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Integer Parameter Estimation in Linear Models with Applications to GPS
GPS integer least-squares integer parameter estimation linear model
2015/7/10
We consider parameter estimation in linear models when some of the parameters are known to be integers. Such problems arise, for example, in positioning using phase measurements in the global position...
A Heuristic for Optimizing Stochastic Activity Networks with Applications to Statistical Digital Circuit Sizing
A Heuristic Optimizing Stochastic Activity Networks Applications Statistical Digital Circuit Sizing
2015/7/10
A deterministic activity network (DAN) is a collection of activities, each with some duration, along with a set of precedence constraints, which specify that activities begin only when certain others ...
From Feshbach-resonance managed Bose-Einstein condensates to anisotropic universes: Applications of the Ermakov-Pinney equation with time-dependent nonlinearity
Two-dimensional condensate time-varying magnetic confinement scattering wave function ordinary differential equations
2014/12/25
In this work we revisit the topic of two-dimensional Bose–Einstein condensates under the influence of time-dependent magnetic confinement and time-dependent scattering length. A moment approach reduce...
Topics in Multivariate Time Series Analysis: Statistical Control, Dimension Reduction Visualization and Thir Business Applications
Topics in Multivariate Time Series Analysis Statistical Control Dimension Reduction Visualization Their Business Applications
2014/10/28
Most business processes are, by nature, multivariate and autocorrelated. Highdimensionality is rooted in processes where more than one variable is considered simultaneously to provide a more comprehen...
Estimating Network Degree Distributions Under Sampling: An Inverse Problem, with Applications to Monitoring Social Media Networks
Estimating Network Degree Distributions Sampling An Inverse Problem Applications Monitoring Social Media Networks
2013/6/14
Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently...
Quantum Annealing for Dirichlet Process Mixture Models with Applications to Network Clustering
Quantum annealing Dirichlet process Stochastic optimization Maximum a posteriori estimation Bayesian nonparametrics
2013/6/17
We developed a new quantum annealing (QA) algorithm for Dirichlet process mixture (DPM) models based on the Chinese restaurant process (CRP). QA is a parallelized extension of simulated annealing (SA)...
Affine Invariant Divergences associated with Composite Scores and its Applications
composite score divergence Bregman score H¨older score affine invariance
2013/6/14
In statistical analysis, measuring a score of predictive performance is an important task. In many scientific fields, appropriate scores were tailored to tackle the problems at hand. A proper score is...
Quantile Regression for Large-scale Applications
Quantile Regression Large-scale Applications
2013/6/14
Quantile regression is a method to estimate the quantiles of the conditional distribution of a response variable, and as such it permits a much more accurate portrayal of the relationship between the ...
Ensembling Classification Models Based on Phalanxes of Variables with Applications in Drug Discovery
classification ranking ensemble random forest cluster pha-lanx
2013/4/28
We have proposed an ensemble method which aggregates over clusters of predictor variables. We form the clusters (we call phalanxes) by joining variables together. The variables in a phalanx are good t...
Optimization viewpoint on Kalman smoothing, with applications to robust and sparse estimation
Optimization viewpoint Kalman smoothing applications robust sparse estimation
2013/4/28
In this paper, we present the optimization formulation of the Kalman filtering and smoothing problems, and use this perspective to develop a variety of extensions and applications. We first formulate ...
Signal Recovery in Unions of Subspaces with Applications to Compressive Imaging
Union of Subspaces Group Sparsity Convex Optimization Structured Sparsity Compressed Sensing
2012/11/22
In applications ranging from communications to genetics, signals can be modeled as lying in a union of subspaces. Under this model, signal coefficients that lie in certain subspaces are active or inac...
Approximate group context tree: applications to dynamic programming and dynamic choice models
categorical time series group context tree
2011/7/19
The paper considers a variable length Markov chain model associated with a group of stationary processes that share the same context tree but potentially different conditional probabilities.
A New Class of Backward Stochastic Partial Differential Equations with Jumps and Applications
Backward Stochastic Partial Differential Equations with Jumps High-Order Partial Differential Operator Vector Partial Differential Equation Existence and Uniqueness Random Environment
2011/6/21
We formulate a new class of stochastic partial differential equations (SPDEs), named
high-order vector backward SPDEs (B-SPDEs) with jumps, which allow the high-order
integral-partial differential o...
Smoothed log-concave maximum likelihood estimation with applications
Classification Functional estimation Log-concave maximum likelihood estimation Log-concavity Smoothing
2011/3/18
We study the smoothed log-concave maximum likelihood estimator of a probability distribution on $\mathbb{R}^d$. This is a fully automatic nonparametric density estimator, obtained as a canonical smoot...
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Learning (cs.LG) Optimization and Control (math.OC) Machine Learning (stat.ML)
2010/12/17
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding cri...