Optimal Permutation Recovery in Permuted Monotone Matrix Model
نویسندگان
چکیده
منابع مشابه
Juxtaposing Catalan Permutation Classes with Monotone Ones
This talk describes a clean and unified way to enumerate all juxtaposition classes of the form “Av(abc) next to Av(xy)”, where abc is a permutation of length three and xy is a permutation of length two. The main tools are Dyck paths, decorated by sequences of points, and context free grammars, used afterwards to enumerate these decorated Dyck paths. Juxtapositions are a simple special case of p...
متن کاملOn optimal permutation codes
Permutation codes are vector quantizers whose codewords are related by permutations and, in one variant, sign changes. Asymptotically, as the vector dimension grows, optimal Variant I permutation code design is identical to optimal entropy-constrained scalar quantizer (ECSQ) design. However, contradicting intuition and previously published assertions, there are finite block length permutation c...
متن کاملNear-optimal matrix recovery from random linear measurements
In matrix recovery from random linear measurements, one is interested in recovering an unknown M -by-N matrix X0 from n < MN measurements yi = Tr(Ai X0) where each Ai is an M -by-N measurement matrix with i.i.d random entries, i = 1, . . . , n. We present a novel matrix recovery algorithm, based on approximate message passing, which iteratively applies an optimal singular value shrinker – a non...
متن کاملOptimal Monotone Drawings of Trees
A monotone drawing of a graph G is a straight-line drawing of G such that, for every pair of vertices u,w in G, there exists a path Puw in G that is monotone in some direction luw. (Namely, the order of the orthogonal projections of the vertices of Puw on luw is the same as the order they appear in Puw.) The problem of finding monotone drawings for trees has been studied in several recent paper...
متن کاملOptimal monotone relabelling of partially non-monotone ordinal data
Noise in multi-criteria data sets can manifest itself as non-monotonicity. Work on the remediation of such non-monotonicity is rather scarce. Nevertheless, errors are often present in real-life data sets, and several monotone classification algorithms are unable to use such partially non-monotone data sets. Fortunately, as we will show here, it is possible to restore monotonicity in an optimal ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2020
ISSN: 0162-1459,1537-274X
DOI: 10.1080/01621459.2020.1713794