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Predicting the Severity of Breast Masses with Data Mining Methods
Breast cancer data mining decision tree neural network support vector machine
2013/6/17
Mammography is the most effective and available tool for breast cancer screening. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approxima...
Capacity Value of Additional Generation: Probability Theory and Sampling Uncertainty
Power system planning Power system operation Power system reliability Risk analysis Wind energy
2013/6/17
The concept of capacity value is widely used to quantify the contribution of additional generation (most notably renewables) within generation adequacy assessments. This paper surveys the existing pro...
A proportional hazard model for the estimation of ionosphere storm occurrence risk
proportional hazard model the estimation ionosphere storm occurrence risk
2013/6/14
Severe Ionosphere magnetic storms are feared events for integrity and continuity of navigation systems such as EGNOS, the European SBAS (Satellite-Based Augmentation System) complementing GPS and an a...
Optimal Periodic Sensor Scheduling in Large-Scale Dynamical Networks
Dynamic system state estimation sensor scheduling sparsity sensor networks
2013/6/14
We consider the problem of finding optimal time-periodic sensor schedules for estimating the state of a large-scale dynamical system. We assume that a large number of sensors have been deployed and th...
Information Criteria for Deciding between Normal Regression Models
Information Criteria Deciding between Normal Regression Models
2013/6/14
Regression models fitted to data can be assessed on their goodness of fit, though models with many parameters should be disfavored to prevent over-fitting. Statisticians' tools for this are little kno...
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...