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Deep learning has greatly improved visual recognition in recent years. However, recent research has shown that there exist many adversarial examples that can negatively impact the performance of such an architecture. This paper focuses on detecting those adversarial examples by analyzing whether they come from the same distribution as the normal examples. Instead of directly training a deep neural...
Symbolic execution is a widely-used program analysis technique. It collects and solves path conditions to guide the program traversing. However, due to the limitation of the current constraint solvers, it is difficult to apply symbolic execution on programs with complex path conditions, like nonlinear constraints and function calls. In this paper, we propose a new symbolic execution tool MLB to handle...
Discovering local geometry of low-dimensional manifold embedded into a high-dimensional space has been widely studied in the literature of machine learning. Counter-intuitively, we will show for the class of signal-independent additive noise, noisy data do not destroy the manifold structure thanks to the blessing of dimensionality. Based on this observation, we propose to reconstruct the manifold...
Classification rule mining has been a very active research topic in data mining and machine learning communities. To effectively cope with this problem, a novel classification rule mining algorithm is proposed by the combination of neighborhood preserving embedding (NPE) and genetic algorithm (GA) in this paper. Experimental results on the UCI data set repository demonstrate that the proposed algorithm...
The support vector machine (SVM) is an algorithm based on structure risk minimizing principle, having high generalization ability. In the course of multi-sensor information fusion of industrial control, sensor has bigger nonlinearity and fuzzy relation between coefficient and relevant parameter. A kind of model and algorithm of multiple sensor information fusion based on the support vector machine...
With the development of the information technology, database security draws more and more attention than before. It is desirable to store data in encrypted form to protect the sensitive data from various attacks. But the efficiency of DBMS will fall as the SQL clauses can not execute over the encrypted data directly. In this paper we propose a secure cipher index with great efficiency over the encrypted...
A visual pattern recognition method based on optimized parallel coordinates is proposed in this paper. We first introduce the traditional theory of parallel coordinates and indicate that parallel coordinates has a potential for classification tasks due to its projective transformation interpretation. Nevertheless, some optimization is needed. The main aim of optimization is to hide the valueless information...
Heuristic hill-climbing search algorithm can do effectively pruning. In practice, it can be used to search a large hypothesis space to get an optimal or an approximate optimal solution. Beam search algorithm retains its advantage in efficiency while reducing the risk of converging to locally optimal hypotheses. Beam search algorithm is widely used in AI field. To k-size beam search, due to only k...
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