Stabilization of linear dynamical systems with scalar quantizers under communication constraints. - Jingge Zhu; Slawomir Stanczak; Gunther Reißig (CISS, 2010)

Cooperative Secret Communication with Artificial Noise in Symmetric Interference Channel. - Jingge Zhu; Jianhua Mo 001; Meixia Tao (IEEE Commun. Lett., 2010)

Lattice codes for many-to-one cognitive interference networks. - Jingge Zhu; Michael Gastpar (ISIT, 2013)

Gaussian (dirty) multiple access channels: A compute-and-forward perspective. - Jingge Zhu; Michael Gastpar (ISIT, 2014)

Asymmetric Compute-and-Forward with CSIT. - Jingge Zhu; Michael Gastpar (CoRR, 2014)

Multiple Access via Compute-and-Forward. - Jingge Zhu; Michael Gastpar (CoRR, 2014)

On lattice codes for Gaussian interference channels. - Jingge Zhu; Michael Gastpar (ISIT, 2015)

Compute-and-forward using nested linear codes for the Gaussian MAC. - Jingge Zhu; Michael Gastpar (ITW, 2015)

Lattice Codes for Many-to-One Interference Channels With and Without Cognitive Messages. - Jingge Zhu; Michael Gastpar (IEEE Trans. Inf. Theory, 2015)

Typical sumsets of lattice points. - Jingge Zhu; Michael Gastpar (ACSSC, 2016)

Typical sumsets of linear codes. - Jingge Zhu; Michael Gastpar (Allerton, 2016)

CFMA (Compute-Forward Multiple Access) and its Applications in Network Information Theory. - Jingge Zhu (2016)

A sequential approximation framework for coded distributed optimization. - Jingge Zhu; Ye Pu; Vipul Gupta; Claire J. Tomlin; Kannan Ramchandran (Allerton, 2017)

Compute-forward multiple access (CFMA) with nested LDPC codes. - Erixhen Sula; Jingge Zhu; Adriano Pastore; Sung Hoon Lim; Michael Gastpar (ISIT, 2017)

On the duality between multiple-access codes and computation codes. - Jingge Zhu; Sung Hoon Lim; Michael Gastpar (ITA, 2017)

Compute-Forward Multiple Access (CFMA): Practical Code Design. - Erixhen Sula; Jingge Zhu; Adriano Pastore; Sung Hoon Lim; Michael Gastpar (CoRR, 2017)

Gaussian Multiple Access via Compute-and-Forward. - Jingge Zhu; Michael Gastpar (IEEE Trans. Inf. Theory, 2017)

Coded Control over Lossy Networks. - Ye Pu; Jingge Zhu; Karl Henrik Johansson; Kannan Ramchandran; Claire J. Tomlin (ACC, 2018)

Customized Local Differential Privacy for Multi-Agent Distributed Optimization. - Roel Dobbe; Ye Pu; Jingge Zhu; Kannan Ramchandran; Claire J. Tomlin (CoRR, 2018)

Analysis of Nakamoto Consensus, Revisited. - Jianyu Niu; Chen Feng 001; Hoang Dau; Yu-Chih Huang; Jingge Zhu (IACR Cryptol. ePrint Arch., 2019)

Compute-Forward Multiple Access (CFMA): Practical Implementations. - Erixhen Sula; Jingge Zhu; Adriano Pastore; Sung Hoon Lim; Michael Gastpar (IEEE Trans. Commun., 2019)

Communication Versus Computation: Duality for Multiple-Access Channels and Source Coding. - Jingge Zhu; Sung Hoon Lim; Michael Gastpar (IEEE Trans. Inf. Theory, 2019)

Local Differential Privacy for Multi-Agent Distributed Optimal Power Flow. - Roel Dobbe; Ye Pu; Jingge Zhu; Kannan Ramchandran; Claire J. Tomlin (ISGT-Europe, 2020)

Information-theoretic analysis for transfer learning. - Xuetong Wu; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (ISIT, 2020)

Semi-Supervised Learning: the Case When Unlabeled Data is Equally Useful. - Jingge Zhu (UAI, 2020)

