Fabio Cozman's List of Selected Publications

Fabio Cozman's Selected Publications (as of April 2009)

You can find a complete list elsewhere; here is a list of publications that contain relatively finished reports on relatively complete research. Basically it contains several of my journal papers plus a selection of conference papers and a few technical reports.

Note that there are interesting papers in the complete list whose content has appeared in papers in this list, and there are nice papers in the complete list whose content is still in development.

Book chapters

F. G. Cozman, I. Cohen, Risks of semi-supervised learning, in Olivier Chapelle, Bernhard Scholkopf, Alexander Zien (editors), Semi-Supervised Learning, pp. 55-70, 2006. Preprint available.

Journal articles

Jaime Shinsuke Ide, Fabio G. Cozman. Approximate algorithms for credal networks with binary variables, International Journal of Approximate Reasoning, v. 48, p. 275-296, 2008. Preprint available.
Fabio G. Cozman, Cassio Polpo de Campos, José Carlos Ferreira da Rocha. Probabilistic logic with independence, International Journal of Approximate Reasoning, v. 49, p. 3-17, 2008. Preprint available.
C. Polpo de Campos, F. G. Cozman. Computing lower and upper expectations under epistemic independence, International Journal of Approximate Reasoning, 44(3):244-260, 2007. Preprint available.
P. Vicig, M. Zaffalon, F. G.Cozman. Notes on "Notes on conditional previsions", International Journal of Approximate Reasoning, 44(3):358-365, 2007. Preprint available.
F. G. Cozman, P. Walley. Graphoid properties of epistemic irrelevance and independence, Annals of Mathematics and Artificial Intelligence, 45:173-195, 2005. Preprint available.
N. Sebe, I. Cohen, F. G. Cozman, T. Gevers, T. S. Huang. Learning probabilistic classifiers for human-computer interaction applications, Multimedia Systems, 10(6):484-498, 2005. Preprint available.
F. T. Ramos, F. G. Cozman. Anytime anyspace probabilistic inference, International Journal of Approximate Reasoning, 38:53-80, 2005. Preprint available.
F. G.Cozman. Graphical models for imprecise probabilities, Journal of International Journal of Approximate Reasoning, 39(2-3):167-184, 2005. Preprint available.
J. C. F. da Rocha, F. G. Cozman. Inference in credal networks: branch-and-bound methods and the A/R+ algorithm, International Journal of Approximate Reasoning, 39(2-3):279-296, 2005. Preprint available.
I. Cohen, F. G. Cozman, N. Sebe, M. C. Cirelo, T. S. Huang. Semisupervised learning of classifiers: Theory, algorithms, and their application to human-computer interaction, IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(12):1553-1568, 2004. Preprint available.
F. G. Cozman, E. Krotkov, C. E. Guestrin. Outdoor Visual Position Estimation for Planetary Rovers, Autonomous Robots, vol. 9, pp. 135-150, 2000. Preprint available.
F. G. Cozman. Credal networks, Artificial Intelligence Journal, vol. 120, pp. 199-233, 2000. Preprint available.
F. G. Cozman. Computing posterior upper expectations, International Journal of Approximate Reasoning, vol. 24, pp. 191-205, 2000. Preprint available.
F. G. Cozman. Calculation of Posterior Bounds Given Convex Sets of Prior Probability Measures and Likelihood Functions, Journal of Computational and Graphical Statistics, vol. 8(4), pp. 824-838, 1999. Preprint available.

