To view the publications from a specific year, select the year from the list below. All are in pdf, unless noted.

• 2009  2008   2007   2006    2005   2004  2003 and before
• Also see motivations and presentations under my recent work page
• Abbreviations for conference and journals names, etc.
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• Discounted Deterministic Markov Decision Processes and Discounted All-Pairs Shortest Paths. O. Madani, M. Thorup, and U. Zwick.   Transactions on Algorithms, 6(32), March 2010.  
• Large-Scale Many-Class Prediction via Flat Techniques. O. Madani and J. Huang.   Workshop on Large-Scale Hierarchical Text Classification at ECIR (associated with the PASCAL Challenge on Hierarchical Text Classification), 2010.
  We obtained top ranks, number one in 5 of 12 evaluation tracks, from among 18 participants!  

• Large-Scale Many-Class Prediction via Flat Techniques. O. Madani and J. Huang.   PASCAL Challenge on Hierarchical Text Classification (short paper), Dec. 2009.  
• Learning When Concepts Abound. O. Madani, M. Connor, and W. Greiner.   Journal of Machine Learning Research (JMLR), 2009. 
• On the Empirical Complexity of Text Classification Problems. O. Madani, H. Raghavan, and R. Jones.   SRI AI Center Technical Report, 2009. 
• Efficient Online Learning and Prediction of Users' Desktop Actions. O. Madani, H. Bui, and E. Yeh.   IJCAI, 2009. 
  • Prediction and Discovery of Users' Desktop Behavior. AAAI Spring Symposiom on Human Behavior Modeling, 2009.
• Discounted Deterministic Markov Decision Processes and Discounted All-Pairs Shortest Paths. O. Madani, M. Thorup, and U. Zwick.   ACM-SIAM SODA, 2009.
   

• Systems Learning for Complex Pattern Problems. O. Madani.  AAAI FSS, Biologically Inspired Cognitive Architectures (BICA), 2008. 
• Error-Driven Generalist+Experts (EDGE): A Multi-stage Ensemble Framework for Text Categorization. J. Huang, O. Madani, and C. Lee Giles.  ACM CIKM, 2008. 
• On Updates that Constrain the Features' Connections During Learning. O. Madani, and J. Huang.  ACM KDD, 2008. 
• Large-Scale Many-Class Learning. O. Madani and M. Connor.  SIAM Conference on Data Mining (SDM). 2008. 

• Exploring Massive Learning via a Prediction System. O. Madani.  AAAI FSS07 (on Computational Approaches to Representation Change During Learning and Development), 2007. 
• Prediction Games in Infinitely Rich Worlds.  O. Madani.  Position paper at AAAI FSS, 2007.
  • Longer technical report on the basic idea/philosophy and various considerations/issues/challenges, 2007.
• Ranked Recall: Efficient Classification by Efficient Learning of Indices that Rank.   O. Madani, M. Connor.  Yahoo! Research Technical Report, 2007.
• Recall Systems: Efficient Learning and Use of Category Indices.   O. Madani, W. Greiner, D. Kempe, and M. Salavatipour.  AISTATS, 2007.
• When will Feature Feedback help?  Quantifying the Complexity of Classification Problems.   H. Raghavan, O. Madani, R. Jones.   IJCAI Workshop on Human in the Loop Computing, 2007.

2006

• Prediction Games in Infinitely Rich Worlds.  O. Madani. 2nd Utility Based Date Mining Workshop (UBDM) at KDD, 2006.
• Learning when Concepts Abound.   O. Madani and W. Greiner. Yahoo! Research Technical Report. May, 2006.
• Active Learning with Feedback on Features and Instances.  H. Raghavan, O. Madani and R. Jones. JMLR, 2006.
• A Large Scale Analysis of Query Logs for Assessing Personalization Opportunities.   S. Wedig and O. Madani. KDD 2006.
• Generating Query Substitutions.  R. Jones, B. Rey, O. Madani, and W. Greiner. WWW 2006.
• Naive Filterbots for Robust Cold-Start Recommendations.  S.T. Park, D. Pennock, O. Madani, N. Good, D. DeCoste.  KDD 2006.
• An Empirical Comparison of Algorithms for Aggregating Expert Predictions.  V. Dani, O. Madani, D. Pennock, S. Sanghai, and B. Galebach. UAI, 2006.

