Tootfinder

Queuing dynamics of asynchronous Federated Learning
Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines
https://arxiv.org/abs/2405.00017 htt…

Queuing dynamics of asynchronous Federated Learning
We study asynchronous federated learning mechanisms with nodes having potentially different computational speeds. In such an environment, each node is allowed to work on models with potential delays and contribute to updates to the central server at its own pace. Existing analyses of such algorithms typically depend on intractable quantities such as the maximum node delay and do not consider the underlying queuing dynamics of the system. In this paper, we propose a non-uniform sampling scheme f…

Scale-Robust Timely Asynchronous Decentralized Learning
Purbesh Mitra, Sennur Ulukus
https://arxiv.org/abs/2404.19749 https://arxiv.o…

Scale-Robust Timely Asynchronous Decentralized Learning
We consider an asynchronous decentralized learning system, which consists of a network of connected devices trying to learn a machine learning model without any centralized parameter server. The users in the network have their own local training data, which is used for learning across all the nodes in the network. The learning method consists of two processes, evolving simultaneously without any necessary synchronization. The first process is the model update, where the users update their local…

Unifying Asynchronous Logics for Hyperproperties
Alberto Bombardelli, Laura Bozzelli, C\'esar S\'anchez, Stefano Tonetta
https://arxiv.org/abs/2404.16778

Unifying Asynchronous Logics for Hyperproperties
We introduce and investigate a powerful hyper logical framework in the linear-time setting, we call generalized HyperLTL with stuttering and contexts (GHyperLTL_SC for short). GHyperLTL_SC unifies known asynchronous extensions of HyperLTL and the well-known extension KLTL of LTL with knowledge modalities under both the synchronous and asynchronous perfect recall semantics. As a main contribution, we individuate a meaningful fragment of GHyperLTL_SC, we call simple GHyperLTL_SC, with a decidable…

This https://arxiv.org/abs/2403.05793 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Performance Bounds for Passive Sensing in Asynchronous ISAC Systems -- Appendices
This document contains the appendices for our paper titled ``Performance Bounds for Passive Sensing in Asynchronous ISAC Systems." The appendices include rigorous derivations of key formulas, detailed proofs of the theorems and propositions introduced in the paper, and details of the algorithm tested in the numerical simulation for validation. These appendices aim to support and elaborate on the findings and methodologies presented in the main text. All external references to equations, theorem…

Asynchronous Neuromorphic Optimization with Lava
Shay Snyder (George Mason University), Sumedh R. Risbud (Intel Labs), Maryam Parsa (George Mason University)
https://arxiv.org/abs/2404.17052

Asynchronous Neuromorphic Optimization with Lava
Performing optimization with event-based asynchronous neuromorphic systems presents significant challenges. Intel's neuromorphic computing framework, Lava, offers an abstract application programming interface designed for constructing event-based computational graphs. In this study, we introduce a novel framework tailored for asynchronous Bayesian optimization that is also compatible with Loihi 2. We showcase the capability of our asynchronous optimization framework by connecting it with a grap…

This https://arxiv.org/abs/2106.10362 has been replaced.
link: https://scholar.google.com/scholar?q=a

Jolteon and Ditto: Network-Adaptive Efficient Consensus with Asynchronous Fallback
Existing committee-based Byzantine state machine replication (SMR) protocols, typically deployed in production blockchains, face a clear trade-off: (1) they either achieve linear communication cost in the happy path, but sacrifice liveness during periods of asynchrony, or (2) they are robust (progress with probability one) but pay quadratic communication cost. We believe this trade-off is unwarranted since existing linear protocols still have asymptotic quadratic cost in the worst case. We desi…

This https://arxiv.org/abs/2210.06186 has been replaced.
link: https://scholar.google.com/scholar?q=a

GOTCHA: Real-Time Video Deepfake Detection via Challenge-Response
With the rise of AI-enabled Real-Time Deepfakes (RTDFs), the integrity of online video interactions has become a growing concern. RTDFs have now made it feasible to replace an imposter's face with their victim in live video interactions. Such advancement in deepfakes also coaxes detection to rise to the same standard. However, existing deepfake detection techniques are asynchronous and hence ill-suited for RTDFs. To bridge this gap, we propose a challenge-response approach that establishes auth…

How Allegro reduced latency outliers by 82% by switching to #XFS:
https://blog.allegro.tech/2024/03/kafka-performance-analysis.html
"'Using a com…

Unlocking Kafka's Potential: Tackling Tail Latency with eBPF
At Allegro, we use Kafka as a backbone for asynchronous communication between microservices. With up to 300k messages published and 1M messages consumed every second, it is a key part of our infrastructure. A few months ago, in our main Kafka cluster, we noticed the following discrepancy: while median response times for produce requests were in single-digit milliseconds, the tail latency was much worse. Namely, the p99 latency was up to 1 second, and the p999 latency was up to 3 seconds. This w…

Joint Activity-Delay Detection and Channel Estimation for Asynchronous Massive Random Access: A Free Probability Theory Approach
Xinyu Bian, Yuyi Mao, Jun Zhang
https://arxiv.org/abs/2402.17996

Joint Activity-Delay Detection and Channel Estimation for Asynchronous Massive Random Access: A Free Probability Theory Approach
Grant-free random access (RA) has been recognized as a promising solution to support massive connectivity due to the removal of the uplink grant request procedures. While most endeavours assume perfect synchronization among users and the base station, this paper investigates asynchronous grant-free massive RA, and develop efficient algorithms for joint user activity detection, synchronization delay detection, and channel estimation. Considering the sparsity on user activity, we formulate a spar…

Event-Triggered Resilient Filtering for 2-D Systems with Asynchronous-Delay: Handling Binary Encoding Decoding with Probabilistic Bit Flips
Yu Chen, Wei Wang
https://arxiv.org/abs/2404.16408

Event-Triggered Resilient Filtering for 2-D Systems with Asynchronous-Delay: Handling Binary Encoding Decoding with Probabilistic Bit Flips
In this paper, the event-triggered resilient filtering problem is investigated for a class of two-dimensional systems with asynchronous-delay under binary encoding-decoding schemes with probabilistic bit flips. To reduce unnecessary communications and computations in complex network systems, alleviate network energy consumption, and optimize the use of network resources, a new event-triggered mechanism is proposed, which focuses on broadcasting necessary measurement information to update innova…