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Tree-based models are often robust to uninformative features and can accurately capture non-smooth, complex decision boundaries. Consequently, they often outperform neural network-based models on tabular datasets at a significantly lower…

Machine Learning · Computer Science 2025-05-08 Urška Matjašec , Nikola Simidjievski , Mateja Jamnik

We give a new general approach for designing exact exponential-time algorithms for subset problems. In a subset problem the input implicitly describes a family of sets over a universe of size n and the task is to determine whether the…

Data Structures and Algorithms · Computer Science 2015-12-08 Fedor V. Fomin , Serge Gaspers , Daniel Lokshtanov , Saket Saurabh

This paper describes an abstractive summarization method for tabular data which employs a knowledge base semantic embedding to generate the summary. Assuming the dataset contains descriptive text in headers, columns and/or some augmenting…

Artificial Intelligence · Computer Science 2018-04-06 Paul Azunre , Craig Corcoran , David Sullivan , Garrett Honke , Rebecca Ruppel , Sandeep Verma , Jonathon Morgan

A fundamental challenge in graph mining is the ever-increasing size of datasets. Graph summarization aims to find a compact representation resulting in faster algorithms and reduced storage needs. The flip side of graph summarization is the…

Data Structures and Algorithms · Computer Science 2020-06-17 Mahdi Hajiabadi , Jasbir Singh , Venkatesh Srinivasan , Alex Thomo

In this paper, we propose a novel space partitioning strategy for implicit hierarchy visualization such that the new plot not only has a tidy layout similar to the treemap, but also is flexible to data changes similar to the Voronoi…

Data Structures and Algorithms · Computer Science 2020-09-17 Yan-Chao Wang , Feng Lin , Hock-Soon Seah

We consider the \emph{Budgeted} version of the classical \emph{Connected Dominating Set} problem (BCDS). Given a graph $G$ and a budget $k$, we seek a connected subset of at most $k$ vertices maximizing the number of dominated vertices in…

Data Structures and Algorithms · Computer Science 2020-03-26 Ioannis Lamprou , Ioannis Sigalas , Vassilis Zissimopoulos

We give almost-linear-time algorithms for approximating rooted minimum cut and maximum arborescence packing in directed graphs, two problems that are dual to each other [Edm73]. More specifically, for an $n$-vertex, $m$-edge directed graph…

Data Structures and Algorithms · Computer Science 2025-12-18 Yonggang Jiang , Yaowei Long , Thatchaphol Saranurak , Benyu Wang

We study graph partitioning problems from a min-max perspective, in which an input graph on n vertices should be partitioned into k parts, and the objective is to minimize the maximum number of edges leaving a single part. The two main…

Data Structures and Algorithms · Computer Science 2011-10-21 Nikhil Bansal , Uriel Feige , Robert Krauthgamer , Konstantin Makarychev , Viswanath Nagarajan , Joseph , Naor , Roy Schwartz

In the \emph{$k$-Diameter-Optimally Augmenting Tree Problem} we are given a tree $T$ of $n$ vertices as input. The tree is embedded in an unknown \emph{metric} space and we have unlimited access to an oracle that, given two distinct…

Data Structures and Algorithms · Computer Science 2023-05-30 Davide Bilò , Luciano Gualà , Stefano Leucci , Luca Pepè Sciarria

Many discrete optimization problems amount to selecting a feasible set of edges of least weight. We consider in this paper the context of spatial graphs where the positions of the vertices are uncertain and belong to known uncertainty sets.…

Data Structures and Algorithms · Computer Science 2022-09-27 Marin Bougeret , Jérémy Omer , Michael Poss

We describe a simple deterministic $O( \varepsilon^{-1} \log \Delta)$ round distributed algorithm for $(2\alpha+1)(1 + \varepsilon)$ approximation of minimum weighted dominating set on graphs with arboricity at most $\alpha$. Here $\Delta$…

Data Structures and Algorithms · Computer Science 2022-06-13 Michal Dory , Mohsen Ghaffari , Saeed Ilchi

We combine two methods for the lossless compression of unlabeled graphs - entropy compressing adjacency lists and computing canonical names for vertices - and solve an ensuing novel optimisation problem: Minimum-Entropy Tree-Extraction…

Data Structures and Algorithms · Computer Science 2026-03-17 Ziad Ismaili Alaoui , Tamio-Vesa Nakajima , Namrata , Sebastian Wild

Summaries of massive data sets support approximate query processing over the original data. A basic aggregate over a set of records is the weight of subpopulations specified as a predicate over records' attributes. Bottom-k sketches are a…

Databases · Computer Science 2008-02-26 Edith Cohen , Haim Kaplan

Keyphrases are crucial for searching and systematizing scholarly documents. Most current methods for keyphrase extraction are aimed at the extraction of the most significant words in the text. But in practice, the list of keyphrases often…

Computation and Language · Computer Science 2024-10-23 Anna Glazkova , Dmitry Morozov

Data summarization is essential to discover insights from large datasets. In a spreadsheets, pivot tables offer a convenient way to summarize tabular data by computing aggregates over some attributes, grouped by others. However, identifying…

Databases · Computer Science 2025-12-03 Whanhee Cho , Anna Fariha

Embeddings of graphs into distributions of trees that preserve distances in expectation are a cornerstone of many optimization algorithms. Unfortunately, online or dynamic algorithms which use these embeddings seem inherently randomized and…

Data Structures and Algorithms · Computer Science 2021-02-11 Bernhard Haeupler , D Ellis Hershkowitz , Goran Zuzic

We consider the problem of augmenting an $n$-vertex tree with one shortcut in order to minimize the diameter of the resulting graph. The tree is embedded in an unknown space and we have access to an oracle that, when queried on a pair of…

Data Structures and Algorithms · Computer Science 2018-10-03 Davide Bilò

We consider a variant of the prize collecting Steiner tree problem in which we are given a \emph{directed graph} $D=(V,A)$, a monotone submodular prize function $p:2^V \rightarrow \mathbb{R}^+ \cup \{0\}$, a cost function $c:V \rightarrow…

Data Structures and Algorithms · Computer Science 2022-10-04 Gianlorenzo D'Angelo , Esmaeil Delfaraz , Hugo Gilbert

Text summarization is a fundamental task in natural language processing (NLP), and the information explosion has made long-document processing increasingly demanding, making summarization essential. Existing research mainly focuses on model…

The efficiency of exact subset sum problem algorithms which compute individual subset sums is defined as $e=min(T/z, 1)$, where $z$ is the number of subset sums computed. $e$ is related to these algorithms' computational complexity. This…

Data Structures and Algorithms · Computer Science 2024-09-18 Nick Dawes