On the AWGN channel with noisy feedback and peak energy constraint. - Yu Xiang 004; Young-Han Kim 001 (ISIT, 2010)

Information flooding. - Yu Xiang 004; Lele Wang 001; Young-Han Kim 001 (Allerton, 2011)

Interactive hypothesis testing with communication constraints. - Yu Xiang 004; Young-Han Kim 001 (Allerton Conference, 2012)

Interactive hypothesis testing against independence. - Yu Xiang 004; Young-Han Kim 001 (ISIT, 2013)

Gaussian Channel With Noisy Feedback and Peak Energy Constraint. - Yu Xiang 004; Young-Han Kim 001 (IEEE Trans. Inf. Theory, 2013)

A few meta-theorems in network information theory. - Yu Xiang 004; Young-Han Kim 001 (ITW, 2014)

Detecting structural changes in dependent data. - Jie Ding 002; Yu Xiang 004; Lu Shen; Vahid Tarokh (GlobalSIP, 2017)

Pseudo-wigner matrices from dual BCH codes. - Ilya Soloveychik; Yu Xiang 004; Vahid Tarokh (ISIT, 2017)

Explicit symmetric pseudo-random matrices. - Ilya Soloveychik; Yu Xiang 004; Vahid Tarokh (ITW, 2017)

Multiple Change Point Analysis: Fast Implementation and Strong Consistency. - Jie Ding 002; Yu Xiang 004; Lu Shen; Vahid Tarokh (IEEE Trans. Signal Process., 2017)

Evolutionary Spectra Based on the Multitaper Method with Application To Stationarity Test. - Yu Xiang 004; Jie Ding 002; Vahid Tarokh (ICASSP, 2018)

Pseudo-Wigner Matrices. - Ilya Soloveychik; Yu Xiang 004; Vahid Tarokh (IEEE Trans. Inf. Theory, 2018)

Symmetric Pseudo-Random Matrices. - Ilya Soloveychik; Yu Xiang 004; Vahid Tarokh (IEEE Trans. Inf. Theory, 2018)

Distributed False Discovery Rate Control with Quantization. - Yu Xiang 004 (ISIT, 2019)

Estimation of the Evolutionary Spectra With Application to Stationarity Test. - Yu Xiang 004; Jie Ding 002; Vahid Tarokh (IEEE Trans. Signal Process., 2019)

On the Robustness of Causal Discovery with Additive Noise Models on Discrete Data. - Kang Du; Austin Goddard; Yu Xiang 004 (DCC, 2020)

Information Laundering for Model Privacy. - Xinran Wang; Yu Xiang 004; Jun Gao; Jie Ding 002 (ICLR, 2021)

Causal Inference Using Linear Time-Varying Filters with Additive Noise. - Kang Du; Yu Xiang 004 (ISIT, 2021)

Differentially Private Variable Selection via the Knockoff Filter. - Mehrdad Pournaderi; Yu Xiang 004 (MLSP, 2021)

A Subsampling-Based Method for Causal Discovery on Discrete Data. - Austin Goddard; Yu Xiang 004 (SSP, 2021)

An Invariant Matching Property for Distribution Generalization under Intervened Response. - Kang Du; Yu Xiang 004 (EUSIPCO, 2022)

Communication-Efficient Distributed Multiple Testing for Large-Scale Inference. - Mehrdad Pournaderi; Yu Xiang 004 (ISIT, 2022)

Lower Bounds on the Error Probability for Invariant Causal Prediction. - Austin Goddard; Yu Xiang 004; Ilya Soloveychik (MLSP, 2022)

Identifying Direct Causes Using Intervened Target Variable. - Kang Du; Yu Xiang 004; Ilya Soloveychik (ACSSC, 2023)

Error Probability Bounds for Invariant Causal Prediction via Multiple Access Channels. - Austin Goddard; Yu Xiang 004; Ilya Soloveychik (ACSSC, 2023)

Communication-Efficient Distribution-Free Inference Over Networks. - Mehrdad Pournaderi; Yu Xiang 004 (ACSSC, 2023)

Generalized Invariant Matching Property Via Lasso. - Kang Du; Yu Xiang 004 (ICASSP, 2023)

Sample-and-Forward: Communication-Efficient Control of the False Discovery Rate in Networks. - Mehrdad Pournaderi; Yu Xiang 004 (ISIT, 2023)

Learning Invariant Representations Under General Interventions on the Response. - Kang Du; Yu Xiang 004 (IEEE J. Sel. Areas Inf. Theory, 2023)

On Large-Scale Multiple Testing Over Networks: An Asymptotic Approach. - Mehrdad Pournaderi; Yu Xiang 004 (IEEE Trans. Signal Inf. Process. over Networks, 2023)

Low-Rank Approximation of Structural Redundancy for Self-Supervised Learning. - Kang Du; Yu Xiang 004 (CLeaR, 2024)

Mining Invariance from Nonlinear Multi-Environment Data: Binary Classification. - Austin Goddard; Kang Du; Yu Xiang 004 (ISIT, 2024)

Training-Conditional Coverage Bounds for Uniformly Stable Learning Algorithms. - Mehrdad Pournaderi; Yu Xiang 004 (CoRR, 2024)

Training-Conditional Coverage Bounds under Covariate Shift. - Mehrdad Pournaderi; Yu Xiang 004 (CoRR, 2024)

Causal Inference From Slowly Varying Nonstationary Processes. - Kang Du; Yu Xiang 004 (IEEE Trans. Signal Inf. Process. over Networks, 2024)