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Broadcasting with coded side information

2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC), 2012
In the original index coding problem, each user has a set of uncoded packets as side information, and wants to decode some other packets from the source node. The source node aims at satisfying the demands of all users as quickly as possible. With linear network coding, this is accomplished by broadcasting linear combinations of the source packets over
Kenneth W. Shum   +2 more
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Boosting with Side Information

2013
In many problems of machine learning and computer vision, there exists side information, i.e., information contained in the training data and not available in the testing phase. This motivates the recent development of a new learning approach known as learning with side information that aims to incorporate side information for improved learning ...
Jixu Chen, Xiaoming Liu 0002, Siwei Lyu
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Watermarking as communications with side information

Proceedings of the IEEE, 1999
Several authors have drawn comparison between embedded signaling or watermarking and communications, especially spread-spectrum communications. We examine the similarities and differences between watermarking and traditional communications. This comparison suggests that watermarking most closely resembles communications with side information at the ...
Ingemar J. Cox   +2 more
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Online learning with side information

MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM), 2017
An online learning problem with side information is considered. The problem is formulated as a graph structured stochastic Multi-Armed Bandit (MAB). Each node in the graph represents an arm in the bandit problem and an edge between two arms indicates closeness in their mean rewards.
Xiao Xu   +3 more
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Exploiting Side Information for Recommendation

2019
Recommender systems have become extremely essential tools to help resolve the information overload problem for users. However, traditional recommendation techniques suffer from critical issues such as data sparsity and cold start problems. To address these issues, a great number of recommendation algorithms have been proposed by exploiting the side ...
Qing Guo 0005   +2 more
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Universal portfolios with side information

IEEE Transactions on Information Theory, 1996
Summary: We present a sequential investment algorithm, the \(\mu\)-weighted universal portfolio with side information, which achieves, to first order in the exponent, the same wealth as the best side-information dependent investment strategy (the best state-constant rebalanced portfolio) determined in hindsight from observed market and side-information
Thomas M. Cover, Erik Ordentlich
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Ising Bandits with Side Information

2015
We develop an online learning algorithm for bandits on a graph with side information where there is an underlying Ising distribution over the vertices at low temperatures. We are motivated from practical settings where the graph state in a social or a computer hosts network (potentially) changes at every trial; intrinsically partitioning the graph thus
Shaona Ghosh, Adam Prügel-Bennett
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The behavioral side of information technology

International Journal of Medical Informatics, 1999
Exposure to technologies is becoming more prevalent in healthcare technologies. Few strategies have been developed that work reliably to successfully implement information technologies. Information technology enables, but does not guarantee organizational change.
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Multiple Watermarking with Side Information

2009
The idea of side information is introduced into multiple watermarking, and a multiple watermarking model with side information is proposed based on the Slepian-Wolf source encoding theory. In the proposed model, the correlation between the cover work and the multiple watermarks and the correlation among the watermarks themselves are considered and used
Jun Xiao 0005, Ying Wang 0030
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Partial Monitoring with Side Information

2012
In a partial-monitoring problem in every round a learner chooses an action, simultaneously an opponent chooses an outcome, then the learner suffers some loss and receives some feedback. The goal of the learner is to minimize his (unobserved) cumulative loss.
Gábor Bartók, Csaba Szepesvári
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