Xiangxiang Xu

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 48

Top Topics

Transfer Learning

Sample Complexity

Theoretic Framework

Top Venues

Publications

Jongha Jon Ryu, Xiangxiang Xu, H. S. Melihcan Erol, Yuheng Bu, Lizhong Zheng, Gregory W. Wornell
Operator SVD with Neural Networks via Nested Low-Rank Approximation. CoRR (2024)
Xinyi Tong, Xiangxiang Xu, Shao-Lun Huang, Lizhong Zheng
Robust Transfer Learning Based on Minimax Principle. Allerton (2023)
Xiangxiang Xu, Lizhong Zheng
Kernel Subspace and Feature Extraction. CoRR (2023)
Xiangxiang Xu, Lizhong Zheng, Ishank Agrawal
Neural Feature Learning for Engineering Problems. Allerton (2023)
Xiangxiang Xu, Lizhong Zheng
Kernel Subspace and Feature Extraction. ISIT (2023)
Xiangxiang Xu, Lizhong Zheng
Sequential Dependence Decomposition and Feature Learning. Allerton (2023)
Xiangxiang Xu, Lizhong Zheng
A Geometric Framework for Neural Feature Learning. CoRR (2023)
Xinyi Tong, Xiangxiang Xu, Shao-Lun Huang
On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing. Entropy 25 (10) (2023)
Ziyan Zheng, Xinyi Tong, Xinchun Yu, Xiangxiang Xu, Shao-Lun Huang
Multi-source Transfer Learning for Signal Detection over a Fading Channel with Co-channel Interference. ICC (2022)
Xiangxiang Xu, Lizhong Zheng
Multivariate Feature Extraction. Allerton (2022)
Xiangxiang Xu, Shao-Lun Huang
On Distributed Learning With Constant Communication Bits. IEEE J. Sel. Areas Inf. Theory 3 (1) (2022)
Xinlei Chen, Susu Xu, Xinyu Liu, Xiangxiang Xu, Hae Young Noh, Lin Zhang, Pei Zhang
Adaptive Hybrid Model-Enabled Sensing System (HMSS) for Mobile Fine-Grained Air Pollution Estimation. IEEE Trans. Mob. Comput. 21 (6) (2022)
Xinyi Tong, Xiangxiang Xu, Shao-Lun Huang
On Sample Complexity of Learning Shared Representations: The Asymptotic Regime. Allerton (2022)
Xiangxiang Xu, Shao-Lun Huang, Lizhong Zheng, Gregory W. Wornell
An Information Theoretic Interpretation to Deep Neural Networks. Entropy 24 (1) (2022)
Xiangxiang Xu, Shao-Lun Huang
An Information Theoretic Framework for Distributed Learning Algorithms. ISIT (2021)
Mingyang Li, Xiangxiang Xu, Shao-Lun Huang, Lin Zhang
Dual Feature Distributional Regularization for Defending Against Adversarial Attacks. ICONIP (6) (2021)
Fei Ma, Xiangxiang Xu, Shao-Lun Huang, Lin Zhang
Maximum Likelihood Estimation for Multimodal Learning with Missing Modality. CoRR (2021)
Xiangxiang Xu, Shao-Lun Huang
On Distributed Hypothesis Testing with Constant-Bit Communication Constraints. ITW (2021)
Xiangxiang Xu, Shao-Lun Huang
On Distributed Learning with Constant Communication Bits. CoRR (2021)
Xinyi Tong, Xiangxiang Xu, Shao-Lun Huang, Lizhong Zheng
A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning. NeurIPS (2021)
Shao-Lun Huang, Xiangxiang Xu
On the Sample Complexity of HGR Maximal Correlation Functions for Large Datasets. IEEE Trans. Inf. Theory 67 (3) (2021)
Xiangxiang Xu, Shao-Lun Huang
On the Optimal Tradeoff Between Computational Efficiency and Generalizability of Oja's Algorithm. IEEE Access 8 (2020)
Rui Ma, Ning Liu, Xiangxiang Xu, Yue Wang, Hae Young Noh, Pei Zhang, Lin Zhang
Fine-Grained Air Pollution Inference with Mobile Sensing Systems: A Weather-Related Deep Autoencoder Model. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4 (2) (2020)
Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng
An Information-Theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Xiangxiang Xu, Shao-Lun Huang
Maximal Correlation Regression. IEEE Access 8 (2020)
Rui Ma, Ning Liu, Xiangxiang Xu, Yue Wang, Hae Young Noh, Pei Zhang, Lin Zhang
