Yu Xiang

51 papers A* 1B 11Misc 5Journal 26Unranked 8
YearRankTypeTitle / Venue / Authors
2024 J jnl
Causal Inference From Slowly Varying Nonstationary Processes.
IEEE Trans. Signal Inf. Process. over Networks
Kang Du, Yu Xiang
2024 — conf
Low-Rank Approximation of Structural Redundancy for Self-Supervised Learning.
CLeaR
Kang Du, Yu Xiang
2024 J jnl
Low-Rank Approximation of Structural Redundancy for Self-Supervised Learning.
CoRR
Kang Du, Yu Xiang
2024 B conf
Mining Invariance from Nonlinear Multi-Environment Data: Binary Classification.
ISIT
Austin Goddard, Kang Du, Yu Xiang
2024 J jnl
Mining Invariance from Nonlinear Multi-Environment Data: Binary Classification.
CoRR
Austin Goddard, Kang Du, Yu Xiang
2024 J jnl
Training-Conditional Coverage Bounds for Uniformly Stable Learning Algorithms.
CoRR
Mehrdad Pournaderi, Yu Xiang
2024 J jnl
Training-Conditional Coverage Bounds under Covariate Shift.
CoRR
Mehrdad Pournaderi, Yu Xiang
2023 Misc conf
Communication-Efficient Distribution-Free Inference Over Networks.
ACSSC
Mehrdad Pournaderi, Yu Xiang
2023 J jnl
Communication-Efficient Distribution-Free Inference Over Networks.
CoRR
Mehrdad Pournaderi, Yu Xiang
2023 Misc conf
Error Probability Bounds for Invariant Causal Prediction via Multiple Access Channels.
ACSSC
Austin Goddard, Yu Xiang, Ilya Soloveychik
2023 J jnl
Error Probability Bounds for Invariant Causal Prediction via Multiple Access Channels.
CoRR
Austin Goddard, Yu Xiang, Ilya Soloveychik
2023 Misc conf
Generalized Invariant Matching Property Via Lasso.
ICASSP
Kang Du, Yu Xiang
2023 J jnl
Generalized Invariant Matching Property via LASSO.
CoRR
Kang Du, Yu Xiang
2023 Misc conf
Identifying Direct Causes Using Intervened Target Variable.
ACSSC
Kang Du, Yu Xiang, Ilya Soloveychik
2023 J jnl
Learning Invariant Representations Under General Interventions on the Response.
IEEE J. Sel. Areas Inf. Theory
Kang Du, Yu Xiang
2023 J jnl
On Large-Scale Multiple Testing Over Networks: An Asymptotic Approach.
IEEE Trans. Signal Inf. Process. over Networks
Mehrdad Pournaderi, Yu Xiang
2023 B conf
Sample-and-Forward: Communication-Efficient Control of the False Discovery Rate in Networks.
ISIT
Mehrdad Pournaderi, Yu Xiang
2022 — conf
An Invariant Matching Property for Distribution Generalization under Intervened Response.
EUSIPCO
Kang Du, Yu Xiang
2022 J jnl
An Invariant Matching Property for Distribution Generalization under Intervened Response.
CoRR
Kang Du, Yu Xiang
2022 B conf
Communication-Efficient Distributed Multiple Testing for Large-Scale Inference.
ISIT
Mehrdad Pournaderi, Yu Xiang
2022 J jnl
Communication-Efficient Distributed Multiple Testing for Large-Scale Inference.
CoRR
Mehrdad Pournaderi, Yu Xiang
2022 J jnl
Learning Invariant Representations under General Interventions on the Response.
CoRR
Kang Du, Yu Xiang
2022 — conf
Lower Bounds on the Error Probability for Invariant Causal Prediction.
MLSP
Austin Goddard, Yu Xiang, Ilya Soloveychik
2022 J jnl
Lower Bounds on the Error Probability for Invariant Causal Prediction.
