Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices

We study minimax rates for denoising simultaneously sparse and low rank matrices in high dimensions. We show that an iterative thresholding algorithm achieves (near) optimal rates adaptively under mild conditions for a large class of loss functions. Numerical experiments on synthetic datasets also demonstrate the competitive performance of the proposed method

Comment: Boosting Algorithms: Regularization, Prediction and Model Fitting

The authors are doing the readers of Statistical Science a true service with a well-written and up-to-date overview of boosting that originated with the seminal algorithms of Freund and Schapire. Equally, we are grateful for high-level software that will permit a larger readership to experiment with, or simply apply, boosting-inspired model fitting. The authors show us a world of methodology that illustrates how a fundamental innovation can penetrate every nook and cranny of statistical thinking and practice. They introduce the reader to one particular interpretation of boosting and then give a display of its potential with extensions from classification (where it all started) to least squares, exponential family models, survival analysis, to base-learners other than trees such as smoothing splines, to degrees of freedom and regularization, and to fascinating recent work in model selection. The uninitiated reader will find that the authors did a nice job of presenting a certain coherent and useful interpretation of boosting. The other reader, though, who has watched the business of boosting for a while, may have quibbles with the authors over details of the historic record and, more importantly, over their optimism about the current state of theoretical knowledge. In fact, as much as ``the statistical view'' has proven fruitful, it has also resulted in some ideas about why boosting works that may be misconceived, and in some recommendations that may be misguided. [arXiv:0804.2752]Comment: Published in at http://dx.doi.org/10.1214/07-STS242B the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Functional principal components analysis via penalized rank one approximation

Two existing approaches to functional principal components analysis (FPCA) are due to Rice and Silverman (1991) and Silverman (1996), both based on maximizing variance but introducing penalization in different ways. In this article we propose an alternative approach to FPCA using penalized rank one approximation to the data matrix. Our contributions are four-fold: (1) by considering invariance under scale transformation of the measurements, the new formulation sheds light on how regularization should be performed for FPCA and suggests an efficient power algorithm for computation; (2) it naturally incorporates spline smoothing of discretized functional data; (3) the connection with smoothing splines also facilitates construction of cross-validation or generalized cross-validation criteria for smoothing parameter selection that allows efficient computation; (4) different smoothing parameters are permitted for different FPCs. The methodology is illustrated with a real data example and a simulation.Comment: Published in at http://dx.doi.org/10.1214/08-EJS218 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Security Analysis of IoT Encryption: Side-channel Cube Attack on Simeck32/64

Simeck, a lightweight block cipher has been proposed to be one of the encryption that can be employed in the Internet of Things (IoT) applications. Therefore, this paper presents the security of the Simeck32/64 block cipher against side-channel cube attack. We exhibit our attack against Simeck32/64 using the Hamming weight leakage assumption to extract linearly independent equations in key bits. We have been able to find 32 linearly independent equations in 32 key variables by only considering the second bit from the LSB of the Hamming weight leakage of the internal state on the fourth round of the cipher. This enables our attack to improve previous attacks on Simeck32/64 within side-channel attack model with better time and data complexity of 2^35 and 2^11.29 respectively.Comment: 12 pages, 6 figures, 4 tables, International Journal of Computer Networks & Communication

Book Review: Studies in the Printing, Publishing and Performance of Music in the 16th Century. by Stanley Boorman

Buja reviews Boorman\u27s 2005 book. Boorman, Stanley. Studies in the Printing, Publishing and Performance of Music in the 16th Century. Aldershot: Ashgate, 2005. Variorium Collected Studies Series, C815. ISBN 0-86078-970-5

tourr: An R Package for Exploring Multivariate Data with Projections

This paper describes an R package which produces tours of multivariate data. The package includes functions for creating different types of tours, including grand, guided, and little tours, which project multivariate data (p-D) down to 1, 2, 3, or, more generally, d (⤠p) dimensions. The projected data can be rendered as densities or histograms, scatterplots, anaglyphs, glyphs, scatterplot matrices, parallel coordinate plots, time series or images, and viewed using an R graphics device, passed to GGobi, or saved to disk. A tour path can be stored for visualisation or replay. With this package it is possible to quickly experiment with different, and new, approaches to tours of data. This paper contains animations that can be viewed using the Adobe Acrobat PDF viewer.

Security Analysis Techniques Using Differential Relationships For Block Ciphers

The uses of block cipher has become crucial in nowadays’ computing era as well as the information security. Information must be available only for authenticated and authorized users.However,flaws and weaknesses in the cryptosystem can breach the security of stored and transmitted information.A weak key in the key schedule is well-known issues which may affect several round keys have same bits in common.Besides,information leaked from the implementation also affects the security of block ciphers.Based on the flaws and leakage,the adversary is able to assess the differential relationships in block cipher using differential cryptanalysis technique. Firstly,the existing differential cryptanalysis techniques have been evaluated.Secondly,based on the gaps that have to be filled in the existing differential cryptanalysis techniques,new frameworks of differential cryptanalysis techniques have been proposed and designed by using Pearson correlation coefficient,Hamming-weight leakage assumption and reference point.The Pearson correlation coefficient is used to determine the repeated differential properties in the key schedules.Meanwhile, reference point and Hamming-weight leakage assumption are used to assess the security of the implementation of block ciphers against side-channel cube attack and differential fault analysis.Thirdly,all proposed frameworks have been assessed.The results show that the repeated differential properties are found for AES, PRESENT and Simeck key schedules.However,AES key schedule is definitely ideal to be adopted in the design for the future cryptographic algorithm.In addition,the newly designed frameworks for side-channel differential analysis techniques have been able to reduce the attack complexities for Simeck32/64,KATAN32 and KTANTAN32 compared to previous work.In conclusion,the proposed frameworks are effective in analyzing the security of block ciphers using differential cryptanalysis techniques