There are three phases in the life of a decision problem, specification, solution, and representation of solution. The specification and solution phases are off-line, while the represention of solution often shall serve an on-line situation with rather tough constraints on time and space. One of the advantages of influence diagrams (IDs) is that for small decision problems, the distinction betw...

Compiling graphical models has recently been under intense investigation, especially for probabilistic modeling and processing. We present here a novel data structure for compiling weighted graphical models (in particular, probabilistic models), called AND/OR Multi-Valued Decision Diagram (AOMDD). This is a generalization of our previous work on constraint networks, to weighted models. The AOMD...

Today existing speech recognisers differ not only in their technology from single word to natural language understanding, from hardware based and software-only solutions but also in the recognition accuracy under realtime conditions in the whole variety of environments and networks. Standardised APIs for a defined state diagram of recognition process are the key requirement for integrating diff...

Recent work in the field of probabilistic inference demonstrated the efficiency of weighted model counting (WMC) engines for exact inference in propositional and, very recently, first order models. To date, these methods have not been applied to decision making models, propositional or first order, such as influence diagrams, and Markov decision networks (MDN). In this paper we show how this te...

power system overvoltages due to switching, lightning and other disturbances are the main problem for designers of the power transformers. once some frequencies of the incoming surges match with some of the natural frequencies of transformer winding, the resonance phenomenon is expected in transformer winding. the resonant overvoltages may destroy the insulation between turns and cause to insul...

In decision-theoretic planning, the problem of planning under uncertainty is formulated as a multidimensional, or factoredMDP. Traditional dynamic programming techniques are ine cient for solving factored MDPs whose state and action spaces are exponential in the number of the state and action variables, correspondingly. We focus on exploiting problems' structure imposed by variable independence...

Kernel canonical correlation analysis (CCA) is a nonlinear extension of CCA, which aims at extracting information shared by two random variables. In this paper, a new notion of conditional kernel CCA is introduced. Conditional kernel CCA aims at analyzing the effect of variable Z to the dependence between X and Y . Rates of convergence of an empirical normalized conditional cross-covariance ope...

The normalized least-mean-square (NLMS) adaptive filter is widely used in system identification. In this paper, we develop an optimized NLMS algorithm, in the context of a state variable model. The proposed algorithm follows a joint-optimization problem on both the normalized step-size and regularization parameters, in order to minimize the system misalignment. Consequently, it achieves a prope...

Major and trace element data are presented for Quaternary basalts from Butajira-Kibet area, close to the western escarpment of Central Main Ethiopian Rift investigate petrogenetic processes involved nature mantle source compositions. The indicate that mildly alkaline characterized by moderate high contents MgO (6.85-9.00 wt. %) TiO2 (2.40-2.92 %). In primitive mantle-normalized multi-element di...