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We study the efficient computation of Shapley values for \emph{product games} -- cooperative games in which the coalition value factorizes as a product of per-player terms. Such games arise in machine learning explainability whenever the…

Machine Learning · Computer Science 2026-05-19 Majid Mohammadi , Grigory Reznikov , Pavel Sinitcyn , Krikamol Muandet , Siu Lun Chau

Consider a multi-class labelling problem, where the labels can take values in $[k]$, and a predictor predicts a distribution over the labels. In this work, we study the following foundational question: Are there notions of multi-class…

Machine Learning · Computer Science 2024-06-11 Parikshit Gopalan , Lunjia Hu , Guy N. Rothblum

We study the efficient learnability of low-degree polynomial threshold functions (PTFs) in the presence of a constant fraction of adversarial corruptions. Our main algorithmic result is a polynomial-time PAC learning algorithm for this…

Data Structures and Algorithms · Computer Science 2024-04-02 Ilias Diakonikolas , Daniel M. Kane , Vasilis Kontonis , Sihan Liu , Nikos Zarifis

This paper shows that causal model discovery is not an NP-hard problem, in the sense that for sparse graphs bounded by node degree k the sound and complete causal model can be obtained in worst case order N^{2(k+2)} independence tests, even…

Artificial Intelligence · Computer Science 2013-09-27 Tom Claassen , Joris Mooij , Tom Heskes

The key limiting factor in graphical model inference and learning is the complexity of the partition function. We thus ask the question: what are general conditions under which the partition function is tractable? The answer leads to a new…

Machine Learning · Computer Science 2012-02-20 Hoifung Poon , Pedro Domingos

Graph Neural Networks (GNNs) have made significant advances on several fundamental inference tasks. As a result, there is a surge of interest in using these models for making potentially important decisions in high-regret applications.…

Machine Learning · Computer Science 2020-02-26 Kaidi Xu , Sijia Liu , Pin-Yu Chen , Mengshu Sun , Caiwen Ding , Bhavya Kailkhura , Xue Lin

We study the \emph{{interval completion}} problem, which asks for the insertion of a set of at most $k$ edges to make a graph of $n$ vertices into an interval graph. We focus on chordal graphs with no small obstructions, where every…

Data Structures and Algorithms · Computer Science 2013-06-14 Yixin Cao

This article contains detailed proofs and additional examples related to the UAI-2013 submission `Learning Sparse Causal Models is not NP-hard'. It describes the FCI+ algorithm: a method for sound and complete causal model discovery in the…

Machine Learning · Statistics 2014-11-07 Tom Claassen , Joris M. Mooij , Tom Heskes

The global Lipschitz constant of a neural network is related to robustness and generalization, yet unlike in many classical models, it is not plainly legible from the parameters. This has motivated sophisticated verification algorithms,…

Machine Learning · Computer Science 2026-05-11 Simon Kuang , Yuezhu Xu , S. Sivaranjani , Xinfan Lin

Motivated by questions in robust control and switched linear dynamical systems, we consider the problem checking whether all convex combinations of k matrices in R^{n x n} are stable. In particular, we are interested whether there exist…

Optimization and Control · Mathematics 2009-01-15 L. Gurvits , A. Olshevsky

The max-cut problem is a classical graph theory problem which is NP-complete. The best polynomial time approximation scheme relies on \emph{semidefinite programming} (SDP). We study the conditions under which graphs of certain classes have…

Optimization and Control · Mathematics 2021-09-07 Daniel Hong , Hyunwoo Lee , Alex Wei

We study the computational complexity of the map redistricting problem (gerrymandering). Mathematically, the electoral district designer (gerrymanderer) attempts to partition a weighted graph into $k$ connected components (districts) such…

Computer Science and Game Theory · Computer Science 2024-01-09 Jack Dippel , Max Dupré la Tour , April Niu , Sanjukta Roy , Adrian Vetta

Causal modeling has long been an attractive topic for many researchers and in recent decades there has seen a surge in theoretical development and discovery algorithms. Generally discovery algorithms can be divided into two approaches:…

Machine Learning · Statistics 2017-02-06 Ridho Rahmadi , Perry Groot , Marianne Heins , Hans Knoop , Tom Heskes

We study the fundamental tradeoffs between computational tractability and statistical accuracy for a general family of hypothesis testing problems with combinatorial structures. Based upon an oracle model of computation, which captures the…

Machine Learning · Statistics 2015-12-31 Zhaoran Wang , Quanquan Gu , Han Liu

Efficient computability is an important property of solution concepts in matching markets. We consider the computational complexity of finding and verifying various solution concepts in trading networks-multi-sided matching markets with…

Computational Complexity · Computer Science 2025-10-03 Tamás Fleiner , Zsuzsanna Jankó , Ildikó Schlotter , Alexander Teytelboym

Recent studies have examined the computational complexity of computing Shapley additive explanations (also known as SHAP) across various models and distributions, revealing their tractability or intractability in different settings.…

Machine Learning · Computer Science 2025-02-19 Reda Marzouk , Shahaf Bassan , Guy Katz , Colin de la Higuera

Verifying the robustness of machine learning models against evasion attacks at test time is an important research problem. Unfortunately, prior work established that this problem is NP-hard for decision tree ensembles, hence bound to be…

Machine Learning · Computer Science 2023-11-14 Stefano Calzavara , Lorenzo Cazzaro , Giulio Ermanno Pibiri , Nicola Prezza

We study the algorithmic complexity of Maker-Breaker games played on the edge sets of general graphs. We mainly consider the perfect matching game and the $H$-game. Maker wins if she claims the edges of a perfect matching in the first, and…

Computational Complexity · Computer Science 2024-11-18 Eric Duchêne , Valentin Gledel , Fionn Mc Inerney , Nicolas Nisse , Nacim Oijid , Aline Parreau , Miloš Stojaković

In this paper the computational complexity of the (bi)simulation problem over restricted graph classes is studied. For trees given as pointer structures or terms the (bi)simulation problem is complete for logarithmic space or NC$^1$,…

Logic in Computer Science · Computer Science 2023-06-22 Moses Ganardi , Stefan Göller , Markus Lohrey

We reveal a complexity chasm, separating the trinomial and tetranomial cases, for solving univariate sparse polynomial equations over certain local fields. First, for any fixed field $K\in\{\mathbb{Q}_2,\mathbb{Q}_3,\mathbb{Q}_5,\ldots\}$,…

Number Theory · Mathematics 2021-06-08 J. Maurice Rojas , Yuyu Zhu
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