Enhancing the Data Learning With Physical Knowledge in Fine-Grained Air Pollution Inference. IEEE Access 8 (2020)
Xiangxiang Xu, Weida Wang, Shao-Lun Huang
On the Sample Complexity of Estimating Small Singular Modes. ISIT (2020)
Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng, Gregory W. Wornell
A Local Characterization for Wyner Common Information. ISIT (2020)
Lu Li, Yang Li, Xiangxiang Xu, Lin Zhang
A maximal correlation embedding method for multilabel human context recognition: poster abstract. IPSN (2019)
Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng
An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data. CoRR (2019)
Shao-Lun Huang, Xiangxiang Xu
On the Sample Complexity of HGR Maximal Correlation Functions. CoRR (2019)
Lu Li, Yang Li, Xiangxiang Xu, Shao-Lun Huang, Lin Zhang
Maximal Correlation Embedding Network for Multilabel Learning with Missing Labels. ICME (2019)
Shao-Lun Huang, Xiangxiang Xu
On the Robustness of Noisy ACE Algorithm and Multi-Layer Residual Learning. ISIT (2019)
Rui Ma, Ning Liu, Xiangxiang Xu, Yue Wang, Hae Young Noh, Pei Zhang, Lin Zhang
A deep autoencoder model for pollution map recovery with mobile sensing networks. UbiComp/ISWC Adjunct (2019)
Shao-Lun Huang, Xiangxiang Xu
On The Sample Complexity of HGR Maximal Correlation Functions. ITW (2019)
Lichen Wang, Jiaxiang Wu, Shao-Lun Huang, Lizhong Zheng, Xiangxiang Xu, Lin Zhang, Junzhou Huang
An Efficient Approach to Informative Feature Extraction from Multimodal Data. AAAI (2019)
Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng, Gregory W. Wornell
An Information Theoretic Interpretation to Deep Neural Networks. ISIT (2019)
Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng, Gregory W. Wornell
An Information Theoretic Interpretation to Deep Neural Networks. CoRR (2019)
Xiangxiang Xu, Shao-Lun Huang
On the Asymptotic Sample Complexity of HGR Maximal Correlation Functions in Semi-supervised Learning. Allerton (2019)
Xinlei Chen, Xiangxiang Xu, Xinyu Liu, Shijia Pan, Jiayou He, Hae Young Noh, Lin Zhang, Pei Zhang
PGA: Physics Guided and Adaptive Approach for Mobile Fine-Grained Air Pollution Estimation. UbiComp/ISWC Adjunct (2018)
Lichen Wang, Jiaxiang Wu, Shao-Lun Huang, Lizhong Zheng, Xiangxiang Xu, Lin Zhang, Junzhou Huang
An Efficient Approach to Informative Feature Extraction from Multimodal Data. CoRR (2018)
Xiangxiang Xu, Shao-Lun Huang, Lizhong Zheng, Lin Zhang
The Geometric Structure of Generalized Softmax Learning. ITW (2018)
Rui Ma, Xiangxiang Xu, Hae Young Noh, Pei Zhang, Lin Zhang
Generative Model Based Fine-Grained Air Pollution Inference for Mobile Sensing Systems. SenSys (2018)
Rui Ma, Xiangxiang Xu, Yue Wang, Hae Young Noh, Pei Zhang, Lin Zhang
Guiding the Data Learning Process with Physical Model in Air Pollution Inference. IEEE BigData (2018)
Xinyu Liu, Xinlei Chen, Xiangxiang Xu, Enhan Mai, Hae Young Noh, Pei Zhang, Lin Zhang
Delay Effect in Mobile Sensing System for Urban Air Pollution Monitoring. SenSys (2017)
Xinyu Liu, Xiangxiang Xu, Xinlei Chen, Enhan Mai, Hae Young Noh, Pei Zhang, Lin Zhang
Individualized Calibration of Industrial-Grade Gas Sensors in Air Quality Sensing System. SenSys (2017)
Xiangxiang Xu, Xinlei Chen, Xinyu Liu, Hae Young Noh, Pei Zhang, Lin Zhang
Gotcha II: Deployment of a Vehicle-based Environmental Sensing System: Poster Abstract. SenSys (2016)
Xinlei Chen, Xiangxiang Xu, Xinyu Liu, Hae Young Noh, Lin Zhang, Pei Zhang
HAP: Fine-Grained Dynamic Air Pollution Map Reconstruction by Hybrid Adaptive Particle Filter: Poster Abstract. SenSys (2016)
Xiangxiang Xu, Pei Zhang, Lin Zhang
Gotcha: a mobile urban sensing system. SenSys (2014)