Text Categorization. Journal of Machine Learning Research, 3:1183–1208, 2003.
  Download:      
• S. Dubnov, R. El-Yaniv, Y. Gdalyahu, E. Schneidman, N. Tishby and G. Yona. A New Nonparametric Pairwise Clustering Algorithm Based on Iterative Estimation of Distance Profiles. Machine Learning, 47(1):35–61, 2002.
  Download:    
• R. Bekkerman, R. El-Yaniv, N. Tishby and Y. Winter. On feature distributional clustering for text categorization. In Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 146–153, 2001.
  Download:      
• R. El-Yaniv and O. Souroujon. Iterative Double Clustering for Unsupervised and Semi-Supervised Learning. In Advances in Neural Information Processing Systems (NIPS) 14, pp. 1025–1032, MIT Press, Cambridge, MA, 2001.
  Download:      
• R. El-Yaniv, S. Fine and N. Tishby. Agnostic Classification of Markovian sequences. In Proceedings of Neural Information Processing Systems (NIPS), pp. 465–471, MIT Press, 1997.
  Download:    

Feature Selection/Generation

• R. Bekkerman, R. El-Yaniv, N. Tishby and Y. Winter. Distributional Word Clusters vs. Words for Text Categorization. Journal of Machine Learning Research, 3:1183–1208, 2003.
  Download:      
• Z. Nevo and R. El-Yaniv. On Online Learning of Decision Lists. Journal of Machine Learning Research (JMLR), 3:271–301, October 2002.
  Download:      
• R. Bekkerman, R. El-Yaniv, N. Tishby and Y. Winter. On feature distributional clustering for text categorization. In Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 146–153, 2001.
  Download:      

Text Categorization

• R. Bekkerman, R. El-Yaniv and A. McCallum. Multi-Way Distributional Clustering via Pairwise Interactions. In Proceedings of the 22nd International Conference on Machine Learning (ICML), pp. 41–48, 2005.
  Download:      
• R. El-Yaniv and N. Etzion-Rosenberg. Hierarchical Multiclass Decompositions with Application to Authorship Determination. Technical Report CS-2004-15, Technion - Israel Institute of Technology, 2004.
  Download:      
• R. Bekkerman, R. El-Yaniv, N. Tishby and Y. Winter. Distributional Word Clusters vs. Words for Text Categorization. Journal of Machine Learning Research, 3:1183–1208, 2003.
  Download:      
• R. Bekkerman, R. El-Yaniv, N. Tishby and Y. Winter. On feature distributional clustering for text categorization. In Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 146–153, 2001.
  Download:      
• R. El-Yaniv and O. Souroujon. Iterative Double Clustering for Unsupervised and Semi-Supervised Learning. In Advances in Neural Information Processing Systems (NIPS) 14, pp. 1025–1032, MIT Press, Cambridge, MA, 2001.
  Download:      

Portfolio Selection and Trading

• A. Borodin, R. El-Yaniv and V. Gogan. Can We Learn to Beat the Best Stock. Journal of Artificial Intelligence Research, 21:579–594, May 2004.
  Download:  
• A. Borodin, R. El-Yaniv and V. Gogan. Can We Learn to Beat the Best Stock. In Advances in Neural Information Processing Systems (NIPS) 16, pp. 345–352, MIT Press, Cambridge, MA, 2003.
  Download:      
• R. El-Yaniv, A. Fiat, R.M. Karp and G. Turpin. Optimal Search and One-Way Trading Online Algorithms. Algorithmica, 30(1):101–139, 2001.
  Download:    
• A. Borodin, R. El-Yaniv and V. Gogan. On the Competitive Theory and Practice of Portfolio Selection (Extended Abstract). In Proceedings of the 4th Latin American Symposium on Theoretical Informatics (LATIN'00), pp. 173–196, 2000.
  Download:    
• A. Chou, J. Cooperstock, R. El-Yaniv, M. Klugerman and T. Leighton. The Statistical Adversary Allows Optimal Money-Making Trading Strategies. In Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 467–476, 1995.
  Download:      
• R. El-Yaniv, A. Fiat, R.M. Karp and G. Turpin. Competitive Analysis of Financial Games. In IEEE Symposium on Foundations of Computer Science (FOCS), pp. 327–333, 1992.
  Download:    