• InterActive Feature Selection.  H. Raghavan, O. Madani and R. Jones. IJCAI, 2005.
• Contextual Recommender Problems.   O. Madani and D. DeCoste. UBDM at  KDD, 2005.
• Biasing Web Search Results for Topic Familiarity.  G. Kumaran, R. Jones, and O. Madani. CIKM, 2005.

• Active Model Selection.  O. Madani, D. J. Lizotte, and R. Greiner. UAI, 2004.
• Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms.  O. Madani, D. Pennock, and G. Flake. Neural Information Processing Systems (NIPS), 2004.
• The Budgeted Multi-Armed Bandit Problem.   O. Madani, D. J. Lizotte, and R. Greiner.  COLT, 2004.
• Empowered Learners!  Manuscript (a summery of some extensions of classical supervised learning, such as active learning), 2004.

• Budgeted Learning of Naive-Bayes Classifiers.  D. J. Lizotte, O. Madani,  and R. Greiner. UAI, 2003.
• On the Undecidability of Probabilistic Planning and Related Stochastic Optimization Problems.   O. Madani, S. Hanks, and A. Condon. AI Journal (AIJ), 2003.
• On Policy Iteration as a Newton's Method and Polynomial Policy Iteration Algorithms .  O. Madani. AAAI, 2002.
• Polynomial Value Iteration Algorithms for Deterministic MDPs.   O. Madani, UAI, 2002.
• Performance of Lookahead Control Policies in the Face of Abstractions and Approximations.   I. Levner, V. Bulitko, O. Madani and R. Greiner. SARA, 2002.
• PhD Thesis: Complexity Results for Infinite-Horizon Markov Decision Processes (abstract in text), 2000.
• Optimal Information Gathering on the Internet with Time and Cost Constraints.   O. Etzioni, S. Hanks, T. Jiang, and O. Madani. SICOMP, 2000.
• On the Undecidability of Probabilistic Planning and Partially Observable Markov Decision Problems.   O. Madani, S. Hanks, and A. Condon. AAAI, 1999.
• Fast and Intuitive Clustering of Web Documents.   O. Zamir, O. Etzioni, O. Madani, R. M. Karp. KDD, 1997.
• Efficient Information Gathering on the Internet.   O. Etzioni, S. Hanks, T. Jiang, R. M. Karp, O. Madani, and O. Waarts, IEEE FOCS, 1996.

Abbreviations of conference names, journals, etc.

• AAAI = National Conference on Artificial Intelligence (also, Association for Advancement of AI)
• ACM = Association for Computing Machinery
• AIJ = Artificial Intelligence Journal
• AISTATS = Conference on Artificial Intelligence and Statistics
• AAAI FSS = AAAI Fall Symposium Series
• CIKM = Conference on Information and Knowledge Management
• COLT = Conference on Learning Theory
• FOCS = IEEE International Conference on Foundations of Computer Science 
• IEEE = Institute of Electrical and Electronics Engineers
• IJCAI = International Joint conference on Artificial Intelligence
• JMLR = Journal of Machine Learning Research
• KDD or SIGKDD = ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
• NIPS = Conference on Neural Information Processing Systems
• SARA = Symposium on Abstraction, Reformulation, and Approximation
• SDM = SIAM (Society of Industrial and Applied Mathematicians) Conference on Data Mining
• SIAM = Society for Industrial and Applied Mathematics
• SICOMP = SIAM Journal on Computing
• SODA = ACM-SIAM Simposium on Discrete Algorithms
• UAI = Conference on Uncertainty in Artificial Intelligence
• UBDM = Utility Based Data Mining (workshop)
• WWW = International World Wide Web Conference

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