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20182026
most citedCompression with Exact Error Distribution for Federated Learning

4 citations · 5 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.IT2025

Coding-Logic Correspondence: Turning Information and Communication Networks into Logical Formulae via Hypergraph Heyting Algebra

Cheuk Ting Li

We propose using confusion hypergraph (hyperconfusion) as a model of information. In contrast to the conventional approach using random variables, we can now perform conjunction, d…

cs.IT2025

New Second-Order Achievability Bounds for Coding with Side Information via Type Deviation Convergence

Xiang Li, Cheuk Ting Li

We propose a framework for second-order achievability, called type deviation convergence, that is generally applicable to settings in network information theory, and is especially…

cs.IT2025

Joint Scheduling and Multiflow Maximization in Wireless Networks

Yanxiao Liu, Shenghao Yang, Cheuk Ting Li

Towards the development of 6G mobile networks, it is promising to integrate a large number of devices from multi-dimensional platforms, and it is crucial to have a solid understand…

cs.IT2025

Rejection-Sampled Linear Codes for Lossy Compression and Channel Simulation

Jianguo Zhao, Cheuk Ting Li

We show that linear codes combined with rejection sampling can yield a capacity-achieving scheme for simulating additive exchangeable noise channels. Specifically, our scheme achie…

cs.IT2025

Discrete Layered Entropy, Conditional Compression and a Tighter Strong Functional Representation Lemma

Cheuk Ting Li

We study a quantity called discrete layered entropy, which approximates the Shannon entropy within a logarithmic gap. Compared to the Shannon entropy, the discrete layered entropy…

cs.IT2025

Nonasymptotic Oblivious Relaying and Variable-Length Noisy Lossy Source Coding

Yanxiao Liu, Sepehr Heidari Advary, Cheuk Ting Li

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 ch…