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In this paper, we propose a coding scheme based on polar codes for empirical coordination of autonomous devices. We consider a two-node network with a noisy link in which the input and output signals have to be coordinated with the source…

Information Theory · Computer Science 2018-02-28 Giulia Cervia , Laura Luzzi , Maël Le Treust , Matthieu R. Bloch

Causal inference is a critical research topic across many domains, such as statistics, computer science, education, public policy and economics, for decades. Nowadays, estimating causal effect from observational data has become an appealing…

Methodology · Statistics 2020-02-10 Liuyi Yao , Zhixuan Chu , Sheng Li , Yaliang Li , Jing Gao , Aidong Zhang

We investigate distributed source coding of two correlated sources X and Y where messages are passed to a decoder in a cascade fashion. The encoder of X sends a message at rate R_1 to the encoder of Y. The encoder of Y then sends a message…

Information Theory · Computer Science 2009-05-13 Paul Cuff , Han-I Su , Abbas El Gamal

We study the effects of quantum entanglement on the performance of two classical zero-error communication tasks among multiple parties. Both tasks are generalizations of the two-party zero-error channel-coding problem, where a sender and a…

Quantum Physics · Physics 2015-01-21 Teresa Piovesan , Giannicola Scarpa , Christian Schaffner

Joint source-channel coding is a compelling paradigm when low-latency and low-complexity communication is required. This work proposes a theoretical framework that integrates classification and anomaly detection within the conventional…

Signal Processing · Electrical Eng. & Systems 2025-09-18 Andriy Enttsel , Weichen Wang , Mauro Mangia , Riccardo Rovatti , Deniz Gündüz

This paper investigates variable-length stop-feedback codes for memoryless channels in point-to-point, multiple access, and random access communication scenarios. The proposed codes employ $L$ decoding times $n_1, n_2, \dots, n_L$ for the…

Information Theory · Computer Science 2023-12-12 Recep Can Yavas , Victoria Kostina , Michelle Effros

Market generators using deep generative models have shown promise for synthetic financial data generation, but existing approaches lack causal reasoning capabilities essential for counterfactual analysis and risk assessment. We propose a…

Machine Learning · Computer Science 2026-03-12 Dennis Thumm , Luis Ontaneda Mijares

We investigate two source coding problems with secrecy constraints. In the first problem we consider real--time fully secure transmission of a memoryless source. We show that although classical variable--rate coding is not an option since…

Information Theory · Computer Science 2012-05-16 Yonatan Kaspi , Neri Merhav

Variational Autoencoders (VAEs) are a popular generative model, but one in which conditional inference can be challenging. If the decomposition into query and evidence variables is fixed, conditional VAEs provide an attractive solution. To…

Machine Learning · Statistics 2018-10-05 Ga Wu , Justin Domke , Scott Sanner

This paper investigates an information-theoretic model of secure semantic-aware communication. For this purpose, we consider the lossy joint source-channel coding (JSCC) of a memoryless semantic source transmitted over a memoryless wiretap…

Information Theory · Computer Science 2026-05-26 Denis Kozlov , Mahtab Mirmohseni , Rahim Tafazolli

We consider the reversible processes between two one-to-one correlated measurement outcomes which underly both problem-solving and quantum nonlocality. In the former case the two outcomes are the setting and the solution of the problem, in…

Quantum Physics · Physics 2021-09-08 Giuseppe Castagnoli

The two-user broadcast channel (BC) with receivers connected by bidirectional cooperation links of finite capacities, known as conferencing decoders, is considered. A novel capacity region outer bound is established based on multiple…

Information Theory · Computer Science 2025-08-12 Reza K. Farsani , Wei Yu

Graphical perception studies typically measure visualization encoding effectiveness using the error of an "average observer", leading to canonical rankings of encodings for numerical attributes: e.g., position > area > angle > volume. Yet…

Human-Computer Interaction · Computer Science 2022-12-22 Russell Davis , Xiaoying Pu , Yiren Ding , Brian D. Hall , Karen Bonilla , Mi Feng , Matthew Kay , Lane Harrison

Encodings or the proof of their absence are the main way to compare process calculi. To analyse the quality of encodings and to rule out trivial or meaningless encodings, they are augmented with quality criteria. There exists a bunch of…

Logic in Computer Science · Computer Science 2015-08-28 Kirstin Peters , Rob van Glabbeek

Hardy's argument constitutes an elegant proof of quantum nonlocality. In this work, we report an exotic application of Hardy's nonlocal correlations in two-party communication setup. We come up with a task, wherein a positive payoff can be…

Unobserved confounding is one of the main challenges when estimating causal effects. We propose a causal reduction method that, given a causal model, replaces an arbitrary number of possibly high-dimensional latent confounders with a single…

Machine Learning · Statistics 2023-02-24 Maximilian Ilse , Patrick Forré , Max Welling , Joris M. Mooij

Entanglement-assisted communication over a random-parameter quantum channel with either causal or non-causal channel side information (CSI) at the encoder is considered. This describes a scenario where the quantum channel depends on the…

Information Theory · Computer Science 2019-12-11 Uzi Pereg

This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only…

Information Theory · Computer Science 2013-07-22 Xi Liu , Osvaldo Simeone , Elza Erkip

We study a lossy source coding problem for a memoryless remote source. The source data is broadcast over an arbitrarily varying channel (AVC) controlled by an adversary. One output of the AVC is received as input at the encoder, and another…

Information Theory · Computer Science 2017-04-26 Amitalok J. Budkuley , Bikash Kumar Dey , Vinod M. Prabhakaran

Disentangled representation learning aims to learn low-dimensional representations where each dimension corresponds to an underlying generative factor. While the Variational Auto-Encoder (VAE) is widely used for this purpose, most existing…

Machine Learning · Computer Science 2024-12-31 Di Fan , Yannian Kou , Chuanhou Gao