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Linear sequence modeling approaches, such as linear attention, provide advantages like linear-time training and constant-memory inference over sequence lengths. However, existing sequence parallelism (SP) methods are either not optimized…

Machine Learning · Computer Science 2025-02-12 Weigao Sun , Disen Lan , Yiran Zhong , Xiaoye Qu , Yu Cheng

This paper considers the problem of sensory data scheduling of multiple processes. There are $n$ independent linear time-invariant processes and a remote estimator monitoring all the processes. Each process is measured by a sensor, which…

Systems and Control · Computer Science 2017-03-28 Shuang Wu , Xiaoqiang Ren , Subhrakanti Dey , Ling Shi

We study the problem of robust time series analysis under the standard auto-regressive (AR) time series model in the presence of arbitrary outliers. We devise an efficient hard thresholding based algorithm which can obtain a consistent…

Machine Learning · Computer Science 2016-07-04 Kush Bhatia , Prateek Jain , Parameswaran Kamalaruban , Purushottam Kar

We consider the design of a linear sensing system with a fixed energy budget assuming that the sampling noise is the dominant noise source. The energy constraint implies that the signal energy per measurement decreases linearly with the…

Signal Processing · Electrical Eng. & Systems 2019-05-22 Yang Lu , Wei Dai , Yonina C. Eldar

We study the complexity of finding communication trees with the lowest possible completion time for rooted, irregular gather and scatter collective communication operations in fully connected, $k$-ported communication networks under a…

Computational Complexity · Computer Science 2018-11-28 Jesper Larsson Träff

We revisit the error correction scheme of real-valued signals when the codeword is corrupted by gross errors on a fraction of entries and a small noise on all the entries. Combining the recent developments of approximate message passing and…

Information Theory · Computer Science 2014-02-04 Jean Barbier , Florent Krzakala , Lenka Zdeborová , Pan Zhang

The efficient communication of noisy data has applications in several areas of machine learning, such as neural compression or differential privacy, and is also known as reverse channel coding or the channel simulation problem. Here we…

Information Theory · Computer Science 2022-05-26 Lucas Theis , Noureldin Yosri

The study of stable matchings usually relies on the assumption that agents' preferences over the opposite side are complete and known. In many real markets, however, preferences might be uncertain and revealed only through costly…

Computer Science and Game Theory · Computer Science 2026-02-25 Moshe Babaioff , Rotem Gil , Assaf Romm

This paper considers a wireless network where multiple flows are delivering status updates about their respective information sources. An end user aims to make accurate real-time estimations about the status of each information source using…

Networking and Internet Architecture · Computer Science 2019-01-31 Daojing Guo , I-Hong Hou

Emerging software-defined networking technologies enable more adaptive communication infrastructures, allowing for quick reactions to changes in networking requirements by exploiting the workload's temporal structure. However, operating…

Networking and Internet Architecture · Computer Science 2022-11-08 Monika Henzinger , Ami Paz , Arash Pourdamghani , Stefan Schmid

In this paper, we consider a status update system, in which update packets are sent to the destination via a wireless medium that allows for multiple rates, where a higher rate also naturally corresponds to a higher error probability. The…

Information Theory · Computer Science 2021-01-01 Guidan Yao , Ahmed M. Bedewy , Ness B. Shroff

It has been well established that wireless network coding can significantly improve the efficiency of multi-hop wireless networks. However, in a stochastic environment some of the packets might not have coding pairs, which limits the number…

Optimization and Control · Mathematics 2015-03-19 Yu-Pin Hsu , Navid Abedini , Natarajan Gautam , Alex Sprintson , Srinivas Shakkottai

Synchronous federated learning (FL) scales poorly with the number of clients due to the straggler effect. Algorithms like FedAsync and GeneralizedFedAsync address this limitation by enabling asynchronous communication between clients and…

Machine Learning · Computer Science 2025-10-23 Abdelkrim Alahyane , Céline Comte , Matthieu Jonckheere , Éric Moulines

Approximate message passing is an iterative algorithm for compressed sensing and related applications. A solid theory about the performance and convergence of the algorithm exists for measurement matrices having iid entries of zero mean.…

Information Theory · Computer Science 2014-10-03 Francesco Caltagirone , Florent Krzakala , Lenka Zdeborová

Various legacy and emerging industrial control applications create the requirement of periodic and time-sensitive communication (TSC) for 5G/6G networks. State-of-the-art semi-persistent scheduling (SPS) techniques fall short of meeting the…

Networking and Internet Architecture · Computer Science 2021-09-06 Nan Jiang , Adnan Aijaz , Yichao Jin

Efficient channel state information (CSI) compression is essential in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems due to the substantial feedback overhead. Recently, deep learning-based…

Information Theory · Computer Science 2026-05-19 Mehdi Sattari , Deniz Gündüz , Tommy Svensson

Distributed learning techniques such as federated learning have enabled multiple workers to train machine learning models together to reduce the overall training time. However, current distributed training algorithms (centralized or…

Machine Learning · Computer Science 2020-02-25 Zhenheng Tang , Shaohuai Shi , Xiaowen Chu

This study considers a wireless network where multiple nodes transmit status updates to a base station (BS) via a shared, error-free channel with limited bandwidth. The status updates arrive at each node randomly. We use the Age of…

Information Theory · Computer Science 2025-03-14 Yuqiao He , Yuchao Chen , Jintao Wang , Jian Song

This paper studies the performance of a transmission and reception scheme for massive access under some practical challenges. One challenge is the near-far problem, i.e., an access point often receives signals from different transmitting…

Information Theory · Computer Science 2023-05-15 Lina Liu , Dongning Guo

We propose application-layer coding schemes to recover lost data in delay-sensitive uplink (sensor-to-gateway) communications in the Internet of Things. Built on an approach that combines retransmissions and forward erasure correction, the…

Information Theory · Computer Science 2022-07-26 Vatsalya Chaubey , Siddhartha S. Borkotoky