Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing wi...

In this paper, we address the task of learning models for predicting structured outputs. We consider both global and local predictions of structured outputs, the former based on a single model that predicts the entire output structure and the latter based on a collection of models, each predicting a component of the output structure. We use ensemble methods and apply them in the context of pred...

A new message authentication code (MAC) is described that exploits the tree structure present in many modern document formats, e.g. SGML and XML. The new code supports incremental updating of the cryptographic checksum in the process of making incremental changes to the document. Theoretical bounds on the probability of a successful substitution attack are derived. Through experimental results ...

Attribute value types play an important role in mostly every datamining task. Most learners, for instance, are restricted to particular value types. The usage of such learners is just possible after special forms of preprocessing. RapidMiner most commonly distinguishes between nominal and numerical values which are well-known to every RapidMineruser. Although, covering a great fraction of attri...

Given a large collection of tree-structured objects (e.g., XML documents), the similarity join finds the pairs of objects that are similar to each other, based on a similarity threshold and a tree edit distance measure. The state-ofthe-art similarity join methods compare simpler approximations of the objects (e.g., strings), in order to prune pairs that cannot be part of the similarity join res...

In multicriteria decision problems many values must be assigned, such as the importance of the different criteria and the values of the alternatives with respect to subjective criteria. Since these assignments are approximate, it is very important to analyze the sensitivity of results when small modifications of the assignments are made. When solving a multicriteria decision problem, it is desi...

subject to q(f |u) = ∏ i q(fi|u) and ∫ dfiq(fi|u) = 1. It is noted that KL(a||b) is the measurement of information “lost” when using b to approximate a. It was argued in [1] that it is appropriate to use this KL divergence as an approximation measure since we are trying to find a sparse representation u and its relationship with f to approximate p by q. The KL divergence above can be expanded a...

This support system for drawing tree-structured diagrams, which is implemented in Prolog and a commercial constraint package, enables a user to nd a layout condition adequate to the drawing purpose. Using meta-programming, it automatically produces a corresponding layout program that generates a constraint logic program (CLP) for deriving a layout solution under the selected layout condition an...

Tree-structures have been proposed for both the construction of block ciphers by Kam and Davida 7], and self-synchronous stream ciphers by K uhn 9]. Attacks on these ciphers have been given by An-derson 2] and Heys and Tavares 6]. In this paper it is demonstrated that a more eecient attack can be conducted when the underlying Boolean functions for the cells are known. It is shown that this atta...