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Large language models adapt to new tasks through in-context learning (ICL) without parameter updates. Current theoretical explanations for this capability assume test tasks are drawn from a distribution similar to that seen during…

Machine Learning · Computer Science 2026-02-23 Di Zhang

Consensus is one of the most fundamental problems in distributed computing. This paper studies the consensus problem in a synchronous dynamic directed network, in which communication is controlled by an oblivious message adversary. The…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-04-06 Hugo Rincon Galeana , Ulrich Schmid , Kyrill Winkler , Ami Paz , Stefan Schmid

Collaborative working is increasingly popular, but it presents challenges due to the need for high responsiveness and disconnected work support. To address these challenges the data is optimistically replicated at the edges of the network,…

Databases · Computer Science 2012-12-12 Stéphane Martin , Mehdi Ahmed-Nacer , Pascal Urso

Adversarial attacks that generate small L_p-norm perturbations to mislead classifiers have limited success in black-box settings and with unseen classifiers. These attacks are also not robust to defenses that use denoising filters and to…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Ali Shahin Shamsabadi , Ricardo Sanchez-Matilla , Andrea Cavallaro

We revisit asynchronous computing in networks of crash-prone processes, under the asynchronous variant of the standard LOCAL model, recently introduced by Fraigniaud et al. [DISC 2022]. We focus on the vertex coloring problem, and our…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-21 Alkida Balliu , Pierre Fraigniaud , Patrick Lambein-Monette , Dennis Olivetti , Mikael Rabie

Conditional independence (CI) is central to causal inference, feature selection, and graphical modeling, yet it is untestable in many settings without additional assumptions. Existing CI tests often rely on restrictive structural…

Machine Learning · Computer Science 2025-12-23 Alek Frohlich , Vladimir Kostic , Karim Lounici , Daniel Perazzo , Massimiliano Pontil

We consider the well known Coordinated Attack Problem, where two generals have to decide on a common attack, when their messengers can be captured by the enemy. Informally, this problem represents the difficulties to agree in the presence…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-22 Emmanuel Godard , Eloi Perdereau

We consider the problem of making distributed computations robust to noise, in particular to worst-case (adversarial) corruptions of messages. We give a general distributed interactive coding scheme which simulates any asynchronous…

Data Structures and Algorithms · Computer Science 2017-02-27 Keren Censor-Hillel , Ran Gelles , Bernhard Haeupler

We present new randomized algorithms that improve the complexity of the classic $(\Delta+1)$-coloring problem, and its generalization $(\Delta+1)$-list-coloring, in three well-studied models of distributed, parallel, and centralized…

Data Structures and Algorithms · Computer Science 2018-11-06 Yi-Jun Chang , Manuela Fischer , Mohsen Ghaffari , Jara Uitto , Yufan Zheng

Graph coloring is fundamental to distributed computing. We give the first general treatment of the coloring of virtual graphs, where the graph $H$ to be colored is locally embedded within the communication graph $G$. Besides generalizing…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-21 Maxime Flin , Magnús M. Halldórsson , Alexandre Nolin

In this article I describe a research agenda for securing machine learning models against adversarial inputs at test time. This article does not present results but instead shares some of my thoughts about where I think that the field needs…

Machine Learning · Computer Science 2019-03-18 Ian Goodfellow

We study a sequential prediction problem in which an adversary is allowed to inject arbitrarily many adversarial instances in a stream of i.i.d. instances, but at each round, the learner may also abstain from making a prediction without…

Machine Learning · Computer Science 2026-03-19 Jialin Yu , Moïse Blanchard

We introduce a variant of the graph coloring problem, which we denote as {\sc Budgeted Coloring Problem} (\bcp). Given a graph $G$, an integer $c$ and an ordered list of integers $\{b_1, b_2, \ldots, b_c\}$, \bcp asks whether there exists a…

Data Structures and Algorithms · Computer Science 2021-10-28 Susobhan Bandopadhyay , Suman Banerjee , Aritra Banik , Venkatesh Raman

One popular hypothesis of neural network generalization is that the flat local minima of loss surface in parameter space leads to good generalization. However, we demonstrate that loss surface in parameter space has no obvious relationship…

Machine Learning · Computer Science 2018-10-16 Fuxun Yu , Chenchen Liu , Yanzhi Wang , Liang Zhao , Xiang Chen

The degree splitting problem requires coloring the edges of a graph red or blue such that each node has almost the same number of edges in each color, up to a small additive discrepancy. The directed variant of the problem requires…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-12-24 Mohsen Ghaffari , Juho Hirvonen , Fabian Kuhn , Yannic Maus , Jukka Suomela , Jara Uitto

This paper continues the study of a new variant of graph coloring with a connectivity constraint recently introduced by Hsieh et al. [COCOON 2024]. A path in a vertex-colored graph is called conflict-free if there is a color that appears…

Data Structures and Algorithms · Computer Science 2025-12-15 Carl Feghali , Hoang-Oanh Le , Van Bang Le

In this research, we introduce the concept of "computational entanglement," a phenomenon observed in overparameterized feedforward linear networks that enables the network to achieve zero loss by fitting random noise, even on previously…

Machine Learning · Computer Science 2024-10-01 YenLung Lai , Xingbo Dong , Zhe Jin

Identifying the sets of operations that can be executed simultaneously is an important problem appearing in many parallel applications. By modeling the operations and their interactions as a graph, one can identify the independent…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-07-28 Ahmet Erdem Sarıyüce , Erik Saule , Ümit V. Çatalyürek

Coded computing has proved to be useful in distributed computing. We have observed that almost all coded computing systems studied so far consider a setup of one master and some workers. However, recently emerging technologies such as…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-04-13 Nastaran Abadi Khooshemehr , Mohammad Ali Maddah-Ali

In the literature on adversarial examples, white box and black box attacks have received the most attention. The adversary is assumed to have either full (white) or no (black) access to the defender's model. In this work, we focus on the…

Machine Learning · Computer Science 2022-03-22 Shi Hu , Eric Nalisnick , Max Welling