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This paper addresses the problem of unsupervised feature learning for text data.Our method is grounded in the principle of minimum description length and uses a dictionary-based compression scheme to ...
To most applied statisticians, a fitting procedure’s degrees of freedom is synonymous with its model complexity, or its capacity for overfitting to data. In particular, it is often used to parameteriz...
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...
Robust Linear Programming and Optimal Control
Linear programming Convex optimization Model-predictive control
2015/7/10
We describe an efficient method for solving an optimal control problem that arises in robust model-predictive control. The problem is to design the input sequence that minimizes the peak tracking erro...
This paper presents a novel approach for constrained state estimation from noisy measurements. The optimal trending algorithms described in this paper assume that the trended system variables have the...
OPERA: Optimization with Ellipsoidal Uncertainty for Robust Analog IC Design
Statistical optim ization
2015/7/10
As the design-manufacturing interface becomes increasingly complicated with IC technology scaling, the corresponding process variability poses great challenges for nanoscale analog/RF design. Design o...
Likelihood Bounds for Constrained Estimation with Uncertainty
Likelihood Bounds Constrained Estimation Uncertainty
2015/7/10
This paper addresses the problem of finding bounds on the optimal maximum a posteriori (or maximum likelihood) estimate in a linear model under the presence of model uncertainty. We introduce the nove...
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 ...
Generalized Chebyshev Bounds via Semidefinite Programming
semidefi nite programming convex optimization duality theory Chebyshev inequalities
2015/7/10
A sharp lower bound on the probability of a set defined by quadratic inequalities, given the first two moments of the distribution, can be efficiently computed using convex optimization. This result g...
In Chebyshev finite-impulse response (FIR) equalization, we design an FIR filter that minimizes the Chebyshev equalization error, i.e., the maximum absolute deviation between the equalized and the des...
Mixed State Estimation for a Linear Gaussian Markov Model
Mixed State Estimation Linear Gaussian Markov Model
2015/7/9
We consider a discrete-time dynamical system with Boolean and continuous states, with the continuous state propagating linearly in the continuous and Boolean state variables, and an additive Gaussian ...
Optimal Estimation of Deterioration from Diagnostic Image Sequence
Damage interior-point methods optimal estimation regularization
2015/7/9
Estimation of mechanical structure damage can greatly benefit from the knowledge that the damage accumulates irreversibly over time. This paper formulates a problem of estimation of a pixel-wise monot...
Convex Piecewise-Linear Fitting
Convex optimization Piecewise-linear approximation Data fi tting
2015/7/9
We consider the problem of fitting a convex piecewise-linear function, with some specified form, to given multi-dimensional data. Except for a few special cases, this problem is hard to solve exactly,...
Relaxed Maximum a Posteriori Fault Identification
Fault detection Statistical estimation Convex relaxation Interior-point methods
2015/7/9
We consider the problem of estimating a pattern of faults, represented as a binary vector, from a set of measurements. The measurements can be noise corrupted real values, or quantized versions of noi...
Robust Design of Slow-Light Tapers in Periodic Waveguides
robust optimization PDE-constrained optimization shape optimization coupling taper
2015/7/9
This paper concerns the design of tapers for coupling power between uniform and slow-light periodic waveguides. New optimization methods are described for designing robust tapers, which not only perfo...