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In this paper we present an algorithm, called conauto-2.0, that can efficiently compute a set of generators of the automorphism group of a graph, and test whether two graphs are isomorphic, finding an isomorphism if they are. This algorithm…

Data Structures and Algorithms · Computer Science 2011-08-05 José Luis López-Presa , Antonio Fernández Anta , Luis Núñez Chiroque

The sparse-group lasso performs both variable and group selection, simultaneously using the strengths of the lasso and group lasso. It has found widespread use in genetics, a field that regularly involves the analysis of high-dimensional…

Machine Learning · Statistics 2025-09-18 Fabio Feser , Marina Evangelou

Group-fairness metrics (e.g., equalized odds) can vary sharply across resamples and are especially brittle under distribution shift, undermining reliable audits. We propose a Wasserstein distributionally robust framework that certifies…

Machine Learning · Computer Science 2025-10-01 Ahmad-Reza Ehyaei , Golnoosh Farnadi , Samira Samadi

Dictionary learning methods continue to gain popularity for the solution of challenging inverse problems. In the dictionary learning approach, the computational forward model is replaced by a large dictionary of possible outcomes, and the…

Machine Learning · Statistics 2023-09-06 Alberto Bocchinfuso , Daniela Calvetti , Erkki Somersalo

Let $1 \le s < t$, $N \ge 1$ be integers and a complex electronic circuit of size $t$ is said to be an $s$-active, $\; s \ll t$, and can work as a system block if not more than $s$ elements of the circuit are defective. Otherwise, the…

Information Theory · Computer Science 2016-07-05 A. G. D'yachkov , I. V. Vorobyev , N. A. Polyanskii , V. Yu. Shchukin

We consider the decoding of linear and array codes from errors when we are only allowed to download a part of the codeword. More specifically, suppose that we have encoded $k$ data symbols using an $(n,k)$ code with code length $n$ and…

Information Theory · Computer Science 2018-10-10 Itzhak Tamo , Min Ye , Alexander Barg

Sparse Representation (SR) techniques encode the test samples into a sparse linear combination of all training samples and then classify the test samples into the class with the minimum residual. The classification of SR techniques depends…

Computer Vision and Pattern Recognition · Computer Science 2019-07-01 Chun-Mei Feng , Yong Xu , Zuoyong Li , Jian Yang

In the $k$-junta testing problem, a tester has to efficiently decide whether a given function $f:\{0,1\}^n\rightarrow \{0,1\}$ is a $k$-junta (i.e., depends on at most $k$ of its input bits) or is $\epsilon$-far from any $k$-junta. Our main…

Computational Complexity · Computer Science 2015-07-15 Andris Ambainis , Aleksandrs Belovs , Oded Regev , Ronald de Wolf

Computing the Sparse Fast Fourier Transform(sFFT) of a K-sparse signal of size N has emerged as a critical topic for a long time. The sFFT algorithms decrease the runtime and sampling complexity by taking advantage of the signal inherent…

Signal Processing · Electrical Eng. & Systems 2020-12-16 Bin Li , Zhikang Jiang , Jie Chen

Flag-style fault-tolerance has become a linchpin in the realization of small fault-tolerant quantum-error correction experiments. The flag protocol's utility hinges on low qubit overhead, which is typically much smaller than in other…

Quantum Physics · Physics 2023-12-05 Dhruv Bhatnagar , Matthew Steinberg , David Elkouss , Carmen G. Almudever , Sebastian Feld

Attaining fault tolerance while maintaining low overhead is one of the main challenges in a practical implementation of quantum circuits. One major technique that can overcome this problem is the flag technique, in which high-weight errors…

Quantum Physics · Physics 2022-08-12 Theerapat Tansuwannont , Debbie Leung

Fault-tolerant syndrome extraction is a key ingredient in implementing fault-tolerant quantum computations. While conventional methods use a number of extra qubits linear in the weight of the syndrome, several improvements have been…

Quantum Physics · Physics 2024-02-22 Benjamin Anker , Milad Marvian

Sparse coding has achieved a great success in various image processing studies. However, there is not any benchmark to measure the sparsity of image patch/group because sparse discriminant conditions cannot keep unchanged. This paper…

Computer Vision and Pattern Recognition · Computer Science 2017-06-13 Zhiyuan Zha , Xin Liu , Xiaohua Huang , Henglin Shi , Yingyue Xu , Qiong Wang , Lan Tang , Xinggan Zhang

Given a weighted graph $G$ and an error parameter $\epsilon > 0$, the {\em graph sparsification} problem requires sampling edges in $G$ and giving the sampled edges appropriate weights to obtain a sparse graph $G_{\epsilon}$ (containing…

Data Structures and Algorithms · Computer Science 2010-04-26 Ramesh Hariharan , Debmalya Panigrahi

While image-text foundation models have succeeded across diverse downstream tasks, they still face challenges in the presence of spurious correlations between the input and label. To address this issue, we propose a simple three-step…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Beier Zhu , Jiequan Cui , Hanwang Zhang , Chi Zhang

Criticality and symmetry, studied by the renormalization groups, lie at the heart of modern physics theories of matters and complex systems. However, surveying these properties with massive experimental data is bottlenecked by the…

Statistical Mechanics · Physics 2024-01-30 Yang Tian , Yizhou Xu , Pei Sun

This article reviews a class of adaptive group testing procedures that operate under a probabilistic model assumption as follows. Consider a set of $N$ items, where item $i$ has the probability $p$ ($p_i$ in the generalized group testing)…

Methodology · Statistics 2021-02-19 Yaakov Malinovsky , Paul S. Albert

Subexponential parameterized algorithms are known for a wide range of natural problems on planar graphs, but the techniques are usually highly problem specific. The goal of this paper is to introduce a framework for obtaining…

Data Structures and Algorithms · Computer Science 2021-10-29 Dániel Marx , Pranabendu Misra , Daniel Neuen , Prafullkumar Tale

Given $n$ elements, an integer $k$ and a parameter $\varepsilon$, we study to select an element with rank in $(k-n\varepsilon,k+n\varepsilon]$ using unreliable comparisons where the outcome of each comparison is incorrect independently with…

Data Structures and Algorithms · Computer Science 2022-05-04 Shengyu Huang , Chih-Hung Liu , Daniel Rutschman

Group testing with inhibitors (GTI) introduced by Farach at al. is studied in this paper. There are three types of items, $d$ defectives, $r$ inhibitors and $n-d-r$ normal items in a population of $n$ items. The presence of any inhibitor in…

Information Theory · Computer Science 2014-12-16 Abhinav Ganesan , Javad Ebrahimi , Sidharth Jaggi , Venkatesh Saligrama
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