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In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results , but all such efforts process word vectors sequentially and neglect long-distance dependencies. To combine deep learning with linguistic structures, we propose a dependency-based convolution approach , making use of tree-based(More)
—In this paper we present a novel generalization of Sammon's Mapping (SM), which is a popular, metric multi-dimensional scaling technique used in data analysis and visualization. The new approach, namely the Kernel-based Sammon Mapping (KSM), yields the classic SM and other much related techniques as special cases. Apart from being able to approximate(More)
In this project we want to explore the monetization of Twitter data in the stock market. The final goal is to make a profit in the market based on having a one day advantage in predicting the next day movement of Microsoft and Apple stocks. We find that Sentiment Analysis on Twitter data is mature enough and can boost prediction accuracy of current(More)
Machine learning techniques are widely used in the domain of Natural Language Processing (NLP) and Computer Vision (CV), In order to capture complex and non-linear features deeper machine learning architectures become more and more popular. A lot of the state of art performance have been reported by employing deep learning techniques. Convolutional Neural(More)
— Recognizing human face from image set has recently seen its prosperity because of its effectiveness in dealing with variations in illumination, expressions, or poses. In this paper, inspired by the prototype notion originating from cognition field, we obtain discriminative feature representation for face recognition by implementing prototype formation on(More)
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