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This paper considers the information bottleneck (IB) problem of a Rayleigh fading multiple-input multiple-out (MIMO) channel with an oblivious relay. The relay is constrained to operate without knowledge of the codebooks, i.e., it performs…

Information Theory · Computer Science 2021-05-10 Hao Xu , Tianyu Yang , Giuseppe Caire , Shlomo Shamai

This paper considers the distributed information bottleneck (D-IB) problem for a primitive Gaussian diamond channel with two relays and Rayleigh fading. Due to the bottleneck constraint, it is impossible for the relays to inform the…

Information Theory · Computer Science 2022-06-30 Hao Xu , Kai-Kit Wong , Giuseppe Caire , Shlomo Shamai

This paper considers the distributed information bottleneck (D-IB) problem for a primitive Gaussian diamond channel with two relays and MIMO Rayleigh fading. The channel state is an independent and identically distributed (i.i.d.) process…

Information Theory · Computer Science 2023-05-09 Yi Song , Hao Xu , Kai-Kit Wong , Giuseppe Caire , Shlomo Shamai

We consider the problem of reliable communication over a discrete memoryless channel (DMC) with the help of a relay, termed the information bottleneck (IB) channel. There is no direct link between the source and the destination, and the…

Information Theory · Computer Science 2023-05-02 Michael Dikshtein , Nir Weinberger , Shlomo Shamai

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

Information bottleneck (IB) is a technique for extracting information in one random variable $X$ that is relevant for predicting another random variable $Y$. IB works by encoding $X$ in a compressed "bottleneck" random variable $M$ from…

Information Theory · Computer Science 2022-11-22 Artemy Kolchinsky , Brendan D. Tracey , David H. Wolpert

The muti-layer information bottleneck (IB) problem, where information is propagated (or successively refined) from layer to layer, is considered. Based on information forwarded by the preceding layer, each stage of the network is required…

Machine Learning · Statistics 2017-11-15 Qianqian Yang , Pablo Piantanida , Deniz Gündüz

The information bottleneck channel (or the oblivious relay channel) concerns a channel coding setting where the decoder does not directly observe the channel output. Rather, the channel output is relayed to the decoder by an oblivious relay…

Information Theory · Computer Science 2026-04-28 Yanxiao Liu , Sepehr Heidari Advary , Cheuk Ting Li

This paper investigates the limits of information transfer over a fast Rayleigh fading MIMO channel, where neither the transmitter nor the receiver has the knowledge of the channel state information (CSI) except the fading statistics. We…

Information Theory · Computer Science 2007-07-13 Rasika R Perera , Tony S Pollock , Thushara D Abhayapala

Information bottleneck (IB) is a paradigm to extract information in one target random variable from another relevant random variable, which has aroused great interest due to its potential to explain deep neural networks in terms of…

Information Theory · Computer Science 2023-08-23 Lingyi Chen , Shitong Wu , Wenhao Ye , Huihui Wu , Hao Wu , Wenyi Zhang , Bo Bai , Yining Sun

We introduce a bottleneck method for learning data representations based on information deficiency, rather than the more traditional information sufficiency. A variational upper bound allows us to implement this method efficiently. The…

Information Theory · Computer Science 2020-11-05 Pradeep Kr. Banerjee , Guido Montúfar

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

Information Bottleneck (IB) is a generalization of rate-distortion theory that naturally incorporates compression and relevance trade-offs for learning. Though the original IB has been extensively studied, there has not been much…

Machine Learning · Computer Science 2019-10-08 Thanh T. Nguyen , Jaesik Choi

Information bottleneck is an information-theoretic principle of representation learning that aims to learn a maximally compressed representation that preserves as much information about labels as possible. Under this principle, two…

Information Theory · Computer Science 2023-11-08 Yuyan Ni , Yanyan Lan , Ao Liu , Zhiming Ma

Extracting relevant information from data is crucial for all forms of learning. The information bottleneck (IB) method formalizes this, offering a mathematically precise and conceptually appealing framework for understanding learning…

Machine Learning · Computer Science 2021-10-27 Vudtiwat Ngampruetikorn , David J. Schwab

The information bottleneck problem (IB) of jointly stationary Gaussian sources is considered. A water-filling solution for the IB rate is given in terms of its SNR spectrum and whose rate is attained via frequency domain test-channel…

Information Theory · Computer Science 2022-08-23 Michael Dikshtein , Nir Weinberger , Shlomo Shamai

In this paper, we investigate the blind channel estimation problem for MIMO systems under Rayleigh fading channel. Conventional MIMO communication techniques require transmitting a considerable amount of training symbols as pilots in each…

Signal Processing · Electrical Eng. & Systems 2021-11-17 Jiancheng Tang , Qianqian Yang , Zhaoyang Zhang

The information bottleneck principle is an elegant and useful approach to representation learning. In this paper, we investigate the problem of representation learning in the context of reinforcement learning using the information…

Machine Learning · Computer Science 2019-11-14 Pei Yingjun , Hou Xinwen

The Information Bottleneck (IB) principle facilitates effective representation learning by preserving label-relevant information while compressing irrelevant information. However, its strong reliance on accurate labels makes it inherently…

Machine Learning · Computer Science 2025-12-12 Yi Huang , Qingyun Sun , Yisen Gao , Haonan Yuan , Xingcheng Fu , Jianxin Li

Learning effective joint embedding for cross-modal data has always been a focus in the field of multimodal machine learning. We argue that during multimodal fusion, the generated multimodal embedding may be redundant, and the discriminative…

Machine Learning · Computer Science 2022-12-06 Sijie Mai , Ying Zeng , Haifeng Hu
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