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A novel multi-view nonparametric discriminant analysis method is proposed for the application of cross-modal image retrieval and zero-shot recognition. We exploit the class boundary structure and discrepancy information of the available views in order to formulate an optimization criterion, which is automatically adjusted to the multi-view class structures. The proposed method allows for multiple...
The problem of approximate nearest neighbor (ANN) search in Big Data has been tackled with a variety of recent methods. Vector quantization based solutions have been maintaining the dominant position, as they operate in the original data space, better preserving inter-point distances. Additive quantization (AQ) in particular has pushed the state-of-the-art in search accuracy, but high computational...
There has been a surge of efforts in cross-modal recognition and retrieval in recent multimedia research. Towards this goal, we investigate a multi-modal subspace learning algorithm together with the Dropout regularizer. Inspired by the regularization for neural networks, we propose to aritificially remove the effect of certain amount of feature bins using the probabilistic approach to prevent the...
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