Conferences and symposia

Fabio G. Cozman. Concentration inequalities and laws of large numbers under epistemic irrelevance, Sixth International Symposium on Imprecise Probability: Theories and Applications, 2009. A revised version of the paper presented at the meeting is available.
Fabio G. Cozman, Rodrigo Polastro. Complexity analysis and variational inference for interpretation-based probabilistic description logics, Conference on Uncertainty in Artificial Intelligence, 2009. Preprint available.
Fabio G. Cozman, Rodrigo Bellizia Polastro. Loopy propagation in a probabilistic description logic, Second International Conference on Scalable Uncertainty Management, Lecture Notes in Artificial Intelligence, LNAI 5291, pp. 120-133, Springer, 2008. Preprint available.
Silvio do Lago Pereira, Leliane N. de Barros, Fabio G. Cozman. Strong Probabilistic Planning, Advances in Artificial Intelligence, 7th Mexican International Conference on Artificial Intelligence (MICAI), Lecture Notes in Computer Science 5317, Springer (ISBN 978-3-540-88635-8), pp. 636-652, 2008. Preprint available.
Felipe W. Trevizan, Fabio G. Cozman, Leliane N. de Barros. Mixed Probabilistic and Nondeterministic Factored Planning through Markov Decision Processes with Set-Valued Transitions, Workshop on A Reality Check for Planning and Scheduling Under Uncertainty at the Eighteenth International Conference on Automated Planning and Scheduling (ICAPS), 2008. Preprint available.
Felipe W. Trevizan, Fabio G. Cozman, Leliane N. de Barros. Planning under Risk and Knightian Uncertainty, International Joint Conference on Artificial Intelligence, pp. 2023-2028, 2007. Preprint available.
Cassio Polpo de Campos, Fabio Gagliardi Cozman. Inference in credal networks through integer programming, Fifth International Symposium on Imprecise Probability: Theories and Applications, pp. 145-154, Praga, República Tcheca, 2007. Preprint available.
Ricardo Shirota Filho, Fabio Gagliardi Cozman, Felipe Werndl Trevizan, Cassio Polpo de Campos, Leliane Nunes de Barros. Multilinear and integer programming for Markov decision processes with imprecise probabilities, Fifth International Symposium on Imprecise Probability: Theories and Applications, pp. 395-404, Praga, República Tcheca, 2007. Preprint available.
A. Antonucci, M. Zaffalon, J. Ide, F. G. Cozman. Binarization algorithms for approximate updating in credal nets. In L. Penserini, P. Peppas, A. Perini, eds., Proceedings of the Third European Starting AI Researcher Symposium, pp. 120-131, Amsterdam, The Netherlands, IOS Press, 2006.
C. P. de Campos, F. G. Cozman. Belief updating and learning in semi-qualitative probabilistic networks, Conference on Uncertainty in Artificial Intelligence (UAI), pp. 153-160, Edinburgh, United Kingdom, 2005. Preprint available.
D. Kikuti, F. G. Cozman, C. P. de Campos. Partially ordered preferences in decision trees: computing strategies with imprecision in probabilities, IJCAI Workshop on Advances in Preference Handling, Edinburgh, United Kingdom, 2005. Preprint available. PLEASE also note that an errata has been produced, correcting a few mistakes in the paper!
C. P. de Campos, F. G. Cozman. The inferential complexity of Bayesian and credal networks, International Joint Conference on Artificial Intelligence, pp. 1313-1318, Edinburgh, United Kingdom, 2005. Preprint available.
J. S. Ide, F. G. Cozman, F. T. Ramos. Generating random Bayesian networks with constraints on induced width, European Conference on Artificial Intelligence (ECAI), pp. 323-327, IOS Press, Amsterdan, 2004. Preprint available.
F. G. Cozman, C. P. de Campos, J. S. Ide, J. C. F. da Rocha. Propositional and relational Bayesian networks associated with imprecise and qualitative probabilistic assessments, Conference on Uncertainty in Artificial Intelligence, pp. 104-111, AUAI Press, 2004. Preprint available.
C. P. de Campos, F. G. Cozman. Inference in credal networs using multilinear programming, Second Starting AI Researcher Symposium (STAIRS), pp. 50-61, IOS Press, 2004. Preprint available.