Computational Finance

• A. Borodin, R. El-Yaniv and V. Gogan. Can We Learn to Beat the Best Stock. Journal of Artificial Intelligence Research, 21:579–594, May 2004.
  Download:  
• A. Borodin, R. El-Yaniv and V. Gogan. Can We Learn to Beat the Best Stock. In Advances in Neural Information Processing Systems (NIPS) 16, pp. 345–352, MIT Press, Cambridge, MA, 2003.
  Download:      
• R. El-Yaniv, A. Fiat, R.M. Karp and G. Turpin. Optimal Search and One-Way Trading Online Algorithms. Algorithmica, 30(1):101–139, 2001.
  Download:    
• A. Borodin, R. El-Yaniv and V. Gogan. On the Competitive Theory and Practice of Portfolio Selection (Extended Abstract). In Proceedings of the 4th Latin American Symposium on Theoretical Informatics (LATIN'00), pp. 173–196, 2000.
  Download:    
• R. El-Yaniv, R. Kaniel and N. Linial. Competitive Optimal Online Leasing. Algorithmica, 25(1):116–140, 1999.
  Download:  
• R. El-Yaniv. Competitive Solutions for Online Financial Problems. ACM Computing Surveys, 30(1):28–69, ACM Press, 1998.
  Download:  
• R. El-Yaniv and R.M. Karp. Nearly Optimal Competitive Online Replacement Policies. Mathematics of Operations Research, 22(4):814–839, 1997.
  Download:    
• A. Chou, J. Cooperstock, R. El-Yaniv, M. Klugerman and T. Leighton. The Statistical Adversary Allows Optimal Money-Making Trading Strategies. In Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 467–476, 1995.
  Download:      
• R. El-Yaniv and R.M. Karp. The Mortgage Problem. In 2nd Israel Symposium on Theory of Computing and Systems, pp. 304–312, 1993.
  Download:  
• R. El-Yaniv, A. Fiat, R.M. Karp and G. Turpin. Competitive Analysis of Financial Games. In IEEE Symposium on Foundations of Computer Science (FOCS), pp. 327–333, 1992.
  Download:    

Competitive Analysis

• A. Borodin, R. El-Yaniv and V. Gogan. Can We Learn to Beat the Best Stock. Journal of Artificial Intelligence Research, 21:579–594, May 2004.
  Download:  
• A. Borodin, R. El-Yaniv and V. Gogan. Can We Learn to Beat the Best Stock. In Advances in Neural Information Processing Systems (NIPS) 16, pp. 345–352, MIT Press, Cambridge, MA, 2003.
  Download:      
• R. Bachrach, R. El-Yaniv and M. Reinstaedtler. On the Competitive Theory and Practice of List Accessing Algorithms. Algorithmica, 32:201–246, 2002.
  Download:      
• R. El-Yaniv, A. Fiat, R.M. Karp and G. Turpin. Optimal Search and One-Way Trading Online Algorithms. Algorithmica, 30(1):101–139, 2001.
  Download:    
• A. Borodin, R. El-Yaniv and V. Gogan. On the Competitive Theory and Practice of Portfolio Selection (Extended Abstract). In Proceedings of the 4th Latin American Symposium on Theoretical Informatics (LATIN'00), pp. 173–196, 2000.
  Download:    
• A. Borodin and R. El-Yaniv. On Randomization in On-Line Computation. Information and Computation, 150(2):244–267, 1999.
  Download:  
• R. El-Yaniv, R. Kaniel and N. Linial. Competitive Optimal Online Leasing. Algorithmica, 25(1):116–140, 1999.
  Download:  
• A. Borodin and R. El-Yaniv. Online Computation and Competitive Analysis, Cambridge University Press, 1998.
  Download:  
• R. El-Yaniv. Competitive Solutions for Online Financial Problems. ACM Computing Surveys, 30(1):28–69, ACM Press, 1998.
  Download:  
• R. Bachrach and R. El-Yaniv. Online list Accessing Algorithms and Their Applications: Recent Empirical Evidence. In Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms (SODA), pp. 53–62, 1997.
  Download:    
• A. Borodin and R. El-Yaniv. On Randomization in On-Line Computation. In Proceedings of the 12th Annual IEEE Conference on Computational Complexity (CCC '97), pp. 226–238, 1997.
  Download:    
• R. El-Yaniv and R.M. Karp. Nearly Optimal Competitive Online Replacement Policies. Mathematics of Operations Research, 22(4):814–839, 1997.
  Download:    
• R. El-Yaniv. Is it Rational to be Competitive? On the Decision Theoretic Foundations of the Competitive Ratio. Technical Report 113, Hebrew University of Jerusalem, Center for Rationality and Interactive Decision Theory, 1996.
  Download:  
• R. El-Yaniv. There are Infinitely Many Competitive-Optimal Online List Accessing Algorithms. Technical Report 103, Hebrew University of Jerusalem, Center for Rationality and Interactive Decision Theory, 1996.
  Download:  
• A. Chou, J. Cooperstock, R. El-Yaniv, M. Klugerman and T. Leighton. The Statistical Adversary Allows Optimal Money-Making Trading Strategies. In Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 467–476, 1995.
  Download:      
• R. El-Yaniv and J. Kleinberg. Geometric Two-Server Algorithms. Information Processing Letters, 53(6):355–358, 1995.
  Download:    
• R. El-Yaniv and R.M. Karp. The Mortgage Problem. In 2nd Israel Symposium on Theory of Computing and Systems, pp. 304–312, 1993.
  Download:  
• R. El-Yaniv, A. Fiat, R.M. Karp and G. Turpin. Competitive Analysis of Financial Games. In IEEE Symposium on Foundations of Computer Science (FOCS), pp. 327–333, 1992.
  Download:    

