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In this paper a new distributed asynchronous algorithm is proposed for time synchronization in networks with random communication delays, measurement noise and communication dropouts. Three different types of the drift correction algorithm…

Systems and Control · Computer Science 2018-02-05 Milos S. Stankovic , Srdjan S. Stankovic , Karl Henrik Johansson

Despite being vastly ignored in the literature, coping with topological noise is an issue of increasing importance, especially as a consequence of the increasing number and diversity of 3D polygonal models that are captured by devices of…

Graphics · Computer Science 2017-05-16 Asli Genctav , Yusuf Sahillioglu , Sibel Tari

We propose an embarrassingly simple but very effective scheme for high-quality dense stereo reconstruction: (i) generate an approximate reconstruction with your favourite stereo matcher; (ii) rewarp the input images with that approximate…

Computer Vision and Pattern Recognition · Computer Science 2021-06-21 Corinne Stucker , Konrad Schindler

Given a rectangle $R$ with area $A$ and a set of areas $L=\{A_1,...,A_n\}$ with $\sum_{i=1}^n A_i = A$, we consider the problem of partitioning $R$ into $n$ sub-regions $R_1,...,R_n$ with areas $A_1,...,A_n$ in a way that the total…

Optimization and Control · Mathematics 2023-09-06 Reyhaneh Mohammadi , Mehdi Behroozi

It was recently shown that a version of the greedy algorithm gives a construction of fault-tolerant spanners that is size-optimal, at least for vertex faults. However, the algorithm to construct this spanner is not polynomial-time, and the…

Data Structures and Algorithms · Computer Science 2020-05-26 Michael Dinitz , Caleb Robelle

Subset repair is an important data cleaning technique that enforces integrity constraints by deleting a minimal number of conflicting tuples, yet multiple minimal repairs often exist. Density-based methods address this ambiguity by favoring…

Databases · Computer Science 2026-01-28 Guoqi Zhao , Xixian Han , Xiaolong Wan

We study the problem of sparse reconstruction from noisy undersampled measurements when the following two things are available. (1) We are given partial, and partly erroneous, knowledge of the signal's support, denoted by $T$. (2) We are…

Information Theory · Computer Science 2016-11-17 Wei Lu , Namrata Vaswani

We propose a new algorithm to the problem of polygonal curve approximation based on a multiresolution approach. This algorithm is suboptimal but still maintains some optimality between successive levels of resolution using dynamic…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Pierre-François Marteau , Gilbas Ménier

In this paper, we propose an original manner to employ a tangential cover algorithm - minDSS - in order to geometrically reconstruct noisy digital contours. To do so, we exploit the representation of graphical objects by maximal primitives…

Computer Vision and Pattern Recognition · Computer Science 2021-11-11 Antoine Vacavant , Bertrand Kerautret , Fabien Feschet

We introduce the idea that the P vs NP problem can have a finer structure. Given the NP complete problem of interest, the configurations space of the problem can be divided in (at least) two regions. In one region, polynomial algorithms to…

Statistical Mechanics · Physics 2026-01-28 Fabrizio Canfora , Marco Cedeno

We propose a method for redistricting, decomposing a geographical area into subareas, called districts, so that the populations of the districts are as close as possible and the districts are compact and contiguous. Each district is the…

Data Structures and Algorithms · Computer Science 2018-01-09 Vincent Cohen-Addad , Philip N. Klein , Neal E. Young

Dynamic sparsity, where the sparsity patterns are unknown until runtime, poses a significant challenge to deep learning. The state-of-the-art sparsity-aware deep learning solutions are restricted to pre-defined, static sparsity patterns due…

We propose a new method for reconstruction of sparse signals with and without noisy perturbations, termed the subspace pursuit algorithm. The algorithm has two important characteristics: low computational complexity, comparable to that of…

Numerical Analysis · Computer Science 2009-01-08 Wei Dai , Olgica Milenkovic

Signals sparse in a transformation domain can be recovered from a reduced set of randomly positioned samples by using compressive sensing algorithms. Simple re- construction algorithms are presented in the first part of the paper. The…

Information Theory · Computer Science 2015-12-08 Ljubisa Stankovic , Isidora Stankovic

This Paper Analyze the performance of Unsymmetrical trimmed median, which is used as detector for the detection of impulse noise, Gaussian noise and mixed noise is proposed. The proposed algorithm uses a fixed 3x3 window for the increasing…

Computer Vision and Pattern Recognition · Computer Science 2012-06-08 K. Vasanth , V. Jawahar Senthil Kumar

Topological data analysis (TDA) has emerged as one of the most promising techniques to reconstruct the unknown shapes of high-dimensional spaces from observed data samples. TDA, thus, yields key shape descriptors in the form of persistent…

Machine Learning · Statistics 2017-11-15 Wei Guo , Krithika Manohar , Steven L. Brunton , Ashis G. Banerjee

The Euclidean TSP with neighborhoods (TSPN) problem seeks a shortest tour that visits a given collection of $n$ regions ({\em neighborhoods}). We present the first polynomial-time approximation scheme for TSPN for a set of regions given by…

Computational Geometry · Computer Science 2017-03-07 Joseph S. B. Mitchell

A polyomino is a polygonal region with axis parallel edges and corners of integral coordinates, which may have holes. In this paper, we consider planar tiling and packing problems with polyomino pieces and a polyomino container $P$. We give…

Computational Geometry · Computer Science 2021-08-10 Anders Aamand , Mikkel Abrahamsen , Thomas D. Ahle , Peter M. R. Rasmussen

Recent studies show that prompt tuning can better leverage the power of large language models than fine-tuning on downstream natural language understanding tasks. However, the existing prompt tuning methods have training instability issues,…

Computation and Language · Computer Science 2023-05-05 Lichang Chen , Heng Huang , Minhao Cheng

We consider a regularized least squares problem, with regularization by structured sparsity-inducing norms, which extend the usual $\ell_1$ and the group lasso penalty, by allowing the subsets to overlap. Such regularizations lead to…

Optimization and Control · Mathematics 2012-09-04 Silvia Villa , Lorenzo Rosasco , Sofia Mosci , Alessandro Verri