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There is a growing interest in the transition from 4-step random access to 2-step random access in machine-type communication (MTC), since 2-step random access is well-suited to short message delivery in various Internet of Things (IoT)…

Information Theory · Computer Science 2021-01-01 Jinho Choi

Multi-head self-attention (MHSA) is a key component of Transformers, a widely popular architecture in both language and vision. Multiple heads intuitively enable different parallel processes over the same input. Yet, they also obscure the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Pooyan Rahmanzadehgervi , Hung Huy Nguyen , Rosanne Liu , Long Mai , Anh Totti Nguyen

Future wireless access networks need to support diversified quality of service (QoS) metrics required by various types of Internet-of-Things (IoT) devices, e.g., age of information (AoI) for status generating sources and ultra low latency…

Information Theory · Computer Science 2019-03-07 Zhiyuan Jiang , Sheng Zhou , Zhisheng Niu

Combining the Information Bottleneck model with deep learning by replacing mutual information terms with deep neural nets has proved successful in areas ranging from generative modelling to interpreting deep neural networks. In this paper,…

Machine Learning · Computer Science 2020-02-19 Aleksander Wieczorek , Volker Roth

This work considers a layered coding approach for efficient transmission of data over a wireless block fading channel without transmitter channel state information (CSI), which is connected to a limited capacity reliable link, known as the…

Information Theory · Computer Science 2020-05-01 Avi Steiner , Shlomo Shamai

Leveraging high-quality joint representations from multimodal data can greatly enhance model performance in various machine-learning based applications. Recent multimodal learning methods, based on the multimodal information bottleneck…

Machine Learning · Computer Science 2025-05-27 Qilong Wu , Yiyang Shao , Jun Wang , Xiaobo Sun

Concept Bottleneck Models (CBMs) aim to enhance interpretability by structuring predictions around human-understandable concepts. However, unintended information leakage, where predictive signals bypass the concept bottleneck, compromises…

Machine Learning · Computer Science 2025-07-22 Mikael Makonnen , Moritz Vandenhirtz , Sonia Laguna , Julia E Vogt

The Information Bottleneck (IB) framework is a general characterization of optimal representations obtained using a principled approach for balancing accuracy and complexity. Here we present a new framework, the Dual Information Bottleneck…

Information Theory · Computer Science 2020-06-09 Zoe Piran , Ravid Shwartz-Ziv , Naftali Tishby

Information Bottlenecks (IBs) learn representations that generalize to unseen data by information compression. However, existing IBs are practically unable to guarantee generalization in real-world scenarios due to the vacuous…

Machine Learning · Computer Science 2023-05-01 Yilin Lyu , Xin Liu , Mingyang Song , Xinyue Wang , Yaxin Peng , Tieyong Zeng , Liping Jing

Token communications (TokCom) is an emerging generative semantic communication concept that reduces transmission rates by using context and multimodal large language model (MLLM)-based token processing, with tokens serving as universal…

Information Theory · Computer Science 2025-09-11 Li Qiao , Mahdi Boloursaz Mashhadi , Zhen Gao , Robert Schober , Deniz Gündüz

Sparse code multiple access (SCMA) has been one of non-orthogonal multiple access (NOMA) schemes aiming to support high spectral efficiency and ubiquitous access requirements for 5G wireless communication networks. Conventional SCMA…

Signal Processing · Electrical Eng. & Systems 2019-06-20 Jinzhi Lin , Shengzhong Feng , Zhile Yang , Yun Zhang , Yong Zhang

This letter proposes UniToCom, a unified token communication paradigm that treats tokens as the fundamental units for both processing and wireless transmission. Specifically, to enable efficient token representations, we propose a…

Signal Processing · Electrical Eng. & Systems 2025-07-03 Hao Wei , Wanli Ni , Wen Wang , Wenjun Xu , Dusit Niyato , Ping Zhang

In supervised learning, understanding an input's proximity to the training data can help a model decide whether it has sufficient evidence for reaching a reliable prediction. While powerful probabilistic models such as Gaussian Processes…

Machine Learning · Computer Science 2024-06-19 Ifigeneia Apostolopoulou , Benjamin Eysenbach , Frank Nielsen , Artur Dubrawski

Next-generation internet of things (IoT) applications need trillions of low-powered wireless mobile devices to connect with each other having ultra-reliability and low-latency. Non-orthogonal multiple access (NOMA) is a promising technology…

Signal Processing · Electrical Eng. & Systems 2020-12-16 Kuntal Deka , Sanjeev Sharma

One objective of the 5G communication system and beyond is to support massive machine type of communication (mMTC) to propel the fast growth of diverse Internet of Things use cases. The mMTC aims to provide connectivity to tens of billions…

Signal Processing · Electrical Eng. & Systems 2021-11-03 Mehmood Alam , Qi Zhang

Information bottleneck (IB) is a method for extracting information from one random variable $X$ that is relevant for predicting another random variable $Y$. To do so, IB identifies an intermediate "bottleneck" variable $T$ that has low…

Machine Learning · Statistics 2022-11-22 Artemy Kolchinsky , Brendan D. Tracey , Steven Van Kuyk

Collaborative perception systems leverage multiple edge devices, such surveillance cameras or autonomous cars, to enhance sensing quality and eliminate blind spots. Despite their advantages, challenges such as limited channel capacity and…

Networking and Internet Architecture · Computer Science 2025-01-07 Zhengru Fang , Senkang Hu , Jingjing Wang , Yiqin Deng , Xianhao Chen , Yuguang Fang

The rapid development of Internet of Things (IoT) technologies has not only enabled new applications, but also presented new challenges for reliable communication with limited resources. In this work, we define a novel problem that can…

Networking and Internet Architecture · Computer Science 2025-09-30 Shaan ul Haque , Siddharth Chandak , Federico Chiariotti , Deniz Gunduz , Petar Popovski

The Information Bottleneck (IB) is a method of lossy compression of relevant information. Its rate-distortion (RD) curve describes the fundamental tradeoff between input compression and the preservation of relevant information embedded in…

Information Theory · Computer Science 2023-07-27 Shlomi Agmon

We view the Information Bottleneck Principle (IBP: Tishby et al., 1999; Schwartz-Ziv and Tishby, 2017) and Predictive Information Bottleneck Principle (PIBP: Still et al., 2007; Alemi, 2019) as special cases of a family of general…

Machine Learning · Computer Science 2019-12-24 Sayandev Mukherjee