In our ICML paper titled “On optimization methods for deep learning”, we discussed the standard and sparse autoencoder model. However, due to space limitations in our paper, we were not able to present further details about the bases learned by the sparse autoencoder model, compare the standard autoencoder with the Hessian Free approach as described in (Martens, 2010) and analyze in detail the ...

In computer science, one is interested mainly in nite objects. Insofar as innnite objects are of interest, they must be computable, i.e., recursive, thus admitting an eeective nite representation. This leads to the notion of a recursive graph, or, more generally, a recursive structure , model or data base. In this paper we summarize our recent work on recursive structures and data bases, includ...

Inconsistency measures help analyzing contradictory knowledge bases and resolving inconsistencies. In recent years several measures with desirable properties have been proposed, but often these measures correspond to combinatorial or nonconvex optimization problems that are hard to solve in practice. In this paper, I study a new family of inconsistency measures for probabilistic knowledge bases...

Designing efficient physical data bases is a complex activity, involving the consideration of a large number of factors. Mathematical programming-based optimization models for physical design make many simplifying assumptions; thus, their applicability is limited. In this article, we show that heuristic algorithms can be successfully used in the development of very good, physical data base desi...

This paper shows possibility of extraction Social, Group and Individual Mind from Multiple Agents Rule Bases. Types those Rule bases are selected as two fuzzy systems, namely Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are describing (modeling) agent behavior. Modifying of agent behavior in the time varying environment will be provided by learning fuzzyneural networks and optimiza...

This paper strongly emphasizes the approach for query optimization which is a frame work model for distributed computing environment systems. We have two popular methods for query optimization. One which is traditional which follows the stages like query planning, deployment and adaptation. The second one which is our main experimental approach which follows the stages like query planning and d...