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The evolution of mathematics is shaped importantly by interestingness: researchers choose which problems to pursue, and students choose which problems to engage with, based on expectations of interest and challenge. As AI systems,…

Model explainability is crucial for human users to be able to interpret how a proposed classifier assigns labels to data based on its feature values. We study generalized linear models constructed using sets of feature value rules, which…

Machine Learning · Statistics 2023-11-06 Sanjeeb Dash , Soumyadip Ghosh , Joao Goncalves , Mark S. Squillante

A graph $G = (V,E)$ is word-representable if there is a word $w$ over the alphabet $V$ such that $x$ and $y$ alternate in $w$ if and only if the edge $(x, y)$ is in $G$. It is known [6] that all $3$-colourable graphs are word-representable,…

Combinatorics · Mathematics 2018-10-01 Marc Elliot Glen

Evaluating the symbolic reasoning of large language models (LLMs) calls for geometry benchmarks that require multi-step proofs grounded in both text and diagrams. However, existing benchmarks are often limited in scale and rarely provide…

Computation and Language · Computer Science 2026-03-23 Yushun Zhang , Weiping Fu , Zesheng Yang , Bo Zhao , Lingling Zhang , Jian Zhang , Yumeng Fu , Jiaxing Huang , Jun Liu

The budgeted information gathering problem - where a robot with a fixed fuel budget is required to maximize the amount of information gathered from the world - appears in practice across a wide range of applications in autonomous…

Robotics · Computer Science 2016-11-15 Sanjiban Choudhury , Ashish Kapoor , Gireeja Ranade , Debadeepta Dey

Machine learning (ML) is being applied to a diverse and ever-growing set of domains. In many cases, domain experts - who often have no expertise in ML or data science - are asked to use ML predictions to make high-stakes decisions. Multiple…

Human-Computer Interaction · Computer Science 2021-09-21 Alexandra Zytek , Dongyu Liu , Rhema Vaithianathan , Kalyan Veeramachaneni

As Machine Learning (ML) systems becomes more ubiquitous, ensuring the fair and equitable application of their underlying algorithms is of paramount importance. We argue that one way to achieve this is to proactively cultivate public…

Computers and Society · Computer Science 2020-04-22 Eric Chu , Nabeel Gillani , Sneha Priscilla Makini

Customization has long been a central goal in interactive systems, yet prior work shows that end-user tailoring occurs infrequently and is often confined to initial setup or moments of breakdown. Recent advances in generative AI suggest…

Human-Computer Interaction · Computer Science 2026-05-13 Karthik Sreedhar , Aryan Kaul , Lydia B. Chilton

Graph clustering is a central topic in unsupervised learning with a multitude of practical applications. In recent years, multi-view graph clustering has gained a lot of attention for its applicability to real-world instances where one has…

Machine Learning · Computer Science 2024-06-10 Vincent Cohen-Addad , Tommaso d'Orsi , Silvio Lattanzi , Rajai Nasser

Handling graph data is one of the most difficult tasks. Traditional techniques, such as those based on geometry and matrix factorization, rely on assumptions about the data relations that become inadequate when handling large and complex…

Machine Learning · Computer Science 2024-04-15 Zhenyu Qian , Yiming Qian , Yuting Song , Fei Gao , Hai Jin , Chen Yu , Xia Xie

Inspired by a common technique for shuffling a deck of cards on a table without riffling, we continue the study of a prequel paper on the pile shuffle and its capabilities as a sorting device. We study two sort feasibility problems of…

Computational Complexity · Computer Science 2025-06-09 Kyle B. Treleaven

Given a graph $G=(V,E)$, the $b$-coloring problem consists in attributing a color to every vertex in $V$ such that adjacent vertices receive different colors, every color has a $b$-vertex, and the number of colors is maximized. A $b$-vertex…

Optimization and Control · Mathematics 2021-03-08 Rafael A. Melo , Michell F. Queiroz , Marcio C. Santos

Graph-based subspace clustering methods have exhibited promising performance. However, they still suffer some of these drawbacks: encounter the expensive time overhead, fail in exploring the explicit clusters, and cannot generalize to…

Machine Learning · Computer Science 2021-02-23 Zhao Kang , Zhiping Lin , Xiaofeng Zhu , Wenbo Xu

Scalable oversight studies methods of training and evaluating AI systems in domains where human judgment is unreliable or expensive, such as scientific research and software engineering in complex codebases. Most work in this area has…

Machine Learning · Computer Science 2024-10-22 Alex Mallen , Nora Belrose

In this work, our objective is to address the problems of generalization and flexibility for text recognition in documents. We introduce a new model that exploits the repetitive nature of characters in languages, and decouples the visual…

Computer Vision and Pattern Recognition · Computer Science 2020-09-15 Chuhan Zhang , Ankush Gupta , Andrew Zisserman

Graphs provide an efficient tool for object representation in various computer vision applications. Once graph-based representations are constructed, an important question is how to compare graphs. This problem is often formulated as a…

Machine Learning · Statistics 2010-04-30 Mikhail Zaslavskiy , Francis Bach , Jean-Philippe Vert

With the arrival of digital maps, the ubiquity of maps has increased sharply and new map functionalities have become available such as changing the scale on the fly or displaying/hiding layers. Users can now interact with maps on multiple…

Human-Computer Interaction · Computer Science 2019-09-05 Christian Kray , Auriol Degbelo

Many puzzle video games, like Sokoban, involve moving some agent in a maze. The reachable locations are usually apparent for a human player, and the difficulty of the game is mainly related to performing actions on objects, such as pushing…

Artificial Intelligence · Computer Science 2023-10-03 Miquel Bofill , Cristina Borralleras , Joan Espasa , Mateu Villaret

Data visualizations present a massive number of potential messages to an observer. One might notice that one group's average is larger than another's, or that a difference in values is smaller than a difference between two others, or any of…

Human-Computer Interaction · Computer Science 2023-08-28 Racquel Fygenson , Steven Franconeri , Enrico Bertini

Graph clustering has many important applications in computing, but due to the increasing sizes of graphs, even traditionally fast clustering methods can be computationally expensive for real-world graphs of interest. Scalability problems…

Social and Information Networks · Computer Science 2018-10-18 Kimon Fountoulakis , David F. Gleich , Michael W. Mahoney