J. C. F. da Rocha, F. G. Cozman, C. P. de Campos. Inference in polytrees with sets of probabilities, Conference on Uncertainty in Artificial Intelligence, pp. 217-224, Morgan Kaufmann, 2003. Preprint available.
F. G. Cozman, I. Cohen, M. C. Cirelo. Semi-supervised learning of mixture models, International Conference on Machine Learning, pp. 99-106, 2003. Preprint available.
I. Cohen, N. Sebe, F. G. Cozman, M. C. Cirelo, T. S. Huang. Learning Bayesian network classifiers for facial expression recognition using both labeled and unlabeled data, IEEE Conference on Computer Vision and Pattern Recognition, 2003. Preprint available.
M. Ackermann, F. G. Cozman. Mechanized knee flexion in lower limb orthoses: A prototype and tests, Congresso Brasileiro de Engenharia Mecânica, pp. 83ffs, 2003.
F. G. Cozman. Algorithms for Conditioning on Events of Zero Probability, Fifteenth International Florida Artificial Intelligence Society Conference, pags. 248-252, Pensacola, Florida, United States, 2002. Preprint available.
F. G. Cozman, I. Cohen. Unlabeled Data can Degrade Classification Performance of Generative Classifiers, Fifteenth International Florida Artificial Intelligence Society Conference, pags. 327-331, Pensacola, Florida, United States, 2002. Preprint available.
F. G. Cozman. Constructing Sets of Probability Measures Through Kuznetsov's Independence Condition, Proceedings of the Second International Symposium on Imprecise Probabilities and Their Applications, pags. 104-111, Ithaca, New York, United States, 2001. Preprint available.
F. G. Cozman. Generalizing Variable Elimination in Bayesian Networks, Proceedings of the IBERAMIA/SBIA 2000 Workshops (Workshop on Probabilistic Reasoning in Artificial Intelligence), pp. 27-32, Editora Tec Art, São Paulo, Brazil, 2000. Preprint available.
C. Guestrin; F. G. Cozman; E. Krotkov. Fast Software Image Stabilization with Color Registration, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 19-24, Victoria, Canada, October, 1998.
F. Cozman; E. Krotkov. Depth from Scattering, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Puerto Rico, June, 1997. Preprint available.
F. Cozman; E. Krotkov. Quasi-Bayesian Strategies for Efficient Plan Generation: Application to the Planning to Observe Problem, Proc. Twelfth Conference Uncertainty in Artificial Intelligence, pp. 186-193, 1996. Preprint available.
R. Simmons; E. Krotkov; L. Chrisman; F. Cozman; R. Goodwin; M. Hebert; L. Katragadda; S. Koenig; G. Krishnaswamy; Y. Shinoda; W. Whittaker; and P. Klarer. Experience with Rover Navigation for Lunar-Like Terrains, Proceedings of the Conference on Intelligent Robots and Systems (IROS), pages 441-446, 1995.
F. Cozman; E. Krotkov. Robot Localization using a Computer Vision Sextant, International Conference on Robotics and Automation, pages 106-111, Nagoya, Japan, May 1995. Preprint available.
F. Cozman; E. Krotkov. Truncated Gaussians as Tolerance Sets, Fifth Workshop on Artificial Intelligence and Statistics, Fort Lauderdale Florida, 1995. Preprint available.
F. G. Cozman; P. E. Miyagi. Trajectory Controller for a Mobile Robot using Optimal Control, XI Congresso Brasileiro de Engenharia Mecânica, 3:537-540, São Paulo, SP Brazil, 1991.

Technical reports

F. G. Cozman, T. Seidenfeld. Independence for full conditional measures, graphoids and Bayesian networks, Technical Report from Escola Politécnica da USP, BT/PMR/0711, 2007.
F. G. Cozman. Axiomatizing Noisy-OR, Technical Report from Escola Politécnica da USP, BT/PMR/0409, 2004. This report is an extended version of paper presented at the European Conference on Artificial Intelligence 2004.
F. Cozman and L. Chrisman. Learning Convex Sets of Probability from Data, Technical Report CMU-RI-TR-97-25, Robotics Institute, Carnegie Mellon University, Pittsburgh, 1997.
F. Cozman. An Informal Introduction to Quasi-Bayesian Theory (and Lower Probability, Lower Expectations, Choquet Capacities, Robust Bayesian Methods, etc...) for AI, Technical Report CMU-RI-TR-97-24, Robotics Institute, Carnegie Mellon University, Pittsburgh, 1997.

fgcozman@usp.br