CoRR
Austin Goddard, Yu Xiang, Ilya Soloveychik
2022 J jnl
On Large-Scale Multiple Testing Over Networks: An Asymptotic Approach.
CoRR
Mehrdad Pournaderi, Yu Xiang
2021 — conf
A Subsampling-Based Method for Causal Discovery on Discrete Data.
SSP
Austin Goddard, Yu Xiang
2021 J jnl
A Subsampling-Based Method for Causal Discovery on Discrete Data.
CoRR
Austin Goddard, Yu Xiang
2021 B conf
Causal Inference Using Linear Time-Varying Filters with Additive Noise.
ISIT
Kang Du, Yu Xiang
2021 — conf
Differentially Private Variable Selection via the Knockoff Filter.
MLSP
Mehrdad Pournaderi, Yu Xiang
2021 J jnl
Differentially Private Variable Selection via the Knockoff Filter.
CoRR
Mehrdad Pournaderi, Yu Xiang
2021 A* conf
Information Laundering for Model Privacy.
ICLR
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
2020 J jnl
Causal Inference Using Linear Time-Varying Filters with Additive Noise.
CoRR
Kang Du, Yu Xiang
2020 J jnl
Information Laundering for Model Privacy.
CoRR
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
2020 B conf
On the Robustness of Causal Discovery with Additive Noise Models on Discrete Data.
DCC
Kang Du, Austin Goddard, Yu Xiang
2019 B conf
Distributed False Discovery Rate Control with Quantization.
ISIT
Yu Xiang
2019 J jnl
Estimation of the Evolutionary Spectra With Application to Stationarity Test.
IEEE Trans. Signal Process.
Yu Xiang, Jie Ding, Vahid Tarokh
2018 Misc conf
Evolutionary Spectra Based on the Multitaper Method with Application To Stationarity Test.
ICASSP
Yu Xiang, Jie Ding, Vahid Tarokh
2018 J jnl
Pseudo-Wigner Matrices.
IEEE Trans. Inf. Theory
Ilya Soloveychik, Yu Xiang, Vahid Tarokh
2018 J jnl
Symmetric Pseudo-Random Matrices.
IEEE Trans. Inf. Theory
Ilya Soloveychik, Yu Xiang, Vahid Tarokh
2017 — conf
Detecting structural changes in dependent data.
GlobalSIP
Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh
2017 B conf
Explicit symmetric pseudo-random matrices.
ITW
Ilya Soloveychik, Yu Xiang, Vahid Tarokh
2017 J jnl
Multiple Change Point Analysis: Fast Implementation and Strong Consistency.
IEEE Trans. Signal Process.
Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh
2017 J jnl
Pseudo-Wigner Matrices from Dual BCH Codes.
CoRR
Ilya Soloveychik, Yu Xiang, Vahid Tarokh
2017 B conf
Pseudo-wigner matrices from dual BCH codes.
ISIT
Ilya Soloveychik, Yu Xiang, Vahid Tarokh
2014 B conf
A few meta-theorems in network information theory.
ITW
Yu Xiang, Young-Han Kim
2013 J jnl
Gaussian Channel With Noisy Feedback and Peak Energy Constraint.
IEEE Trans. Inf. Theory
Yu Xiang, Young-Han Kim
2013 B conf
Interactive hypothesis testing against independence.
ISIT
Yu Xiang, Young-Han Kim
2012 — conf
Interactive hypothesis testing with communication constraints.
Allerton Conference
Yu Xiang, Young-Han Kim
2011 J jnl
Gaussian Channel with Noisy Feedback and Peak Energy Constraint
CoRR
Yu Xiang, Young-Han Kim
2011 — conf
Information flooding.
Allerton
Yu Xiang, Lele Wang, Young-Han Kim
2010 B conf
On the AWGN channel with noisy feedback and peak energy constraint.
ISIT
Yu Xiang, Young-Han Kim