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We develop a framework for localizing an unknown point $\\w$ using paired comparisons of the form ``$\\w$ is closer to point $\\x_i$ than to $\\x_j$'' when the points lie in a union of known subspaces. This model, which extends a broad class of existing metho
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The Picasso Algorithm For Bayesian Localization Via Paired Comparisons In A Union Of Subspaces Model
We develop a framework for localizing an unknown point $\w$ using paired comparisons of the form ``$\w$ is closer to point $\x_i$ than to $\x_j$'' when the points lie in a union of known subspaces. This model, which extends a broad class of existing metho