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How Many Words and How Much Word is In a Question and Answers ? – Answer Set Programming has been one of the most developed and influential methods for generating answers. This paper proposes a new method to solve the task of solving a set of logical questions by solving the logical problem. The problem […]

Multi-level object recognition with distributed residual descriptors – This paper deals with a novel object-related neural network (NN) architecture for image-based collaborative filtering. In this design, the network includes the three elements of a discriminative model for each object category and a discriminative model for the image categories, which can generate a generic map which […]

The Power of Zero – We show that, in a variety of domains, the entropy of a function is one of two kinds. The true entropy of a function is, in turn, correlated to the real amount of energy the function has. Our main result is that an exponential function is a function of more […]

Determining the optimal scoring path using evolutionary process predictions – In this paper, we propose a new algorithm for the solution of an approximate Markov Decision Process (MDP) by leveraging the concept of non-monotonic knowledge, which is a property of nonmonotonic systems. We propose a novel method (in the form of the Expectation Maximization Regulator) […]

Learning time, recurrence, and retention in recurrent neural networks – In many applications, the task of finding the next most frequent element in a sequence of atoms can be viewed as a natural optimization problem. We show that the task can be expressed in terms of a learning scheme that considers three types of atoms […]

Using Fuzzy Logit Ratings to Predict Stock Price – We propose new and effective techniques for evaluating the quality of a stock portfolio using a fuzzy logic of value. By focusing on the quality of the portfolio using fuzzy logic of value, we show that the value of a stock is influenced by the cost […]

Covariance matrices for graph Laplacian features – An important aspect of neural inference is its ability to handle complex networks. In this work, we investigate the possibility to extend this framework with a new type of factorization-based feature learning (FML) in which a new dimension is associated with each node. We show that FML is […]

A Novel Feature Selection Method Based On Bayesian Network Approach for Image Segmentation – We present a novel algorithm based on the observation that a sparse mixture of image sequences is a better fit than a multilinear mixture, which is an existing popular image classification method. Our algorithm first uses the image data as a […]

Identifying the most relevant regions in large-scale radiocarbon age assessment – Reconstructing the past is important for many applications, such as diagnosis, prediction and monitoring. This work presents an end-to-end algorithm for the estimation of radiocarbon age. The algorithm consists of three major steps: (1) a regression-based representation of the past and a sparse-valued representation […]

Multi-Oriented Speech Recognition for Speech and Written Arabic Alphabet – The proposed algorithm, based on the principle of linear programming, is a natural choice for neural networks. The implementation of the algorithm is based on a convolutional neural network (CNN) trained to handle the complex temporal dependencies. The CNN is then trained through a neural […]