Short Blocklength Distribution Matching by Linear Programming. - Shuangyu Dong; Honglin Ji; Zhaopeng Xu; Jingge Zhu; William Shieh (ECOC, 2021)

Is Phase Shift Keying Optimal for Channels with Phase-Quantized Output? - Neil Irwin Bernardo; Jingge Zhu; Jamie S. Evans (ISIT, 2021)

Online Transfer Learning: Negative Transfer and Effect of Prior Knowledge. - Xuetong Wu; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (ISIT, 2021)

On Minimizing Symbol Error Rate Over Fading Channels With Low-Resolution Quantization. - Neil Irwin Bernardo; Jingge Zhu; Jamie S. Evans (IEEE Trans. Commun., 2021)

A Linear Physical-Layer Network Coding Based Multiple Access Approach. - Qiuzhuo Chen; Fangtao Yu; Tao Yang 004; Jingge Zhu; Rongke Liu (ISIT, 2022)

A Learning-Based Approach to Approximate Coded Computation. - Navneet Agrawal; Yuqin Qiu; Matthias Frey; Igor Bjelakovic; Setareh Maghsudi; Slawomir Stanczak; Jingge Zhu (ITW, 2022)

Fast Rate Generalization Error Bounds: Variations on a Theme. - Xuetong Wu; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (ITW, 2022)

On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis. - Xuetong Wu; Mingming Gong; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (CoRR, 2022)

Ancestral Colorings of Perfect Binary Trees With Applications in Private Retrieval of Merkle Proofs. - Quang Cao; Rinaldo Gagiano; Duy Huynh; Xun Yi; Son Hoang Dau; Phuc Lu Le; Quang-Hung Luu; Emanuele Viterbo; Yu-Chih Huang; Jingge Zhu; Mohammad M. Jalalzai; Chen Feng 001 (CoRR, 2022)

An Information-Theoretic Analysis for Transfer Learning: Error Bounds and Applications. - Xuetong Wu; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (CoRR, 2022)

On the Capacity-Achieving Input of the Gaussian Channel With Polar Quantization. - Neil Irwin Bernardo; Jingge Zhu; Jamie S. Evans (IEEE Trans. Commun., 2022)

Capacity Bounds for One-Bit MIMO Gaussian Channels With Analog Combining. - Neil Irwin Bernardo; Jingge Zhu; Yonina C. Eldar; Jamie S. Evans (IEEE Trans. Commun., 2022)

On the Capacity-Achieving Input of Channels With Phase Quantization. - Neil Irwin Bernardo; Jingge Zhu; Jamie S. Evans (IEEE Trans. Inf. Theory, 2022)

Stability Bounds for Learning-Based Adaptive Control of Discrete-Time Multi-Dimensional Stochastic Linear Systems with Input Constraints. - Seth Siriya; Jingge Zhu; Dragan Nesic; Ye Pu (CDC, 2023)

Committed Private Information Retrieval. - Quang Cao; Hong-Yen Tran; Son Hoang Dau; Xun Yi; Emanuele Viterbo; Chen Feng 001; Yu-Chih Huang; Jingge Zhu; Stanislav Kruglik; Han Mao Kiah (ESORICS (1), 2023)

Accelerating Graph Neural Networks via Edge Pruning for Power Allocation in Wireless Networks. - Lili Chen; Jingge Zhu; Jamie S. Evans (GLOBECOM (Workshops), 2023)

Hardware-Limited Non-Uniform Task-Based Quantizers. - Neil Irwin Bernardo; Jingge Zhu; Yonina C. Eldar; Jamie S. Evans (ICASSP, 2023)

On the Value of Stochastic Side Information in Online Learning. - Junzhang Jia; Xuetong Wu; Jamie S. Evans; Jingge Zhu (ICASSP, 2023)

Graph Neural Networks for Power Allocation in Wireless Networks with Full Duplex Nodes. - Lili Chen; Jingge Zhu; Jamie S. Evans (ICC Workshops, 2023)

Learning Channel Codes from Data: Performance Guarantees in the Finite Blocklength Regime. - Neil Irwin Bernardo; Jingge Zhu; Jamie S. Evans (ISIT, 2023)

