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- Baoyuan Liu, Min Wang, Hassan Foroosh, Marshall F. Tappen, Marianna Pensky
- 2015 IEEE Conference on Computer Vision and…
- 2015

Deep neural networks have achieved remarkable performance in both image classification and object detection problems, at the cost of a large number of parameters and computational complexity. In this work, we show how to reduce the redundancy in these parameters using a sparse decomposition. Maximum sparsity is obtained by exploiting both inter-channel and… (More)

- Umberto Amato, Anestis Antoniadis, Marianna Pensky
- Statistics and Computing
- 2006

The paper considers regression problems with univariate design points. The design points are irregular and no assumptions on their distribution are imposed. The regression function is retrieved by a wavelet based reproducing kernel Hilbert space (RKHS) technique with the penalty equal to the sum of blockwise RKHS norms. In order to simplify numerical… (More)

- Claudia Angelini, Luisa Cutillo, Daniela De Canditiis, Margherita Mutarelli, Marianna Pensky
- BMC Bioinformatics
- 2008

Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a… (More)

The paper proposes a method of deconvolution in a periodic setting which combines two important ideas, the fast wavelet and Fourier transform-based estimation procedure of Johnstone et al. [J. Roy. Statist. Soc. Ser. B 66 (2004) 547] and the multichannel system technique proposed by Casey and Walnut [SIAM Rev. 36 (1994) 537]. An unknown function is… (More)

Hence the problem of estimating g in (1.2) is called a deconvolution problem. The problem arises in many applications [see, e.g., Desouza (1991), Louis (1991), Zhang (1992)] and, therefore, it was studied extensively in the last decade. The most popular approach to the problem was to estimate p x by a kernel estimator and then solve equation (1.2) using a… (More)

We consider a problem of recovering a high-dimensional vector μ observed in white noise, where the unknown vector μ is assumed to be sparse. The objective of the paper is to develop a Bayesian formalism which gives rise to a family of l0-type penalties. The penalties are associated with various choices of the prior distributions πn(·) on the number of… (More)

- Claudia Angelini, Daniela De Canditiis, Margherita Mutarelli, Marianna Pensky
- Statistical applications in genetics and…
- 2007

The objective of the present paper is to develop a truly functional Bayesian method specifically designed for time series microarray data. The method allows one to identify differentially expressed genes in a time-course microarray experiment, to rank them and to estimate their expression profiles. Each gene expression profile is modeled as an expansion… (More)

We extend deconvolution in a periodic setting to deal with functional data. The resulting functional deconvolution model can be viewed as a generalization of a multitude of inverse problems in mathematical physics where one needs to recover initial or boundary conditions on the basis of observations from a noisy solution of a partial differential equation.… (More)

The problem of estimating the log-spectrum of a stationary Gaussian time series by Bayesianly induced shrinkage of empirical wavelet coefficients is studied. A model in the wavelet domain that accounts for distributional properties of the log-periodogram at levels of fine detail and approximate normality at coarse levels in the wavelet decomposition, is… (More)

The objective of the paper is to develop a truly functional fully Bayesian method which allows to identify differentially expressed genes in a time-course microarray experiment. Each gene expression profile is modeled as an expansion over some orthonormal basis with coefficients and the number of basis functions estimated from the data. The proposed… (More)