Publications - by Type

• Book • Journal • Refereed Conference • Technical Report •

Book

• A. Borodin and R. El-Yaniv. Online Computation and Competitive Analysis, Cambridge University Press, 1998.
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Journal

• 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.
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• R. El-Yaniv and L. Gerzon. Effective Transductive Learning via Objective Model Selection. Pattern Recognition Letters, 26(13):2104–2115, 2005.
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• 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.
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• Y. Baram, R. El-Yaniv and K. Luz. Online Choice of Active Learning Algorithms. Journal of Machine Learning Research, 5:255–291, March 2004.
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• 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.
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• 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.
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• 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.
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• R. Yaroshinsky, R. El-Yaniv and S. Seiden. How to Better Use Expert Advice. Machine Learning, 55(3):271–309, June 2004.
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• 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.
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• M. Ben-Or and R. El-Yaniv. Optimally-Resilient Interactive Consistency in Constant Time. Distributed Computing, 4(16):249–262, 2003.
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• R. Bachrach, R. El-Yaniv and M. Reinstaedtler. On the Competitive Theory and Practice of List Accessing Algorithms. Algorithmica, 32:201–246, 2002.
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• 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.
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• 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.
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• Z. Nevo and R. El-Yaniv. On Online Learning of Decision Lists. Journal of Machine Learning Research (JMLR), 3:271–301, October 2002.
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• 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.
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• 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.
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• A. Borodin and R. El-Yaniv. On Randomization in On-Line Computation. Information and Computation, 150(2):244–267, 1999.
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• R. El-Yaniv, R. Kaniel and N. Linial. Competitive Optimal Online Leasing. Algorithmica, 25(1):116–140, 1999.
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• R. El-Yaniv. Competitive Solutions for Online Financial Problems. ACM Computing Surveys, 30(1):28–69, ACM Press, 1998.
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• R. El-Yaniv and R.M. Karp. Nearly Optimal Competitive Online Replacement Policies. Mathematics of Operations Research, 22(4):814–839, 1997.
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• R. El-Yaniv and J. Kleinberg. Geometric Two-Server Algorithms. Information Processing Letters, 53(6):355–358, 1995.
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Refereed Conference

• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• R. El-Yaniv and R.M. Karp. The Mortgage Problem. In 2nd Israel Symposium on Theory of Computing and Systems, pp. 304–312, 1993.
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• 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.
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• 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.
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• 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.
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Technical Report

• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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• 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.
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