CFMA for Gaussian MIMO Multiple Access Channels. - Lanwei Zhang; Jamie S. Evans; Jingge Zhu (ISIT, 2023)

Coded Distributed Image Classification. - Jiepeng Tang; Navneet Agrawal; Slawomir Stanczak; Jingge Zhu (MLSP, 2023)

On the tightness of information-theoretic bounds on generalization error of learning algorithms. - Xuetong Wu; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (CoRR, 2023)

Learning-Based Adaptive Control for Stochastic Linear Systems With Input Constraints. - Seth Siriya; Jingge Zhu; Dragan Nesic; Ye Pu (IEEE Control. Syst. Lett., 2023)

Design and Analysis of Hardware-Limited Non-Uniform Task-Based Quantizers. - Neil Irwin Bernardo; Jingge Zhu; Yonina C. Eldar; Jamie S. Evans (IEEE Trans. Signal Process., 2023)

A Bayesian approach to (online) transfer learning: Theory and algorithms. - Xuetong Wu; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (Artif. Intell., 2023)

GNN-Based Joint Channel and Power Allocation in Heterogeneous Wireless Networks. - Lili Chen; Jingge Zhu; Jamie S. Evans (ICC Workshops, 2024)

Compute-Forward Multiple Access for Gaussian MIMO Channels. - Lanwei Zhang; Jamie S. Evans; Jingge Zhu (CoRR, 2024)

Power Allocation for Compute-and-Forward over Fading Channels. - Lanwei Zhang; Jamie S. Evans; Jingge Zhu (CoRR, 2024)

Non-Asymptotic Bounds for Closed-Loop Identification of Unstable Nonlinear Stochastic Systems. - Seth Siriya; Jingge Zhu; Dragan Nesic; Ye Pu (CoRR, 2024)

On the Generalization for Transfer Learning: An Information-Theoretic Analysis. - Xuetong Wu; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (IEEE Trans. Inf. Theory, 2024)

TreePIR: Efficient Private Retrieval of Merkle Proofs via Tree Colorings with Fast Indexing and Zero Storage Overhead. - Quang Cao; Son Hoang Dau; Rinaldo Gagiano; Duy Huynh; Xun Yi; Phuc Lu Le; Quang-Hung Luu; Emanuele Viterbo; Yu-Chih Huang; Jingge Zhu; Mohammad M. Jalalzai; Chen Feng 001 (SP, 2025)

Emergence of Computational Structure in a Neural Network Physics Simulator. - Rohan Hitchcock; Gary W. Delaney; Jonathan H. Manton; Richard Scalzo; Jingge Zhu (CoRR, 2025)

Semi-Supervised Learning Under General Causal Models. - Archer Moore; Heejung Shim; Jingge Zhu; Mingming Gong (IEEE Trans. Neural Networks Learn. Syst., 2025)

Simultaneous Computation and Communication Over MAC. - Matthias Frey; Igor Bjelakovic; Michael C. Gastpar; Jingge Zhu (IEEE Trans. Inf. Theory, 2025)

Graph Neural Networks for Resource Allocation in Multi-Channel Wireless Networks. - Lili Chen; Changyang She; Jingge Zhu; Jamie S. Evans (CoRR, 2025)

Compute-Forward Multiple Access for Gaussian Fast Fading Channels. - Lanwei Zhang; Jamie S. Evans; Jingge Zhu (IEEE Trans. Inf. Theory, 2025)

A DPI-PAC-Bayesian Framework for Generalization Bounds. - Muhan Guan; Farhad Farokhi; Jingge Zhu (CoRR, 2025)

A new multi-wing hyperchaotic system and its application in image encryption. - Pengfei Ding; Weiwei Hu; Penghui Geng; Juan Zhang; Jingge Zhu (J. Supercomput., 2025)

Fast Rate Information-Theoretic Bounds on Generalization Errors. - Xuetong Wu; Jonathan H. Manton; Uwe Aickelin; Jingge Zhu (IEEE Trans. Inf. Theory, 2025)