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Variable length communication over a compound channel with feedback is considered. Traditionally, capacity of a compound channel without feedback is defined as the maximum rate that is determined before the start of communication such that…

Information Theory · Computer Science 2011-06-30 Aditya Mahajan , Sekhar Tatikonda

This work examines adaptive distributed learning strategies designed to operate under communication constraints. We consider a network of agents that must solve an online optimization problem from continual observation of streaming data.…

Machine Learning · Computer Science 2025-04-25 Marco Carpentiero , Vincenzo Matta , Ali H. Sayed

A communication setup is considered where a transmitter wishes to convey a message to a receiver and simultaneously estimates the state of that receiver through a common waveform. The state is estimated at the transmitter by means of…

Information Theory · Computer Science 2022-06-03 Mehrasa Ahmadipour , Mari Kobayashi , Miche`le Wigger , Giuseppe Caire

This paper designs traffic signal control policies for a network of signalized intersections without knowing the demand and parameters. Within a model predictive control (MPC) framework, control policies consist of an algorithm that…

Systems and Control · Electrical Eng. & Systems 2025-03-17 Zhexian Li , Ketan Savla

Visible light communications (VLC) is an emerging field in technology and research. Estimating the channel taps is a major requirement for designing reliable communication systems. Due to the nonlinear characteristics of the VLC channel…

Neural and Evolutionary Computing · Computer Science 2018-05-22 Anil Yesilkaya , Onur Karatalay , Arif Selcuk Ogrenci , Erdal Panayirci

Channel capacity describes the size of the nearly ideal channels, which can be obtained from many uses of a given channel, using an optimal error correcting code. In this paper we collect and compare minor and major variations in the…

Quantum Physics · Physics 2009-11-10 Dennis Kretschmann , Reinhard F Werner

Variational inequalities are a formalism that includes games, minimization, saddle point, and equilibrium problems as special cases. Methods for variational inequalities are therefore universal approaches for many applied tasks, including…

This paper addresses the problem of distributed state estimation via multiple access channels (MACs). We consider a scenario where two encoders are simultaneously communicating their measurements through a noisy channel. Firstly, the…

Systems and Control · Electrical Eng. & Systems 2022-12-23 Ghassen Zafzouf , Girish N. Nair , Farhad Farokhi

We derive a regularized formula for the common randomness assisted entanglement transmission capacity of finite arbitrarily varying quantum channels (AVQC's). For finite AVQC's with positive capacity for classical message transmission we…

Quantum Physics · Physics 2015-03-17 R. Ahlswede , I. Bjelakovic , H. Boche , J. Noetzel

In this work, the problem of communicating decisions of a classifier over a noisy channel is considered. With machine learning based models being used in variety of time-sensitive applications, transmission of these decisions in a reliable…

Information Theory · Computer Science 2024-04-24 Noel Teku , Sudarshan Adiga , Ravi Tandon

Consider the problem of a multiple access channel in a time dependent environment with a large number of users. In such a system, mostly due to practical constraints (e.g., decoding complexity), not all users can be scheduled together, and…

Information Theory · Computer Science 2018-11-07 Ori Shmuel , Asaf Cohen , Omer Gurewitz

Variational inequalities are a broad and flexible class of problems that includes minimization, saddle point, and fixed point problems as special cases. Therefore, variational inequalities are used in various applications ranging from…

Optimization and Control · Mathematics 2024-04-02 Aleksandr Beznosikov , Martin Takáč , Alexander Gasnikov

Motivated by large-scale optimization problems arising in the context of machine learning, there have been several advances in the study of asynchronous parallel and distributed optimization methods during the past decade. Asynchronous…

Machine Learning · Computer Science 2020-06-25 Mahmoud Assran , Arda Aytekin , Hamid Feyzmahdavian , Mikael Johansson , Michael Rabbat

Modeling the spread of social contagions is central to various applications in social computing. In this paper, we study the learnability of the competitive threshold model from a theoretical perspective. We demonstrate how competitive…

Machine Learning · Computer Science 2022-05-10 Yifan Wang , Guangmo Tong

We investigate the possibility of forcing a self-supervised model trained using a contrastive predictive loss to extract slowly varying latent representations. Rather than producing individual predictions for each of the future…

Distribution matching can be used to learn invariant representations with applications in fairness and robustness. Most prior works resort to adversarial matching methods but the resulting minimax problems are unstable and challenging to…

Machine Learning · Computer Science 2024-06-05 Ziyu Gong , Ben Usman , Han Zhao , David I. Inouye

In online advertising (Ad), advertisers are always eager to know how to globally optimize their budget allocation strategies across different channels for more conversions such as orders, payments, etc. Ignoring competition among different…

Computer Science and Game Theory · Computer Science 2023-05-12 Guangyuan Shen , Shenjie Sun , Dehong Gao , Shaolei Li , Libin Yang , Yongping Shi , Wei Ning

Strongly conflict-avoiding codes (SCACs) are employed in a slot-asynchronous multiple-access collision channel without feedback to guarantee that each active user can send at least one packet successfully in the worst case within a fixed…

Information Theory · Computer Science 2016-05-17 Yijin Zhang , Yuan-Hsun Lo , Wing Shing Wong

The wiretap channel models secure communication between two users in the presence of an eavesdropper who must be kept ignorant of transmitted messages. The performance of such a system is usually characterized by its secrecy capacity which…

Information Theory · Computer Science 2017-09-07 Holger Boche , Rafael F. Schaefer , H. Vincent Poor

Recent advances in deep learning have led to AI-based error correction decoders that report empirical performance improvements over traditional belief-propagation (BP) decoding on AWGN channels. While such gains are promising, a fundamental…

Information Theory · Computer Science 2026-02-03 Haoyu Lei , Mohammad Jalali , Chin Wa Lau , Farzan Farnia
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