搜索结果: 46-60 共查到“知识库 科学技术统计学”相关记录243条 . 查询时间(3.362 秒)
Reducing decision errors in the paired comparison of the diagnostic accuracy of screening tests with Gaussian outcomes
cancer screening differential verification bias area under the curve type I error power paired screening trial receiver operating characteristic analysis
2013/6/14
Scientists often use a paired comparison of the areas under the receiver operating characteristic curves to decide which continuous cancer screening test has the best diagnostic accuracy. In the paire...
Robust Logistic Regression using Shift Parameters
Robust Logistic Regression Shift Parameters
2013/6/17
Annotation errors can significantly hurt classifier performance, yet datasets are only growing noisier with the increased use of Amazon Mechanical Turk and techniques like distant supervision that aut...
One out of four dogs will develop cancer in their lifetime and 20% of those are lymphoma. Pet-Screen has developed a lymphoma diagnostic test which examines the levels of two biomarkers. This method o...
Optimal filtering and the dual process
auxiliary variables Bayesian conjugacy Dirichlet process finite mixture models Cox-Ingersoll-Ross process hidden Markov model,Kalman filters
2013/6/14
We link optimal filtering for hidden Markov models to the notion of duality for Markov processes. We show that when the signal is dual to a process that has two components, one deterministic and one a...
An analysis of block sampling strategies in compressed sensing
Compressed Sensing blocks of measurements sampling continuous trajectories exact recovery,ℓ 1 minimization.
2013/6/17
Compressed sensing (CS) is a theory which guarantees the exact recovery of sparse signals from a few number of linear projections. The sampling schemes suggested by current CS theories are often of li...
The present paper - a continuation of our recent series of papers on Casimir friction for a pair of particles at low relative particle velocity - extends the analysis so as to include dense media. The...
Sparse Adaptive Dirichlet-Multinomial-like Processes
sparse coding adaptive parameters Dirichlet-Multinomial Polya urn data-dependent redundancy bound small/large alphabet data compression
2013/6/14
Online estimation and modelling of i.i.d. data for short sequences over large or complex "alphabets" is a ubiquitous (sub)problem in machine learning, information theory, data compression, statistical...
Modeling Information Propagation with Survival Theory
Modeling Information Propagation Survival Theory
2013/6/14
Networks provide a skeleton for the spread of contagions, like, information, ideas, behaviors and diseases. Many times networks over which contagions diffuse are unobserved and need to be inferred. He...
We consider the problem of clustering noisy high-dimensional data points into a union of low-dimensional subspaces and a set of outliers. The number of subspaces, their dimensions, and their orientati...
Estimation of frequency modulations on wideband signals; applications to audio signal analysis
Estimation frequency modulations wideband signals applications audio signal analysis
2013/6/14
The problem of joint estimation of power spectrum and modulation from realizations of frequency modulated stationary wideband signals is considered. The study is motivated by some specific signal clas...
HRF estimation improves sensitivity of fMRI encoding and decoding models
fMRI hemodynamic HRF GLM BOLD en-coding decoding
2013/6/14
Extracting activation patterns from functional Magnetic Resonance Images (fMRI) datasets remains challenging in rapid-event designs due to the inherent delay of blood oxygen level-dependent (BOLD) sig...
A New Global Stochastic Search Approach for Inverse Problems: Application to Ultrasound Modulated Optical Tomography
inverse problems global stochastic search discretized Kushner-Stratonovich equation gain-based update ultrasound modulated optical tomography
2013/6/14
A global stochastic search method, which is strictly derivative-free yet directed through a gain-based additive update term, is proposed and applied to the inverse problem of ultrasound modulated opti...
Corrupted Sensing: Novel Guarantees for Separating Structured Signals
Corrupted sensing compressed sensing deconvolution error correction structured signal sparsity block sparsity low rank atomic norms ℓ 1 minimization
2013/6/14
We study the problem of corrupted sensing, a generalization of compressed sensing in which one aims to recover a signal from a collection of corrupted or unreliable measurements. While an arbitrary si...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional multivariate regression models. Compared to existing methods, CMR calibrates the regularization for ...
Switching Nonparametric Regression Models and the Motorcycle Data revisited
nonparametric regression machine learning mixture of Gaussian processes latent variables EM algorithm motorcy-cle data
2013/6/14
We propose a methodology to analyze data arising from a curve that, over its domain, switches among J states. We consider a sequence of response variables, where each response y depends on a covariate...