State-of-the-art methods of attribute detection from faces almost always assume the presence of a full, unoccluded face. Hence, their performance degrades for partially visible and occluded faces. In this paper, we introduce SPLITFACE, a deep convolutional neural network-based method that is explicitly designed to perform attribute detection in partially occluded faces. Taking several facial se...

Empirical evidence indicates that the training time for the support vector machine (SVM) scales to the square of the number of training data points. In this paper, we introduce the Bayesian committee support vector machine (BC-SVM) and achieve an algorithm for training the SVM which scales linearly in the number of training data points. We verify the good performance of the BC-SVM using several...

In a We use statistical mechanics to study generalization in large committee machines. For an architecture with nonoverlapping receptive fields a replica calculation yields the generalization error in the limit of a large number of hidden units. For continuous weights the generalization error falls off asymptotically inversely proportional to Q, the number of training examples per weight. For b...

In this paper we use various methods for multiple neural network combination in tasks of prepositional phrase at tachment. Experiments with aggregation functions such as unweighted and weighted average, OWA operator, Choquet integral and stacked generalization demonstrate that combining multiple networks improve the estimation of each individual neural network. Using the Ratnaparkhi data set (t...

A natural way to deal with training samples in imbalanced class problems is to prune them removing redundant patterns, easy to classify and probably over represented, and label noisy patterns that belonging to one class are labelled as members of another. This allows classifier construction to focus on borderline patterns, likely to be the most informative ones. To appropriately define the abov...

The dynamics of learning from examples in the K = 3 nonoverlapping committee machine with single presentation of examples is studied. The optimal algorithm, in the sense of mean generalization, is obtained from a variational analysis of the diierential equations which describe the dynamics. The agreement of the theoretical predictions and the results of numerical simulations is excellent. The o...

OBJECTIVES This manuscript assesses safety climate data from the National Machine Guarding Program (NMGP)-a nationwide intervention to improve machine safety. METHODS Baseline safety climate surveys were completed by 2161 employees and 341 owners or managers at 115 businesses. A separate onsite audit of safety management practices and machine guarding equipment was conducted at each business....

Three phases are considered for multiple response optimization (MRO) problems. They are design of experiments, modeling and optimization. Committee machines (CM) as a set of some experts such as some artificial neural networks (ANNs) can be applied for modeling phase. Then, genetic algorithm (GA) determines the final solution with object maximizing the global desirability as optimization phase....

Statistical mechanics is applied to lossy compression using multilayer perceptrons for unbiased Boolean messages. We utilize a treelike committee machine (committee tree) and treelike parity machine (parity tree) whose transfer functions are monotonic. For compression using a committee tree, a lower bound of achievable distortion becomes small as the number of hidden units K increases. However,...