On the Sample Complexity of Subspace Learning

A large number of algorithms in machine learning, from principal component analysis (PCA), and its non-linear (kernel) extensions, to more recent spectral embedding and support estimation methods, rely on estimating a linear subspace from samples. In this paper we introduce a general formulation of this problem and derive novel learning error estimates. Our results rely on natural assumptions on the spectral properties of the covariance operator associated to the data distribu- tion, and hold for a wide class of metrics between subspaces. As special cases, we discuss sharp error estimates for the reconstruction properties of PCA and spectral support estimation. Key to our analysis is an operator theoretic approach that has broad applicability to spectral learning methods.Comment: Extendend Version of conference pape

Implementasi Kebijakan Fiskal: Pembiayaan Program Pembangunan Berbasis Rukun Tetangga (Pbrt) di Kabupaten Sumbawa Barat

Fiscal policy is one form of economic policies pursued in the context of macroeco-nomic stabilization, promote growth, equity, and sustainability menjega budget. WestSumbawa regency is one of regencies in NTB province has embarked on one of fiscalpolicy implementation is in the financing of Neighborhood-Based Development pro-gram (PBRT). PBRT program is a strategy of development by putting the region atthe lowest level of development of the neighborhood (RT). This policy is the empow-erment of RT with the understanding that the RT is not the lowest governmentalstructures and nongovernmental organizations that are able to understand all the com-plaints and needs of their citizens. RT becomes a very important institution in whichis located all the pecking order and also serves as a populist economic base which isthen defined as the Regulation (Regulation No. 27 Year 2008 regarding PBRT). Thispaper reviewed the implementation of the program PBRT is related to how big thebudget from the budget for financing. Furthermore, by using Regulatory Impact Analysiswill be analyzed whether the policy PBRT program will bring net benefits to societyand increase welfare in West Sumbawa regency

HF-rTMS treatment decreases psychomotor retardation in medication-resistant melancholic depression

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Automated Vehicle Monitoring System

An automated vehicle monitoring system is proposed in this paper. The surveillance system is based on image processing techniques such as background subtraction, colour balancing, chain code based shape detection, and blob. The proposed system will detect any human\u27s head as appeared at the side mirrors. The detected head will be tracked and recorded for further action

Distinct phosphorylation clusters determines the signalling outcome of the free fatty acid receptor FFA4/GPR120

It is established that long-chain free fatty acids including ω-3 fatty acids mediate an array of biological responses through members of the free fatty acid receptor family, which includes FFA4. However, the signalling mechanisms and modes of regulation of this receptor class remain unclear. Here we employ mass spectrometry to determine that phosphorylation of mouse (m)FFAR4 occurs at five serine and threonine residues clustered in two separable regions of the C terminal tail, designated cluster 1 (Thr347, Thr349 and Ser350) and cluster 2 (Ser357 and Ser361). Mutation of these phospho-acceptor sites to alanine completely prevented phosphorylation of mFFA4 but did not limit receptor coupling to ERK1/2 activation. Rather an inhibitor of Gq/11 proteins completely prevented receptor signalling to ERK1/2. In contrast, the recruitment of arrestin 3, receptor internalization and activation of Akt were regulated by mFFA4 phosphorylation. The analysis of mFFA4 phosphorylation-dependent signalling was extended further by selective mutations of the phospho-acceptor sites. Mutations within cluster 2 did not affect agonist activation of Akt but instead significantly compromised receptor internalization and arrestin 3 recruitment. Distinctly, mutation of the phospho-acceptor sites within cluster 1 had no effect on receptor internalization and a less extensive effect on arrestin 3 recruitment, but significantly uncoupled the receptor from Akt activation. These unique observations define differential effects on signalling mediated by phosphorylation at distinct locations. This hallmark feature supports the possibility that the signalling outcome of mFFA4 activation can be determined by the pattern of phosphorylation (phosphorylation barcode) at the C-terminus of the receptor

On Fast Leverage Score Sampling and Optimal Learning

Leverage score sampling provides an appealing way to perform approximate computations for large matrices. Indeed, it allows to derive faithful approximations with a complexity adapted to the problem at hand. Yet, performing leverage scores sampling is a challenge in its own right requiring further approximations. In this paper, we study the problem of leverage score sampling for positive definite matrices defined by a kernel. Our contribution is twofold. First we provide a novel algorithm for leverage score sampling and second, we exploit the proposed method in statistical learning by deriving a novel solver for kernel ridge regression. Our main technical contribution is showing that the proposed algorithms are currently the most efficient and accurate for these problems

Aplikasi Jaringan Saraf Tiruan Backpropagation Untuk Memprediksi Penyakit Tht Di Rumah Sakit Mardi Rahayu Kudus

Artificial neural network (ANN) is a modern computing paradigm. That can be used for the pattern recognition and other. Backpropagation is artificial neural network which using hidden layer addition. Computation of artificial neural network through some certain step like training phase and examination. After both the step reached, so a neural network capable to recognize pattern to be entered will be found.The purpose of this research is simulation of artificial neural network that capable to pattern recognition from output of electrocardiogram by helped of MATLAB program. Input of result electrocardiogram record, then input of data can be normalization after that data can be proccesed by backpropagation computing with two step (training phase and examination phase). Output of ANN is like explaning condition of patient is normal, rhinitis kronis or epistaksis