We study the minimum random bit rate required to simulate a random system (channel), where the simulator operates with a given external input. As measures of simulation accuracy we use both the variational distance and the d distance between joint input-output distributions. We find the asymptotic number of random bits per input sample required for accurate simulation, as a function of the dist...

Wyner-Ziv (WZ) encoder is a low -complexity encoder and can be made to achieve compression comparable to traditional high complexity encoders but at the expense of a high-complexity decoder. The high complexity of the decoder is mainly attributed to the generation of side information which involves motion estimation. In this paper sub-pixel motion estimation and intra-prediction based on H.264 ...

Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application of learning distance metrics from historical relevance feedback log data, which leads to a novel scenario called collaborative image retrieval. The log data provide the side information expressed as relevance judgemen...

Orthogonal frequency division multiplexing (OFDM) has become a promising method for many wireless communication applications. However, one main drawback of OFDM systems is the high peak-to-average power ratio (PAPR). Selected mapping (SLM) is a well-known technique to decrease the problem of high PAPR in OFDM systems. In this method, transmitter is obliged to send some bits named side informati...

The estimation of affinity relationships between sets of entities can be aided by a variety of available sources of auxiliary information about these entities. Estimating the unknown affinity values given a few known values forms an important class of problems in data mining. This paper introduces a class of Bayesian mixture models Side Information Aware Bayesian Affinity Estimation (SABAE), th...

We study online learning of finite Markov decision process (MDP) problems when a side information vector is available. The problem is motivated by applications such as clinical trials, recommendation systems, etc. Such applications have an episodic structure, where each episode corresponds to a patient/customer. Our objective is to compete with the optimal dynamic policy that can take side info...

With the broad application of web 2.0 technology, various kinds of online social networks arise at present. The emergence of social networks not only helps the public to facilitate the sharing and communicating, but also helps them to know more new friends from cyberspace social circle. Therefore, friends recommendation becomes a critical function for various online social networks. Problem of ...

With the Bandwidth Extension (BWE) techniques it is possible to enhance the bandwidth of limited speech signals and provide backward compatibility with respect to the communication networks. Artificial Bandwidth Extension (ABWE) uses correlations between the low and the high frequency ranges, to predict a wideband signal outgoing from a narrowband signal [1, 2]. The advantage of the ABWE techni...

The work described in this thesis examined a new approach to speech enhancement. Enhancement algorithms to estimate clean speech from a noisy signal and a limited amount of side information were developed and implemented. The work evaluated algorithms that used linear predicitive (LP) coefficients and zero-phase impulse response coefficients as side information. An approximate maximum likelihoo...

Matrix and tensor completion techniques have proven useful in many applications such as recommender systems, image/video restoration, and web search. We explore the idea of using external information in completing missing values in tensors. In this work, we present a framework that employs side information as kernel matrices for tensor factorization. We apply our framework to problems of recomm...