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Cardinality constraints or, more generally, weight constraints are well recognized as an important extension of answer-set programming. Clearly, all common algorithmic tasks related to programs with cardinality or weight constraints - like…

Logic in Computer Science · Computer Science 2020-02-19 Reinhard Pichler , Stefan Rümmele , Stefan Szeider , Stefan Woltran

In the Tree Deletion Set problem the input is a graph G together with an integer k. The objective is to determine whether there exists a set S of at most k vertices such that G-S is a tree. The problem is NP-complete and even NP-hard to…

Data Structures and Algorithms · Computer Science 2013-10-01 Archontia C. Giannopoulou , Daniel Lokshtanov , Saket Saurabh , Ondrej Suchy

We consider the problem of drawing multiple gene trees inside a single species tree in order to visualize multispecies coalescent trees. Specifically, the drawing of the species tree fills a rectangle in which each of its edges is…

Discrete Mathematics · Computer Science 2022-11-01 Jonathan Klawitter , Felix Klesen , Moritz Niederer , Alexander Wolff

Kernel methods provide a theoretically grounded framework for non-linear and non-parametric learning, with strong analytic foundations and statistical guarantees. Yet, their scalability has long been limited by prohibitive time and memory…

Machine Learning · Computer Science 2025-10-01 Maedeh Zarvandi , Michael Timothy , Theresa Wasserer , Debarghya Ghoshdastidar

Decision forests induce supervised similarities through the partition structure of their trees. Yet forest proximity computation is still often treated as a quadratic operation in the number of samples, which limits scalability and…

Machine Learning · Computer Science 2026-04-21 Adrien Aumon , Guy Wolf , Kevin R. Moon , Jake S. Rhodes

In this paper we provide an extended formulation for the class of constraint satisfaction problems and prove that its size is polynomial for instances whose constraint graph has bounded treewidth. This implies new upper bounds on extension…

Computational Complexity · Computer Science 2015-04-29 Petr Kolman , Martin Koutecký

The isomorphism problem is a fundamental problem in network analysis, which involves capturing both low-order and high-order structural information. In terms of extracting low-order structural information, graph isomorphism algorithms…

Data Structures and Algorithms · Computer Science 2023-07-28 Yifan Feng , Jiashu Han , Shihui Ying , Yue Gao

Tabular foundation models like TabPFN and TabICL achieve state-of-the-art performance through in-context learning, yet their architectures remain fundamentally opaque. We introduce KernelICL, a framework to enhance tabular foundation models…

Machine Learning · Computer Science 2026-02-03 Ratmir Miftachov , Bruno Charron , Simon Valentin

We optimize pipeline parallelism for deep neural network (DNN) inference by partitioning model graphs into $k$ stages and minimizing the running time of the bottleneck stage, including communication. We give practical and effective…

Machine Learning · Computer Science 2024-06-05 Aaron Archer , Matthew Fahrbach , Kuikui Liu , Prakash Prabhu

The Connected Vertex Cover problem, where the goal is to compute a minimum set of vertices in a given graph which forms a vertex cover and induces a connected subgraph, is a fundamental combinatorial problem and has received extensive…

Data Structures and Algorithms · Computer Science 2020-04-30 Diptapriyo Majumdar , M. S. Ramanujan , Saket Saurabh

We investigate the power of graph isomorphism algorithms based on algebraic reasoning techniques like Gr\"obner basis computation. The idea of these algorithms is to encode two graphs into a system of equations that are satisfiable if and…

Computational Complexity · Computer Science 2015-02-23 Christoph Berkholz , Martin Grohe

We present a general variational framework for the training of freeform nonlinearities in layered computational architectures subject to some slope constraints. The regularization that we add to the traditional training loss penalizes the…

Machine Learning · Statistics 2025-03-31 Michael Unser , Alexis Goujon , Stanislas Ducotterd

We describe a kernel of size 9k-8 for the NP-hard problem of computing the Tree Bisection and Reconnect (TBR) distance k between two unrooted binary phylogenetic trees. We achieve this by extending the existing portfolio of reduction rules…

Data Structures and Algorithms · Computer Science 2022-09-21 Steven Kelk , Simone Linz , Ruben Meuwese

This paper presents an algorithm, Voted Kernel Regularization , that provides the flexibility of using potentially very complex kernel functions such as predictors based on much higher-degree polynomial kernels, while benefitting from…

Machine Learning · Computer Science 2015-09-16 Corinna Cortes , Prasoon Goyal , Vitaly Kuznetsov , Mehryar Mohri

Kernel methods have achieved very good performance on large scale regression and classification problems, by using the Nystr\"om method and preconditioning techniques. The Nystr\"om approximation -- based on a subset of landmarks -- gives a…

Machine Learning · Computer Science 2020-02-21 Michaël Fanuel , Joachim Schreurs , Johan A. K. Suykens

Handling the ever-increasing scale of contemporary deep learning and transformer-based models poses a significant challenge. Overparameterized Transformer networks outperform prior art in Natural Language processing and Computer Vision.…

Machine Learning · Computer Science 2024-11-05 Soheil Zibakhsh Shabgahi , Mohammad Sohail Shariff , Farinaz Koushanfar

Regularization is an essential element of virtually all kernel methods for nonparametric regression problems. A critical factor in the effectiveness of a given kernel method is the type of regularization that is employed. This article…

Statistics Theory · Mathematics 2016-05-31 Lee H. Dicker , Dean P. Foster , Daniel Hsu

The maximum common subtree isomorphism problem asks for the largest possible isomorphism between subtrees of two given input trees. This problem is a natural restriction of the maximum common subgraph problem, which is ${\sf NP}$-hard in…

Data Structures and Algorithms · Computer Science 2016-08-23 Andre Droschinsky , Nils M. Kriege , Petra Mutzel

Interpolation and approximation of functionals with conditionally positive definite kernels is considered on sets of centers that are not determining for polynomials. It is shown that polynomial consistency is sufficient in order to define…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

Preconditioning is at the heart of iterative solutions of large, sparse linear systems of equations in scientific disciplines. Several algebraic approaches, which access no information beyond the matrix itself, are widely studied and used,…

Numerical Analysis · Mathematics 2025-01-28 Jie Chen