The k-nearest neighbor classification method (kNNC) is one of the simplest nonparametric classification methods. The mutual k-NN classification method (MkNNC) is a variant of k-NNC based on mutual neighborship. We propose another variant of k-NNC, the symmetric k-NN classification method (SkNNC) based on both mutual neighborship and one-sided neighborship. The performance of MkNNC and SkNNC dep...

SUMMARY Visual adaptation is a universal phenomenon associated with human visual system. This adaptation affects not only the perception of low-level visual systems processing color, motion, and orientation, but also the perception of high-level visual systems processing complex visual patterns, such as facial identity and expression. Although it remains unclear for the mutual interaction mecha...

In this paper, we evaluate the accuracy and robustness of intensity-based 2D-3D registration for six image similarity measures using clinical gold-standard spine image data from four patients. The goldstandard transformations are obtained using four bone-implanted fiducial markers. The three best similarity measures are mutual information, cross correlation, and gradient correlation. The mean t...

In cross-language information retrieval it is often important to align words that are similar in meaning in two corpora written in different languages. Previous research shows that using context similarity to align words is helpful when no dictionary entry is available. We suggest a new method which selects a subset of words (pivot words) associated with a query and then matches these words acr...

In recent years, there has been a massive growth of regulatory and related information available online. This information is distributed across many different domains creating a problem for accessing and managing this data. This paper proposes a framework to access information across two such domains – patents and court cases. The framework is designed to boost the value of a set of patents bas...

In maximum-likelihood based speech recognition systems, it is important to accurately estimate the joint distribution of feature vectors given a particular acoustic model. In previous work, we showed we can boost accuracy in this task by modeling the joint distribution of time-localized feature vectors along with statistics relating those feature vectors to their surrounding context. In this wo...

In this paper, we derive new closed-form expressions for the gradient of the mutual information with respect to arbitrary parameters of the two-user multiple access channel (MAC). The derived relations generalize the fundamental relation between the derivative of the mutual information and the minimum mean squared error (MMSE) to multiuser setups. We prove that the derivative of the mutual info...

structures, 3accidentally correlated, 6adding-arrows, 36ancestrally, 31atomic states, 37 background knowledge, 26Bayesian network, 2Bayesian Networks Maximise En-tropy, 30 causal extension, 6causal irrelevance, 28causal Markov condition, 1, 3causal restriction, 8, 9conditional mutual information, 40constrained network, 40correlation restrictio...

The mutual understanding in conversation is very important for human relations. This study investigates the mental function of the formation of mutual understanding between two people in conversation using the embodied approach. Forty people participated in this study. They are divided into pairs randomly. Four conversation situations between two (make/listen to fun or pleasant talk, make/liste...