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In many learning problems, the training and testing data follow different distributions and a particularly common situation is the \textit{covariate shift}. To correct for sampling biases, most approaches, including the popular kernel mean…

Machine Learning · Computer Science 2020-03-13 Henry Lam , Fengpei Li , Siddharth Prusty

This work interprets and generalizes consensus-type algorithms as switching dynamics leading to symmetrization of some vector variables with respect to the actions of a finite group. We show how the symmetrization framework we develop…

Quantum Physics · Physics 2015-06-17 Luca Mazzarella , Francesco Ticozzi , Alain Sarlette

A problem of developing the consensus protocols in public blockchain systems which spend a combination of energy and space resources is addressed. A technique is proposed that provides a flexibility for selection of the energy and space…

Cryptography and Security · Computer Science 2019-11-19 Miodrag J. Mihaljevic

Atomic broadcast is a reliable communication abstraction ensuring that all processes deliver the same set of messages in a common global order. It is a fundamental building block for implementing fault-tolerant services using either active…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-19 Manuel Bravo , Gregory Chockler , Alexey Gotsman , Alejandro Naser-Pastoriza , Christian Roldán

Off-policy evaluation methods are important in recommendation systems and search engines, where data collected under an existing logging policy is used to estimate the performance of a new proposed policy. A common approach to this problem…

Machine Learning · Computer Science 2023-01-04 Jaron J. R. Lee , David Arbour , Georgios Theocharous

Efficiently allocating incoming jobs to nodes in large-scale clusters can lead to substantial improvements in both cluster utilization and job performance. In order to allocate incoming jobs, cluster schedulers usually rely on a set of…

Machine Learning · Computer Science 2026-03-12 Martin Asenov , Qiwen Deng , Gingfung Yeung , Adam Barker

Censorship resistance with short-term inclusion guarantees is an important feature of decentralized systems, missing from many state-of-the-art and even deployed consensus protocols. In leader-based protocols the leader arbitrarily selects…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-19 Orestis Alpos , Bernardo David , Nikolas Kamarinakis , Dionysis Zindros

Effective token compression remains a critical challenge for scaling models to handle increasingly complex and diverse datasets. A novel mechanism based on contextual reinforcement is introduced, dynamically adjusting token importance…

Computation and Language · Computer Science 2025-08-11 Naderdel Piero , Zacharias Cromwell , Nathaniel Wainwright , Matthias Nethercott

The consensus control with optimal cost remains major challenging although consensus control problems have been well studied in recent years. In this paper, we study the consensus control of multi-agent system associated with a given cost…

Optimization and Control · Mathematics 2018-03-28 Juanjuan Xu , Huanshui Zhang

The amount of publicly available biomedical literature has been growing rapidly in recent years, yet question answering systems still struggle to exploit the full potential of this source of data. In a preliminary processing step, many…

Information Retrieval · Computer Science 2018-01-10 Ferenc Galkó , Carsten Eickhoff

Simulating mixtures of distributions with signed weights proves a challenge as standard simulation algorithms are inefficient in handling the negative weights. In particular, the natural representation of mixture variates as associated with…

Computation · Statistics 2025-06-17 Julien Stoehr , Christian P. Robert

This paper addresses the finite-time non-overshooting leader-following consensus problem for multi-agent systems, whose agents are modeled by a dynamical system topologically equivalent to the integrator chain. Based on the weighted…

Optimization and Control · Mathematics 2024-12-12 Min Li , Andrey Polyakov , Siyuan Wang , Gang Zheng

In this paper, we enhance the traditional confusion network system combination approach with an additional model trained by a neural network. This work is motivated by the fact that the commonly used binary system voting models only assign…

Computation and Language · Computer Science 2018-12-19 Markus Freitag , Jan-Thorsten Peter , Stephan Peitz , Minwei Feng , Hermann Ney

A distributed average consensus algorithm robust to a wide range of impulsive channel noise distributions is proposed. This work is the first of its kind in the literature to propose a consensus algorithm which relaxes the requirement of…

Systems and Control · Computer Science 2015-06-22 Sivaraman Dasarathan , Cihan Tepedelenlioglu , Mahesh Banavar , Andreas Spanias

Evolution Strategies (ES) emerged as a scalable alternative to popular Reinforcement Learning (RL) techniques, providing an almost perfect speedup when distributed across hundreds of CPU cores thanks to a reduced communication overhead.…

Machine Learning · Statistics 2018-11-13 Víctor Campos , Xavier Giro-i-Nieto , Jordi Torres

Quorum systems are a key abstraction in distributed fault-tolerant computing for capturing trust assumptions. They can be found at the core of many algorithms for implementing reliable broadcasts, shared memory, consensus and other…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-03 Orestis Alpos , Christian Cachin , Björn Tackmann , Luca Zanolini

Modern LLM reinforcement learning (RL) workloads require a highly efficient weight transfer system to scale training across heterogeneous computational resources. However, existing weight transfer approaches either fail to provide…

This paper provides a serious attempt towards constructing a switching-algebraic theory for weighted monotone voting systems, whether they are scalar-weighted or vector-weighted. The paper concentrates on the computation of a prominent…

Computer Science and Game Theory · Computer Science 2023-04-18 Ali Muhammad Rushdi , Muhammad Ali Rushdi

The paper presents a novel learning-based sampling strategy that guarantees rejection-free sampling of the free space under both biased and approximately uniform conditions, leveraging multivariate kernel densities. Historical data from a…

Robotics · Computer Science 2025-05-15 Thomas T. Enevoldsen , Roberto Galeazzi

Content caching is a widely studied technique aimed to reduce the network load imposed by data transmission during peak time while ensuring users' quality of experience. It has been shown that when there is a common link between caches and…

Information Theory · Computer Science 2021-10-20 Abdollah Ghaffari Sheshjavani , Ahmad Khonsari , Seyed Pooya Shariatpanahi , Masoumeh Moradian