Ziqiang Shi

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This paper studies the recovery guarantees of the models of minimizing X * + 1 2α X 2 F where X is a tensor and X * and X F are the trace and Frobenius norm of respectively. We show that they can efficiently recover low-rank tensors. In particular, they enjoy exact guarantees similar to those known for minimizing X * under the conditions on the sensing(More)
The Violent Scenes Detection Task of MediaEval provides a valuable platform for algorithm evaluation and performance comparison. This is a very challenging task as there exist many forms of violent scenes, which vary significantly in their visual and auditory clues. In this notebook paper, we describe our system used in MediaEval 2013, which focuses on the(More)
In this paper we propose an algorithm to classify tensor data. Our methodology is built on recent studies about matrix classification with the trace norm constrained weight matrix and the tensor trace norm. Similar to matrix classification, the tensor classification is formulated as a convex optimization problem which can be solved by using the(More)
Query by humming is a straight approach to content-based music retrieval. There are three main challenges: query processing, melody representation and matching algorithm. This paper focuses on the first two problems by proposing a two-layer index and multi-stage matching to accelerate searching and improve effectiveness. The two-layer index includes tune(More)
In this article, a novel framework based on trace norm minimization for audio classification is proposed. In this framework, both the feature extraction and classification are obtained by solving corresponding convex optimization problem with trace norm regularization. For feature extraction, robust principle component analysis (robust PCA) via minimization(More)
It is important to protect children from harmful effects of objectionable materials, such as pornography, which are now prevalent on the Internet. In this paper, a new method from the feature porno-sounds recognition point of view is proposed to detect adult video sequences automatically which serves as a complementary approach to the recognition method(More)
In this paper, we generalize the Gaussian Mixture Model (GMM) in two ways: a) by introducing novel distance measures between two vectors based on nonlinear maps to give more general mixture models; b) by building mixture models based on multiple different kinds of distributions. These two generalizations cope with different problems arisen in feature(More)
In order to naturally combine audio information from different dimensions and build robust audio processing system, a novel framework based on low-rank tensor representation features for audio segment classification is proposed in this paper. The audio signal is first transformed into tensor format data, and then these tensor data are mapped to a low-rank(More)