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We address the collective matrix completion problem of jointly recovering a collection of matrices with shared structure from partial (and potentially noisy) observations. To ensure well--posedness of the problem, we impose a joint low rank…

Machine Learning · Statistics 2015-04-09 Suriya Gunasekar , Makoto Yamada , Dawei Yin , Yi Chang

In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subset of the columns of the input nonnegative data matrix containing all columns),…

Machine Learning · Statistics 2014-04-07 Nicolas Gillis , Stephen A. Vavasis

In this paper, we consider the problem of generating a set of counterfactual explanations for a group of instances, with the one-for-many allocation rule, where one explanation is allocated to a subgroup of the instances. For the first…

Machine Learning · Computer Science 2024-02-16 Andrea Lodi , Jasone Ramírez-Ayerbe

Constant-recursive sequences are those which satisfy a linear recurrence, so that later terms can be obtained as a linear combination of the previous ones. The rank of a constant-recursive sequence is the minimal number of previous terms…

Number Theory · Mathematics 2025-01-27 Eric Rowland , Jesus Sistos Barron

Conformal prediction constructs a confidence set for an unobserved response of a feature vector based on previous identically distributed and exchangeable observations of responses and features. It has a coverage guarantee at any nominal…

Machine Learning · Statistics 2022-12-08 Eugene Ndiaye , Ichiro Takeuchi

A locally-optimal structure is a combinatorial structure such as a maximal independent set that cannot be improved by certain (greedy) local moves, even though it may not be globally optimal. It is trivial to construct an independent set in…

Computational Complexity · Computer Science 2016-04-20 Leslie Ann Goldberg , Rob Gysel , John Lapinskas

A coreset is a subset of the training set, using which a machine learning algorithm obtains performances similar to what it would deliver if trained over the whole original data. Coreset discovery is an active and open line of research as…

Machine Learning · Computer Science 2020-02-21 Pietro Barbiero , Giovanni Squillero , Alberto Tonda

Let G be a simple connected graph with vertex set V(G) and edge set E(G. Each vertex of V(G) is colored by a color from the set of colors {c_1, c_2,\dots, c_{\alpha}}. We take a subset S of V(G), such that for every vertex v in V(G)\S, at…

Computational Geometry · Computer Science 2024-07-08 Bubai Manna

Compressed sensing is a technique for finding sparse solutions to underdetermined linear systems. This technique relies on properties of the sensing matrix such as the restricted isometry property. Sensing matrices that satisfy this…

Computational Complexity · Computer Science 2012-11-06 Pascal Koiran , Anastasios Zouzias

Matrix completion is a classical problem in data science wherein one attempts to reconstruct a low-rank matrix while only observing some subset of the entries. Previous authors have phrased this problem as a nuclear norm minimization…

Machine Learning · Computer Science 2019-04-19 Christian Parkinson , Kevin Huynh , Deanna Needell

Scientific practice typically involves repeatedly studying a system, each time trying to unravel a different perspective. In each study, the scientist may take measurements under different experimental conditions (interventions,…

Machine Learning · Statistics 2014-03-11 Sofia Triantafillou , Ioannis Tsamardinos

Among the biggest challenges in property-based testing (PBT) is the constrained random generation problem: given a predicate on program values, randomly sample from the set of all values satisfying that predicate, and only those values.…

Programming Languages · Computer Science 2026-04-15 Harrison Goldstein , Hila Peleg , Cassia Torczon , Daniel Sainati , Leonidas Lampropoulos , Benjamin C. Pierce

As a step towards improving the abstract reasoning capability of machines, we aim to solve Raven's Progressive Matrices (RPM) with neural networks, since solving RPM puzzles is highly correlated with human intelligence. Unlike previous…

Computer Vision and Pattern Recognition · Computer Science 2022-05-30 Tao Zhuo , Mohan Kankanhalli

We systematically study the computational complexity of a broad class of computational problems in phylogenetic reconstruction. The class contains for example the rooted triple consistency problem, forbidden subtree problems, the quartet…

Computational Complexity · Computer Science 2017-08-15 Manuel Bodirsky , Peter Jonsson , Trung Van Pham

The well-known Deficiency One Theorem gives structural conditions on a chemical reaction network under which, for any set of parameter values, the steady states of the corresponding mass action system may be easily characterized. It is also…

Optimization and Control · Mathematics 2016-03-02 Matthew D. Johnston

Biclustering is a class of techniques that simultaneously clusters the rows and columns of a matrix to sort heterogeneous data into homogeneous blocks. Although many algorithms have been proposed to find biclusters, existing methods suffer…

Machine Learning · Statistics 2020-02-11 Michelle N. Ngo , Dustin S. Pluta , Alexander N. Ngo , Babak Shahbaba

In this paper, we study contention resolution schemes for matchings. Given a fractional matching $x$ and a random set $R(x)$ where each edge $e$ appears independently with probability $x_e$, we want to select a matching $M \subseteq R(x)$…

Data Structures and Algorithms · Computer Science 2024-08-29 Pranav Nuti , Jan Vondrák

Genetic and comparative genomic studies indicate that extant genomes are more properly considered to be a fusion product of random mutations over generations and genomic material transfers between individuals of different lineages. This has…

Quantitative Methods · Quantitative Biology 2018-01-16 Andreas D. M. Gunawan , Bingxin Lu , Louxin Zhang

We present new algorithms for the problem of multiple string matching of gapped patterns, where a gapped pattern is a sequence of strings such that there is a gap of fixed length between each two consecutive strings. The problem has…

Data Structures and Algorithms · Computer Science 2014-07-08 Emanuele Giaquinta , Kimmo Fredriksson , Szymon Grabowski , Alexandru I. Tomescu , Esko Ukkonen

The perfect phylogeny is one of the most used models in different areas of computational biology. In this paper we consider the problem of the Persistent Perfect Phylogeny (referred as P-PP) recently introduced to extend the perfect…

Data Structures and Algorithms · Computer Science 2014-05-30 Paola Bonizzoni , Anna Paola Carrieri , Gianluca Della Vedova , Gabriella Trucco