Texture Analysis

• S. Dubnov, Z. Bar-Joseph, R. El-Yaniv, D. Lischinski and M. Werman. Synthesizing Sound Textures through Wavelet Tree Learning. IEEE Computer Graphics and Applications, 22(4):38–48, 2002.
  Download:    
• Z. Bar-Joseph, R. El-Yaniv, D. Lischinski and M. Werman. Texture Mixing and Texture Movie Synthesis Using Statistical Learning. IEEE Transactions on Visualization and Computer Graphics, 7(2):120–135, 2001.
  Download:    
• Z. Bar-Joseph, S. Dubnov, R. El-Yaniv, D. Lischinski and M. Werman. Statistical Learning of Granular Synthesis Parameters with Applications for Sound Texture Synthesis. In Proceedings of the 1999 International Computer Music Conference (ICMC), pp. 178–181, 1999.
  Download:  
• S. Dubnov, G. Assayag and R. El-Yaniv. Universal classification applied to musical sequences. In Proceedings of the 1998 International Computer Music Conference (ICMC), pp. 332–340, 1998.
  Download:  

Fault Tolerant Distributed Computation

• M. Ben-Or and R. El-Yaniv. Optimally-Resilient Interactive Consistency in Constant Time. Distributed Computing, 4(16):249–262, 2003.
  Download:  
• E. Anagnostou, R. El-Yaniv and V. Hadzilacos. Memory Adaptive Self-Stabilizing Protocols. In Proceedings of the 6th International Workshop on Distributed Algorithms, pp. 203–220, Springer-Verlag, 1992.
  Download:  
• E. Anagnostou and R. El-Yaniv. More on the Power of Random Walks: Uniform Self-Stabilizing Randomized Algorithms. In Proceedings of the 5th International Workshop on Distributed Algorithms, pp. 31–51, Springer-Verlag, 1991.
  Download:  

Bioinformatics

• I. Sharon, A. Birkland, K. Chang, R. El-Yaniv and G. Yona. Correcting BLAST E-values for Low-Complexity Segments. Journal of Computational Biology, 12(7):978–1001, 2005.
  Download:    

Medical Diagnosis

• A. Brook, R. El-Yaniv, E. Isler, R. Kimmel, R. Meir and D. Peleg. Breast Cancer Diagnosis From Biopsy Images Using Generic Features and SVMs. Technion - Israel Institute of Technology, 2006.
  Download:  

Single-Class Classification

• R. El-Yaniv and M. Nisenson. Optimal Single-Class Classification Strategies. In Advances in Neural Information Processing Systems (NIPS) 20, MIT Press, Cambridge, MA, 2006.
  Download:  

Multi-Class Classification

• R. El-Yaniv, D. Pechyony and E. Yom-Tov. Superior Multiclass Classification Through Margin-Optimized Single Binary Problem. Technical Report H-0243, IBM Research Report, 2006.
  Download:  

Compression

• R. Begleiter and R. El-Yaniv. Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition. Journal of Machine Learning Research, 7:379–411, 2006.
  Download:  

Other

• G. Shakhnarovich, R. El-Yaniv and Y. Baram. Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML), pp. 521–528, 2001.
  Download:      

Generated by bib2html on Nov 23, 2006. bib2html was written by Patrick Riley.