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We consider deterministic distributed algorithms for reaching agreement in synchronous networks of arbitrary topologies. Links are bi-directional and prone to failures while nodes stay non-faulty at all times. A faulty link may omit…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-27 Bogdan S. Chlebus , Dariusz R. Kowalski , Jan Olkowski , Jedrzej Olkowski

Distributed algorithms and theories are called for in this era of big data. Under weaker local signal-to-noise ratios, we improve upon the celebrated one-round distributed principal component analysis (PCA) algorithm designed in the spirit…

Methodology · Statistics 2025-07-01 ZeYu Li , Xinsheng Zhang , Wang Zhou

Achieving agreement among distributed parties is a fundamental task in modern systems, underpinning applications such as consensus in blockchains, coordination in cloud infrastructure, and fault tolerance in critical services. However, this…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-18 Andrei Constantinescu , Marc Dufay , Anton Paramonov , Roger Wattenhofer

Nearly thirty years ago, it was shown that $\Omega(\sqrt{n})$ registers are needed to solve obstruction-free consensus among $n$ processes. This lower bound was improved to $n$ registers in 2018, which exactly matches the best upper bound.…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-04 Sean Ovens

This work introduces RARE (Retrieval-Augmented Reasoning Enhancement), a versatile extension to the mutual reasoning framework (rStar), aimed at enhancing reasoning accuracy and factual integrity across large language models (LLMs) for…

Computation and Language · Computer Science 2025-06-03 Hieu Tran , Zonghai Yao , Junda Wang , Yifan Zhang , Zhichao Yang , Hong Yu

Prefix caching is a key latency optimization for autoregressive LLM serving, yet existing systems assume dense per-token key/value reuse. State-space models change the structure of the problem: a recurrent layer can resume from a single…

Machine Learning · Computer Science 2026-05-08 Mikhail Shirokikh , Sergey Nikolenko

The Lasso is one of the most important approaches for parameter estimation and variable selection in high dimensional linear regression. At the heart of its success is the attractive rate of convergence result even when $p$, the dimension…

Statistics Theory · Mathematics 2019-08-09 Junlong Zhao , Chenlei Leng

In this paper, we consider the "foreach" sparse recovery problem with failure probability $p$. The goal of which is to design a distribution over $m \times N$ matrices $\Phi$ and a decoding algorithm $\algo$ such that for every…

Data Structures and Algorithms · Computer Science 2013-04-24 Anna C. Gilbert , Hung Q. Ngo , Ely Porat , Atri Rudra , Martin J. Strauss

The computational complexity of internal diffusion-limited aggregation (DLA) is examined from both a theoretical and a practical point of view. We show that for two or more dimensions, the problem of predicting the cluster from a given set…

Condensed Matter · Physics 2007-05-23 Cristopher Moore , Jonathan Machta

Communication for omniscience (CO) refers to the problem where the users in a finite set $V$ observe a discrete multiple random source and want to exchange data over broadcast channels to reach omniscience, the state where everyone recovers…

Information Theory · Computer Science 2020-12-22 Ni Ding , Parastoo Sadeghi , Thierry Rakotoarivelo

In prior work, Gupta et al. (SPAA 2022) presented a distributed algorithm for multiplying sparse $n \times n$ matrices, using $n$ computers. They assumed that the input matrices are uniformly sparse--there are at most $d$ non-zeros in each…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-24 Chetan Gupta , Janne H. Korhonen , Jan Studený , Jukka Suomela , Hossein Vahidi

Cross-Encoder (CE) and Dual-Encoder (DE) models are two fundamental approaches for query-document relevance in information retrieval. To predict relevance, CE models use joint query-document embeddings, while DE models maintain factorized…

Preference-based alignment methods (e.g., RLHF, DPO) typically optimize a single scalar objective, implicitly averaging over heterogeneous human preferences. In practice, systematic annotator and user-group disagreement makes mean-reward…

Machine Learning · Computer Science 2026-05-19 Mingxi Zou , Jiaxiang Chen , Junfan Li , Langzhang Liang , Qifan Wang , Xu Yinghui , Zenglin Xu

In the $\varepsilon$-Consensus-Halving problem, a fundamental problem in fair division, there are $n$ agents with valuations over the interval $[0,1]$, and the goal is to divide the interval into pieces and assign a label "$+$" or "$-$" to…

Computational Complexity · Computer Science 2023-04-26 Aris Filos-Ratsikas , Alexandros Hollender , Katerina Sotiraki , Manolis Zampetakis

For over a decade now we have been witnessing the success of {\em massive parallel computation} (MPC) frameworks, such as MapReduce, Hadoop, Dryad, or Spark. One of the reasons for their success is the fact that these frameworks are able to…

Data Structures and Algorithms · Computer Science 2018-02-02 Artur Czumaj , Jakub Łącki , Aleksander Mądry , Slobodan Mitrović , Krzysztof Onak , Piotr Sankowski

Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challenging, especially when correctness diverges from surface-level majority agreement. Existing…

Computation and Language · Computer Science 2026-04-15 Manh Nguyen , Sunil Gupta , Hung Le

A consensus tree is a phylogenetic tree that captures the similarity between a set of conflicting phylogenetic trees. The problem of computing a consensus tree is a major step in phylogenetic tree reconstruction. It also finds applications…

Data Structures and Algorithms · Computer Science 2017-07-05 Paweł Gawrychowski , Gad M. Landau , Wing-Kin Sung , Oren Weimann

A lattice is a partially-ordered set in which every pair of elements has a unique meet (greatest lower bound) and join (least upper bound). We present new data structures for lattices that are simple, efficient, and nearly optimal in terms…

Data Structures and Algorithms · Computer Science 2020-06-17 J. Ian Munro , Bryce Sandlund , Corwin Sinnamon

We consider a robust aggregation problem in the presence of both truthful and adversarial experts. The truthful experts will report their private signals truthfully, while the adversarial experts can report arbitrarily. We assume experts…

Machine Learning · Computer Science 2025-02-07 Yongkang Guo , Yuqing Kong

We present Areon, a family of latency-friendly, stake-weighted, multi-proposer proof-of-stake consensus protocols. By allowing multiple proposers per slot and organizing blocks into a directed acyclic graph (DAG), Areon achieves robustness…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-01 Álvaro Castro-Castilla , Marcin Pawlowski , Hong-Sheng Zhou