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We consider the classical sparse regression problem of recovering a sparse signal $x_0$ given a measurement vector $y = \Phi x_0+w$. We propose a tree search algorithm driven by the deep neural network for sparse regression (TSN). TSN…

Machine Learning · Computer Science 2019-04-02 Kyung-Su Kim , Sae-Young Chung

We study a generalization of the Steiner tree problem, where we are given a weighted network $G$ together with a collection of $k$ subsets of its vertices and a root $r$. We wish to construct a minimum cost network such that the network…

Data Structures and Algorithms · Computer Science 2017-07-12 Guru Guruganesh , Jennifer Iglesias , R. Ravi , Laura Sanità

Given a vertex-weighted connected graph $G = (V, E)$, the maximum weight internal spanning tree (MwIST for short) problem asks for a spanning tree $T$ of $G$ such that the total weight of the internal vertices in $T$ is maximized. The…

Data Structures and Algorithms · Computer Science 2017-05-30 Zhi-Zhong Chen , Guohui Lin , Lusheng Wang , Yong Chen , Dan Wang

It is known that problems like Vertex Cover, Feedback Vertex Set and Odd Cycle Transversal are polynomial time solvable in the class of chordal graphs. We consider these problems in a graph that has at most $k$ vertices whose deletion…

Data Structures and Algorithms · Computer Science 2020-02-25 Ashwin Jacob , Fahad Panolan , Venkatesh Raman , Vibha Sahlot

Tackling simulation optimization problems with non-convex objective functions remains a fundamental challenge in operations research. In this paper, we propose a class of random search algorithms, called Regular Tree Search, which…

Optimization and Control · Mathematics 2025-06-24 Du-Yi Wang , Guo Liang , Guangwu Liu , Kun Zhang

Partitioning trees are efficient data structures for $k$-nearest neighbor search. Machine learning libraries commonly use a special type of partitioning trees called $k$d-trees to perform $k$-nn search. Unfortunately, $k$d-trees can be…

Machine Learning · Computer Science 2023-02-28 Mashaan Alshammari , John Stavrakakis , Adel F. Ahmed , Masahiro Takatsuka

A soft tree is an actively studied variant of a decision tree that updates splitting rules using the gradient method. Although soft trees can take various architectures, their impact is not theoretically well known. In this paper, we…

Machine Learning · Computer Science 2023-02-10 Ryuichi Kanoh , Mahito Sugiyama

The proper thinness of a graph is an invariant that generalizes the concept of a proper interval graph. Every graph has a numerical value of proper thinness and the graphs with proper thinness~1 are exactly the proper interval graphs. A…

Combinatorics · Mathematics 2025-05-19 Flavia Bonomo-Braberman , Ignacio Maqueda , Nina Pardal

The nni-distance is a well-known distance measure for phylogenetic trees. We construct an efficient parallel approximation algorithm for the nni-distance in the CRCW-PRAM model running in O(log n) time on O(n) processors. Given two…

Data Structures and Algorithms · Computer Science 2012-05-16 Mikael Gast , Mathias Hauptmann

Given a set of n points in the plane, each point having a positive weight, and an integer k>0, we present an optimal O(n \log n)-time deterministic algorithm to compute a step function with k steps that minimizes the maximum weighted…

Data Structures and Algorithms · Computer Science 2012-10-12 Hervé Fournier , Antoine Vigneron

This paper presents a detailed comparison of a recently proposed algorithm for optimizing decision trees, tree alternating optimization (TAO), with other popular, established algorithms. We compare their performance on a number of…

Machine Learning · Computer Science 2020-03-23 Arman Zharmagambetov , Suryabhan Singh Hada , Miguel Á. Carreira-Perpiñán , Magzhan Gabidolla

In this paper we consider alignment of sparse graphs, for which we introduce the Neighborhood Tree Matching Algorithm (NTMA). For correlated Erd\H{o}s-R\'{e}nyi random graphs, we prove that the algorithm returns -- in polynomial time -- a…

Data Structures and Algorithms · Computer Science 2020-11-02 Luca Ganassali , Laurent Massoulié

Optimal transport provides a metric which quantifies the dissimilarity between probability measures. For measures supported in discrete metric spaces, finding the optimal transport distance has cubic time complexity in the size of the…

Machine Learning · Computer Science 2024-01-30 Samantha Chen , Puoya Tabaghi , Yusu Wang

The strong thin tree conjecture states that every $k$-edge-connected graph $G$ contains an $O(1/k)$-thin spanning tree, meaning a spanning tree which contains at most an $O(1/k)$ fraction of the edges across each cut in $G$. This conjecture…

Data Structures and Algorithms · Computer Science 2026-05-14 Nathan Klein , Neil Olver , Zi Song Yeoh

We provide a new algorithm for the treatment of inverse problems which combines the traditional SVD inversion with an appropriate thresholding technique in a well chosen new basis. Our goal is to devise an inversion procedure which has the…

Statistics Theory · Mathematics 2016-08-14 Gérard Kerkyacharian , Pencho Petrushev , Dominique Picard , Thomas Willer

Decision tree optimization is notoriously difficult from a computational perspective but essential for the field of interpretable machine learning. Despite efforts over the past 40 years, only recently have optimization breakthroughs been…

Machine Learning · Computer Science 2022-11-24 Jimmy Lin , Chudi Zhong , Diane Hu , Cynthia Rudin , Margo Seltzer

Probabilistic distributions over spanning trees in directed graphs are a fundamental model of dependency structure in natural language processing, syntactic dependency trees. In NLP, dependency trees often have an additional root…

Computation and Language · Computer Science 2022-07-11 Ran Zmigrod , Tim Vieira , Ryan Cotterell

We construct near optimal linear decision trees for a variety of decision problems in combinatorics and discrete geometry. For example, for any constant $k$, we construct linear decision trees that solve the $k$-SUM problem on $n$ elements…

Computational Geometry · Computer Science 2017-05-05 Daniel M. Kane , Shachar Lovett , Shay Moran

In this paper we investigate the problem of estimating the cluster tree for a density $f$ supported on or near a smooth $d$-dimensional manifold $M$ isometrically embedded in $\mathbb{R}^D$. We analyze a modified version of a $k$-nearest…

We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high…

Computer Vision and Pattern Recognition · Computer Science 2012-08-13 Yao Lu , Kaizhu Huang , Cheng-Lin Liu