In privacy-preserving data mining (PPDM), a widely used method for achieving data mining goals while preserving privacy is based on k-anonymity. This method, which protects subject-specific sensitive data by anonymizing it before it is released for data mining, demands that every tuple in the released table should be indistinguishable from no fewer than k subjects. The most common approach for ...

We present a dynamic branching scheme for set partitioning problems. The idea is to trace features of the underlying MIP model and to base search decisions on the features of the current subproblem to be solved. We show how such a system can be trained efficiently by introducing minimal learning bias that traditional model-based machine learning approaches rely on. Experiments on a highly heter...

Metaheuristic algorithms, such as simulated annealing, tabu search and evolutionary algorithms, are popular techniques for solving optimization problems when exact methods are not practical. For example, the run times required to obtain exact solutions to many common combinatorial problems grow exponentially (or worse) with the problem size, and as a result, solving even a relatively modest siz...

The role of aggregation in natural language generation is to combine two or more linguistic structures into a single sentence. The task is crucial for generating concise and readable texts. We present an efficient algorithm for automatically learning aggregation rules from a text and its related database. The algorithm treats aggregation as a set partitioning problem and uses a global inference...

The design of a transfer line is considered. This line is used for a repetitive execution of a given set of operations to produce identical items. The line is composed of a sequence of workstations equipped with processing modules (blocks). Each block performs specific operations. The machined items move along the workstations in the same direction. There is the same cost associated with each w...

A vector enhancement of Said and Pearlman’s Set Partitioning in Hierarchical Trees (SPIHT) methodology, named VSPIHT, has recently been proposed for embedded wavelet image compression. While the VSPIHT algorithm works better than scalar SPIHT for most images, a common vector dimension to use for coding an entire image may not be optimal. Since statistics vary widely within an image, a greater e...

The packing lemma of Haussler states that given a set system (X,R) with bounded VC dimension, if every pair of sets in R have large symmetric difference, then R cannot contain too many sets. Recently it was generalized to the shallow packing lemma, applying to set systems as a function of their shallow-cell complexity. In this paper we present several new results and applications related to pac...

Abshacl This paper proposes , B novel orthogonal hop set partitioning (OHSP) scheme aimed at reducing the collisions between piconets at the hop level, by pariitioning the original Bluetooth hop band into five orthogonal sub-hop sets. To support OHSP, an orthogonal hop sets construction method and enhanced synthesizer structure are presented. In each piconet, the master randomly and independent...

In this paper, we describe an efficient GA representation scheme for solving the setpartitioning problem (SPP). The SPP is an important class of combinatorial optimization problem that may be found in many industrial/business applications. The paper introduces a group representation scheme in a genetic search where columns of the partition matrix (problem space) with the same characteristics ar...

In this paper, to conquer the scalability issue of evolvable hardware (EHW), we introduce a novel system-decomposition-strategy which realizes training set partition in the intrinsic evolution of a non-truth table based 32 characters classification system. The new method is expected to improve the convergence speed of the proposed evolvable system by compressing fitness value evaluation period ...