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A general graph-structured neural network architecture operates on graphs through two core components: (1) complex enough message functions; (2) a fixed information aggregation process. In this paper, we present the Policy Message Passing…

Machine Learning · Computer Science 2019-10-01 Zhiwei Deng , Greg Mori

In this manuscript a factor graph approach is employed to investigate the recursive filtering problem for a mixed linear/nonlinear state-space model, i.e. for a model whose state vector can be partitioned in a linear state variable…

Statistics Theory · Mathematics 2016-07-29 Giorgio M. Vitetta , Emilio Sirignano , Francesco Montorsi , Matteo Sola

Edge machine learning can deliver low-latency and private artificial intelligent (AI) services for mobile devices by leveraging computation and storage resources at the network edge. This paper presents an energy-efficient edge processing…

Information Theory · Computer Science 2020-03-03 Kai Yang , Yuanming Shi , Wei Yu , Zhi Ding

We present a dynamic resource allocation strategy for energy-efficient and Electromagnetic Field (EMF) exposure aware computation offloading at the wireless network edge. The goal is to maximize the overall system sum-rate of offloaded…

Signal Processing · Electrical Eng. & Systems 2022-04-28 Mattia Merluzzi , Serge Bories , Emilio Calvanese Strinati

Automated Feature Engineering (AFE) refers to automatically generate and select optimal feature sets for downstream tasks, which has achieved great success in real-world applications. Current AFE methods mainly focus on improving the…

Machine Learning · Computer Science 2022-12-27 Kafeng Wang , Pengyang Wang , Chengzhong xu

The Free Energy Principle (FEP) states that under suitable conditions of weak coupling, random dynamical systems with sufficient degrees of freedom will behave so as to minimize an upper bound, formalized as a variational free energy, on…

Quantum Physics · Physics 2022-07-21 Chris Fields , Karl Friston , James F. Glazebrook , Michael Levin

The challenge of solving data mining problems in e-commerce applications such as recommendation system (RS) and click-through rate (CTR) prediction is how to make inferences by constructing combinatorial features from a large number of…

Machine Learning · Computer Science 2021-10-20 Zhenyuan Zhong , Jie Yang , Yacong Ma , Shoubin Dong , Jinlong Hu

Modern large-scale machine learning applications require stochastic optimization algorithms to be implemented on distributed compute systems. A key bottleneck of such systems is the communication overhead for exchanging information across…

Machine Learning · Computer Science 2021-03-16 Samuel Horváth , Peter Richtárik

The Peng-Robinson equation of state (PR-EoS) has become one of the most extensively applied equations of state in chemical engineering and petroleum industry due to its excellent accuracy in predicting the thermodynamic properties of a wide…

Numerical Analysis · Mathematics 2019-03-22 Jisheng Kou , Shuyu Sun , Xiuhua Wang

Expectation Propagation (EP) is a widely used iterative message-passing algorithm that decomposes a global inference problem into multiple local ones. It approximates marginal distributions as ``beliefs'' using intermediate functions called…

Machine Learning · Statistics 2026-04-07 Zilu Zhao , Jichao Chen , Dirk Slock

Active inference is a state-of-the-art framework in neuroscience that offers a unified theory of brain function. It is also proposed as a framework for planning in AI. Unfortunately, the complex mathematics required to create new models --…

Machine Learning · Computer Science 2021-05-11 Théophile Champion , Marek Grześ , Howard Bowman

Free energy perturbation (FEP) was proposed by Zwanzig more than six decades ago as a method to estimate free energy differences, and has since inspired a huge body of related methods that use it as an integral building block. Being an…

The dramatic increase of network infrastructure comes at the cost of rapidly increasing energy consumption, which makes optimization of energy efficiency (EE) an important topic. Since EE is often modeled as the ratio of rate to power, we…

Information Theory · Computer Science 2015-03-19 Christian Isheden , Zhijiat Chong , Eduard Jorswieck , Gerhard Fettweis

Currently, the world experiences an unprecedentedly increasing generation of application data, from sensor measurements to video streams, thanks to the extreme connectivity capability provided by 5G networks. Going beyond 5G technology,…

Signal Processing · Electrical Eng. & Systems 2022-04-21 Mattia Merluzzi , Miltiadis C. Filippou , Leonardo Gomes Baltar , Emilio Calvanese Strinati

Based on prior work by Eckford, it is shown how expectation maximization (EM) may be viewed, and used, as a message passing algorithm in factor graphs.

Information Theory · Computer Science 2016-11-17 J. Dauwels , S. Korl , H. -A. Loeliger

In this paper, we propose a novel Adaptive Transmission Strategy to improve energy efficiency~(EE) in a wireless point-to-point transmission system with Quality of Service~(QoS) requirement, i.e., delay-outage probability considered. The…

Information Theory · Computer Science 2018-07-24 Linlin Zou , Yanzhao Hou , Xiaofeng Tao , Qimei Cui , Xueqing Huang

We present a message-passing algorithm to solve the edge disjoint path problem (EDP) on graphs incorporating under a unique framework both traffic optimization and path length minimization. The min-sum equations for this problem present an…

Disordered Systems and Neural Networks · Physics 2016-01-21 Fabrizio Altarelli , Alfredo Braunstein , Luca Dall'Asta , Caterina De Bacco , Silvio Franz

This paper investigates the design and analysis of minimum mean square error (MMSE) turbo decision feedback equalization (DFE), with expectation propagation (EP), for single carrier modulations. Classical non iterative DFE structures have…

Signal Processing · Electrical Eng. & Systems 2018-07-03 Serdar Şahin , Antonio M. Cipriano , Charly Poulliat , Marie-Laure Boucheret

Recently, different communities in computer science, telecommunication and control systems have devoted a huge effort towards the design of energy efficient solutions for data transmission and network management. This paper collocates along…

Networking and Internet Architecture · Computer Science 2015-03-11 Angelo Cenedese , Marco Michielan , Federico Tramarin , Stefano Vitturi

Understanding how individual agents make strategic decisions within collectives is important for advancing fields as diverse as economics, neuroscience, and multi-agent systems. Two complementary approaches can be integrated to this end.…

Multiagent Systems · Computer Science 2025-05-21 Jaime Ruiz-Serra , Patrick Sweeney , Michael S. Harré