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We study consistency of learning algorithms for a multi-class performance metric that is a non-decomposable function of the confusion matrix of a classifier and cannot be expressed as a sum of losses on individual data points; examples of…

Machine Learning · Computer Science 2015-01-05 Harish G. Ramaswamy , Harikrishna Narasimhan , Shivani Agarwal

Learning distribution families over $\mathbb{R}^d$ is a fundamental problem in unsupervised learning and statistics. A central question in this setting is whether a given family of distributions possesses sufficient structure to be (at…

Machine Learning · Statistics 2025-06-10 Arefe Boushehrian , Amir Najafi

This thesis investigates the central role of homomorphism problems (structure-preserving maps) in two complementary domains: database querying over finite, graph-shaped data, and constraint solving over (potentially infinite) structures.…

Logic in Computer Science · Computer Science 2025-10-10 Rémi Morvan

One of the central problems in the study of parametrized constraint satisfaction problems is the Dichotomy Conjecture by T. Feder and M. Vardi stating that the constraint satisfaction problem (CSP) over a fixed, finite constraint language…

Computational Complexity · Computer Science 2017-12-12 Dejan Delić

This work investigates structural and computational aspects of list-based graph coloring under interval constraints. Building on the framework of analogous and p-analogous problems, we show that classical List Coloring, $\mu$-coloring, and…

Computational Complexity · Computer Science 2025-12-22 Simone Ingrid Monteiro Gama , Rosiane de Freitas Rodrigues

As a fundamental problem in pattern recognition, graph matching has applications in a variety of fields, from computer vision to computational biology. In graph matching, patterns are modeled as graphs and pattern recognition amounts to…

Computer Vision and Pattern Recognition · Computer Science 2008-06-19 Tiberio S. Caetano , Julian J. McAuley , Li Cheng , Quoc V. Le , Alex J. Smola

We study stochastic optimization with data-adaptive sampling schemes to train pairwise learning models. Pairwise learning is ubiquitous, and it covers several popular learning tasks such as ranking, metric learning and AUC maximization. A…

Machine Learning · Computer Science 2025-04-10 Sijia Zhou , Yunwen Lei , Ata Kabán

Certifying feasibility in decision-making, critical in many industries, can be framed as a constraint satisfaction problem. This paper focuses on characterising a subset of parameter values from an a priori set that satisfy constraints on a…

Systems and Control · Electrical Eng. & Systems 2025-11-14 Max Mowbray , Nilay Shah , Benoît Chachuat

We consider here the problem of obtaining reliable, consistent information from inconsistent databases -- databases that do not have to satisfy given integrity constraints. We use the notion of consistent query answer -- a query answer…

Databases · Computer Science 2007-05-23 Jan Chomicki , Jerzy Marcinkowski

We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Previous approaches to this problem, such as those of Chow ([1]),…

Machine Learning · Computer Science 2012-07-19 Mukund Narasimhan , Jeff A. Bilmes

Monotone learning describes learning processes in which expected performance consistently improves as the amount of training data increases. However, recent studies challenge this conventional wisdom, revealing significant gaps in the…

Machine Learning · Computer Science 2025-05-22 Ming Li , Chenyi Zhang , Qin Li

We introduce some classical complexity-theoretic techniques to Parameterized Complexity. First, we study relativization for the machine models that were used by Chen, Flum, and Grohe (2005) to characterize a number of parameterized…

Computational Complexity · Computer Science 2018-07-18 Ralph Christian Bottesch

To determine if two lists of numbers are the same set, we sort both lists and see if we get the same result. The sorted list is a canonical form for the equivalence relation of set equality. Other canonical forms arise in graph isomorphism…

Computational Complexity · Computer Science 2011-06-30 Lance Fortnow , Joshua A. Grochow

Following the wide-spread adoption of machine learning models in real-world applications, the phenomenon of performativity, i.e. model-dependent shifts in the test distribution, becomes increasingly prevalent. Unfortunately, since models…

Machine Learning · Statistics 2026-01-21 Ivan Kirev , Lyuben Baltadzhiev , Nikola Konstantinov

Score matching is a recently developed parameter learning method that is particularly effective to complicated high dimensional density models with intractable partition functions. In this paper, we study two issues that have not been…

Machine Learning · Computer Science 2012-05-14 Siwei Lyu

Let $G$ be a graph such that each vertex has its list of available colors, and assume that each list is a subset of the common set consisting of $k$ colors. For two given list colorings of $G$, we study the problem of transforming one into…

Data Structures and Algorithms · Computer Science 2017-05-23 Tatsuhiko Hatanaka , Takehiro Ito , Xiao Zhou

We consider the following natural graph cut problem called Critical Node Cut (CNC): Given a graph $G$ on $n$ vertices, and two positive integers $k$ and $x$, determine whether $G$ has a set of $k$ vertices whose removal leaves $G$ with at…

Data Structures and Algorithms · Computer Science 2015-06-30 Danny Hermelin , Moshe Kaspi , Christian Komusiewicz , Barak Navon

Correctness of concurrent objects is defined in terms of safety properties such as linearizability, sequential consistency, and quiescent consistency, and progress properties such as wait-, lock-, and obstruction-freedom. These properties,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-07 Brijesh Dongol , Lindsay Groves

A matching is a set of edges in a graph with no common endpoint. A matching M is called acyclic if the induced subgraph on the endpoints of the edges in M is acyclic. Given a graph G and an integer k, Acyclic Matching Problem seeks for an…

Computational Complexity · Computer Science 2022-10-05 Sahab Hajebi , Ramin Javadi

Linear stochastic transitivity is a central assumption in paired comparison models that is rarely verified in practice. Empirical violations, however, are common and can substantially affect inference and ranking. We develop a class of…

Methodology · Statistics 2026-04-02 Rahul Singh , Ori Davidov