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Found 4 papers, 1 papers with code
Metric Learning from Limited Pairwise Preference Comparisons
We study whether the metric can still be recovered, even though it is known that learning individual ideal items is now no longer possible.
Optimization on Pareto sets: On a theory of multi-objective optimization
But as the set of Pareto optimal vectors can be very large, we further consider a more practically significant Pareto-constrained optimization problem, where the goal is to optimize a preference function constrained to the Pareto set.
Online nearest neighbor classification
We study an instance of online non-parametric classification in the realizable setting.
Convergence of online $k$-means
We prove asymptotic convergence for a general class of $k$-means algorithms performed over streaming data from a distribution: the centers asymptotically converge to the set of stationary points of the $k$-means cost function.
