E. Boros, P. L. Hammer, and J. N. Hooker, Predicting cause-effect relationships from incomplete discrete observations, SIAM Journal on Discrete Mathematics 7 (1994) 531543. Home/Search Document Details and Download
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A Continuous Approach to Inductive Inference - Kamath (1992) (18 citations) (Correct)
....good topological properties, such as having connected level sets, which has led to successful interior point methods for several problems, e.g. 12] 9] 13] 18] Guided by these results, we investigate the application of a similar approach for inductive inference. For related work, see e.g. [2], 5] and [25] Before we continue, we require some definitions. Consider the Boolean function F : f0; 1g n f0; 1g. An element of the domain of F is called a minterm of F . The set of minterms for which F evaluates to 1 (0) is called the on set (off set) An incompletely specified Boolean ....
E. Boros, P.L. Hammer, and J.N. Hooker. Predicting cause-effect relationships from incomplete discrete observations. Technical report, RUTCOR, Rutgers University, Piscataway, NJ, 1991.
Extensions of Partially Defined Boolean Functions with.. - Boros, Ibaraki, al. (1996) Self-citation (Boros) (Correct)
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E. Boros, P. L. Hammer, and J. N. Hooker, Predicting cause-effect relationships from incomplete discrete observations, SIAM Journal on Discrete Mathematics 7 (1994) 531543.
Boolean Analysis of Incomplete Examples - Boros, Ibaraki, al. (1996) Self-citation (Boros) (Correct)
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E. Boros, P. L. Hammer, and J. N. Hooker, Predicting cause-effect relationships from incomplete discrete observations, SIAM Journal on Discrete Mathematics 7 (1994) 531543.
Boolean Regression - Boros, Hammer, Hooker (1994) Self-citation (Boros Hammer Hooker) (Correct)
....component, whether to grant someone government benefits, and so on. A related class of applications involve the prediction of a boolean outcome on the basis of boolean data. We may, for instance, wish to predict whether a substance is carcinogenic on the basis of some tests we perform on it [3]. Each test has a boolean outcome: positive or negative. The data set consists of test results for a number of substances that were also investigated clinically for carcinogenicity (again a boolean outcome) Noisy data are possible, since the clinical trials could be misleading. The object is ....
....In such cases one can encode many valued attributes using two or more boolean variables, and one can develop a different boolean function for each possible outcome. The resulting predictions, however, are not necessarily the same that result from using a single nonboolean function. 4 In [3] we take a first step toward solving the nonboolean case; we show how to find an error minimizing fit with a monotone nonboolean function by solving an easy network flow problem, provided the possible values of the function have an interval order. But nonboolean functions need further ....
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Boros, E., P. L. Hammer and J. N. Hooker, Predicting cause-effect relationships from incomplete discrete observations, to appear in SIAM Journal of Discrete Mathematics.
Mathematical Programming Methods for Reasoning under Uncertainty - Hooker (1991) Self-citation (Hooker) (Correct)
....of these topics can be found in [1, 8] We should remark in passing that mathematical programming methods can also be applied to inductive reasoning, which is important for the construction of expert systems and other rule bases. Some of these methods are deterministic [35, 23] but one approach [5, 6] infers rules from noisy data. It treats inductive inference as a statistical regression problem in which the fitted formula is a logical rather than a numerical formula. See [5] for a readable introduction. 2 Probabilistic Logic Probabilistic logic is the result of George Boole s effort to ....
Boros, E., P. L. Hammer, and J. N. Hooker, Predicting cause-effect relationships from incomplete discrete observations, working paper 1991-22, Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, PA 15213 USA, 1991.
Logical Inference and Polyhedral Projection - Hooker (1992) Self-citation (Hooker) (Correct)
....R Jeroslow, G. Gallo, R. Rago and J. Hooker have developed new methods for inference in first order predicate logic [15, 34, 30] Chandru and Hooker have proposed a set covering model for inference in Dempster Shafer theory [9] Inductive logic has been addressed with pseudo boolean optimization [4, 5], integer programming [47] and interior point methods [37] For more complete surveys of the research described above, see [7, 9, 23, 25] ae 4 Logical Projection 4.1 The Projection Problem Given a vector t = t 1 ; t n ) and an index set K = f1; kg with k n, we say that t K ....
E. Boros, P. L. Hammer, and J. N. Hooker, Predicting cause-effect relationships from incomplete discrete observations, working paper 1991-22, Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, PA 15213 USA.
Monotone Boolean Function Learning Techniques Integrated With.. - Evangelos (Correct)
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Boros E., Hammer, P., and Hooker, J. (1993), "Predicting cause-effect relationships from Incomplete Discrete Observations", Rutgers center for operations research, RUTCOR research report RRR 9-93, Rutgers University,USA.
Relation between Protein Structure, Sequence Homology and.. - al. (1995) (Correct)
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Boros,E., Hammer,P.L. and Hooker,J.N. (1994) Predicting Cause-Effect Relationships from Incomplete Discrete Observations. SIAM Journal on Discrete Mathematics, 7-4, 531--543.
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