Riemannian optimization methods have shown to be both fast and accurate in recovering a large-scale tensor from its incomplete observation. However, in almost all recent Riemannian tensor completion methods, only low rank constraint is considered. Another important fact, side information or features, remains far from exploiting within the Riemannian optimization framework. In this paper, we exp...

Most extractive summarization methods focus on the main body of the document from which sentences need to be extracted. However, the gist of the document may lie in side information, such as the title and image captions which are often available for newswire articles. We propose to explore side information in the context of single-document extractive summarization. We develop a framework for si...

A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this amounts to finding a suitable metric in the data space. In the supervised case, Linear Discriminant Analysis (LDA) can be used to find an appropriate subspace in which the data structure is apparent. Other ways to learn a suita...

This paper proposes several methods for noise reduction using deterministic side information about the desired signal as a constraint on the reconstruction. Two forms of side information are considered separately: short-time linear predictive coefficients, and short-time zero-phase impulse response coefficients. We derive general expressions for the ML, MAP and MMSE estimators, and develop algo...

The general investment problem concerns the allocation of wealth among m assets (stocks) to generate high returns with low risk or uncertainty. Cover and Ordentlich consider this problem from an information theoretic perspective in the case where a side information sequence aids the investment decisions but no assumptions are made on the relative likelihoods (probabilities) of stock returns seq...

The problem of classical data compression when the decoder has quantum side information at his disposal is considered. This is a quantum generalization of the classical Slepian-Wolf theorem. The optimal compression rate is found to be H(X)−χ where H(X) is the Shannon entropy of the source and χ is the Holevo quantity of the ensemble describing the classicalquantum correlations between the sourc...

This paper considers the implementation of the cubic public-key transformation, a publickey cryptographic scheme that requires sending of additional side-information. A coding scheme for the side-information, based on the residue number system, is presented. In the conventional one-to-one encryption mapping also, such coding can be used to send additional like that of watermarking, which could ...

For a given set of quantizers and a data vector, the optimal bit allocation in a rate/distortion sense is the sequence of quantizers which minimizes the overall distortion for a given bit budget. In an operational framework, this sequence is dependent on the data realization rather than on its probabilistic model and the cost of describing the sequence itself becomes therefore part of the bit b...

Computer vision tasks often have side information available that is helpful to solve the task. For example, for crowd counting, the camera perspective (e.g., camera angle and height) gives a clue about the appearance and scale of people in the scene. While side information has been shown to be useful for counting systems using traditional hand-crafted features, it has not been fully utilized in...