Lipschitz changes of variables between perturbations of log-concave measures
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Manifold models provide low-dimensional representations that are useful for analyzing and classifying data in a transformation-invariant way. In this paper we study the problem of jointly building multiple pattern transformation manifolds from a collection ...
This paper aims to maximize the profitability of a set of brand SKUs stocked at a particular retailer by optimizing the number of facings for each product. Based on the past data, a set of variables such as retail price of different SKUs, linear footage th ...
In this paper, we consider mixture approaches that adaptively combine outputs of several parallel running adaptive algorithms. These parallel units can be considered as diversity branches that can be exploited to improve the overall performance. We study v ...
We consider two biological phenomena taking place at the air-water interface: the water lapping of felines and the water running of lizards. Although seemingly disparate motions, we show that they are intimately linked by their underlying hydrodynamics and ...
We present a novel framework for automatically constraining parameters of compartmental models of neurons, given a large set of experimentally-measured responses of these neurons. In experiments, intrinsic noise gives rise to a large variability (e.g., in ...
Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to legacy (primary) networks. In this paper, a novel wide ...
Institute of Electrical and Electronics Engineers2009
Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and opportunistically use under-utilized frequency bands without causing harmful interference to primary networks. Since individual cognitive radios might ...
Transformation invariance is an important property in pattern recognition, where different observations of the same object typically receive the same label. This paper focuses on a transformation invariant distance measure that represents the minimum dista ...
The set of solutions of a parameter-dependent linear partial differential equation with smooth coefficients typically forms a compact manifold in a Hilbert space. In this paper we review the generalized reduced basis method as a fast computational tool for ...
We introduce a 3-D parametric active contour algorithm for the shape estimation of DNA molecules from stereo cryo-electron micrographs. We consider a 3-D filament (consisting of a B-spline skeleton and a specified radial profile) and match its projections ...