Dots-And-Boxes is a well-known and widely-played combinatorial game. While the rules of play are very simple, the state space for even very small games is extremely large, and finding the outcome under optimal play is correspondingly hard. In this paper we introduce a Dots-And-Boxes solver which is significantly faster than the current state-of-the-art: over an order-of-magnitude faster on seve...

In this work we investigate several issues in order to improve the performance of probabilistic estimation trees (PETs). First, we derive a new probability smoothing that takes into account the class distributions of all the nodes from the root to each leaf. Secondly, we introduce or adapt some new splitting criteria aimed at improving probability estimates rather than improving classification ...

Internet Traffic classification is vital for various network activities such as detection of malware. Security is major issue of concern which accounts for the reputation and reliability of system. Malware effects the system adversely results in data loss or abnormal functioning. Hence, detection and as well as removal of malware is crucial. Combining set of classifiers called as ensembling pro...

We describe an experimental study of pruning methods for decision tree classiiers when the goal is minimizing loss rather than error. In addition to two common methods for error minimization, CART's cost-complexity pruning and C4.5's error-based pruning, we study the extension of cost-complexity pruning to loss and one pruning variant based on the Laplace correction. We perform an empirical com...

Abstract Recently, many studies have been carried out on model compression to handle the high computational cost and memory footprint brought by implementation of deep neural networks. In this paper, convolutional networks is constructed as a multiobjective optimization problem with two conflicting objectives, reducing size improving performance. A novel structured pruning method called Convent...

The multiple knapsack problem (MKP) is a classical combinatorial optimization problem. A recent algorithm for some classes of the MKP is bin-completion, a bin-oriented, branch-and-bound algorithm. In this paper, we propose path-symmetry and path-dominance, which are instances of the symmetry detection by dominance detection approach for pruning symmetric nodes in the MKP branch-and-bound search...

Attribute grammars permit the specification of static semantics in an applicative and modular fashion, and thus are a good basis for syntaxdirected editors. Such editora represent progrsma as attributed trees, which are modified by operations such as subtree pruning and grafting. After each modification, a subset of attributes, AFFEGTED* requires new values. Membership in AFFEGTED is not known ...

In model-driven engineering, the aim of design space exploration (DSE) is to generate a set of design candidates that satisfy a given set of constraints and requirements, and are optimal with respect to some criteria. In multi-paradigm modeling it is not uncommon to perform a variety of computationally expensive analyses as part of such an exploration process. However, existing DSE techniques d...

Default unification operations combine strict information with information from one or more defeasible feature structures. Many such operations require finding the maximal subsets of a set of atomic constraints that are consistent with each other and with the strict feature structure, where a subset is maximally consistent with respect to the subsumption ordering if no constraint can be added t...