Results 61 to 70 of about 3,880,374 (297)
Sparse Regression Codes for Multi-terminal Source and Channel Coding [PDF]
, 2012 We study a new class of codes for Gaussian multi-terminal source and channel coding. These codes are designed using the statistical framework of high-dimensional linear regression and are called Sparse Superposition or Sparse Regression codes.
Tatikonda, Sekhar, Venkataramanan, Ramji
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background B‐cell lymphoblastic lymphoma (B‐LBL) represents a rare variety of non‐Hodgkin lymphoma, with limited research on its biology, progression, and management. Methods A retrospective analysis was performed on the clinical characteristics of 256 patients aged ≤18 years who received treatment under the China Net Childhood Lymphoma (CNCL)‐
Zhijuan Liu +20 more
wiley +1 more source
Dynamics of Interest Rate Curve by Functional Auto-regression [PDF]
The paper applies methods of functional data analysis – functional auto-regression, principal components and canonical correlations – to the study of the dynamics of interest rate curve.
Alexei Onatski, Slava Kargin
core +3 more sources
On the Convergence Rate of Kernel-Based Sequential Greedy Regression
Abstract and Applied Analysis, 2012 A kernel-based greedy algorithm is presented to realize efficient sparse learning with data-dependent basis functions. Upper bound of generalization error is obtained based on complexity measure of hypothesis space with covering numbers.
Xiaoyin Wang, Xiaoyan Wei, Zhibin Pan
doaj +1 more source
Inflation Rate Prediction in Indonesia using Optimized Support Vector Regression Model
JITeCS (Journal of Information Technology and Computer Science), 2020 Inflation is a indicator which illustrated the economics condition of a country. This moneter phenomenom is signed with the increase of price in entire case. It can cause an effect for political sector which impact to economic stability in a nation.
Irvi Oktanisa +2 more
doaj +1 more source
Testing the equality of nonparametric regression curves [PDF]
, 1992 This paper proposes a test for the equality of nonparametric regression curves that does not depend on the choice of a smoothing number. The test statistic is a weighted empirical process easy to compute.
Delgado, Miguel A.
core +3 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background The delipid extracorporeal lipoprotein filter from plasma (DELP) treatment can effectively reduce blood lipid, increase blood flow, and improve neurological deficits in patients with acute ischemic stroke (AIS). However, its effect on vision and retinal microcirculation in stroke patients has never been reported.
Ning Li +9 more
wiley +1 more source
Regularity dependence of the rate of convergence of the learning curve for Gaussian process regression [PDF]
, 2012 This paper deals with the speed of convergence of the learning curve in a Gaussian process regression framework. The learning curve describes the average generalization error of the Gaussian process used for the regression.
Garnier, Josselin, Gratiet, Loic Le
core +2 more sources
Forecasting exchange rates using local regression
Applied Economics Letters, 2010 In this article we use a generalization of the standard nearest neighbours, called local regression (LR), to study the predictability of the yen/US$ and pound sterling/US$ exchange rates. We also compare our results with those previously obtained with global methods such as neural networks, genetic programming, data fusion and evolutionary neural ...
Álvarez-Díaz, Marcos +1 more
openaire +2 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Introduction Cognitive impairment and exercise intolerance are common in dialysis patients. Cerebral perfusion and oxygenation play a major role in both cognitive function and exercise execution; HD session per se aggravates cerebral ischemia in this population. This study aimed to compare cerebral oxygenation and perfusion at rest and in mild
Marieta P. Theodorakopoulou +10 more
wiley +1 more source