Jie Ding

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 99

Top Venues

CoRR

ICASSP

IEEE Trans. Signal Process.

ICLR

Publications

Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees. CoRR (2024)
Enmao Diao, Qi Le, Suya Wu, Xinran Wang, Ali Anwar, Jie Ding, Vahid Tarokh
ColA: Collaborative Adaptation with Gradient Learning. CoRR (2024)
Erum Mushtaq, Duygu Nur Yaldiz, Yavuz Faruk Bakman, Jie Ding, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr
CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning. CoRR (2024)
Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
Quickest Change Detection for Unnormalized Statistical Models. IEEE Trans. Inf. Theory 70 (2) (2024)
Ganghua Wang, Xun Xian, Ashish Kundu, Jayanth Srinivasa, Xuan Bi, Mingyi Hong, Jie Ding
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective. ICLR (2024)
Xingzi Xu, Ali Hasan, Jie Ding, Vahid Tarokh
Base Models for Parabolic Partial Differential Equations. CoRR (2024)
Jiawei Zhang, Yuhong Yang, Jie Ding
Additive-Effect Assisted Learning. CoRR (2024)
Youjia Zhou, Yi Zhou, Jie Ding, Bei Wang
Visualizing and Analyzing the Topology of Neuron Activations in Deep Adversarial Training. TAG-ML (2023)
Gen Li, Ganghua Wang, Jie Ding
Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization. CoRR (2023)
Xingzi Xu, Ali Hasan, Khalil Elkhalil, Jie Ding, Vahid Tarokh
Characteristic Neural Ordinary Differential Equation. ICLR (2023)
Chenglong Ye, Reza Ghanadan, Jie Ding
Meta Clustering for Collaborative Learning. J. Comput. Graph. Stat. 32 (3) (2023)
Ganghua Wang, Xun Xian, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective. CoRR (2023)
Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
Score-based Quickest Change Detection for Unnormalized Models. AISTATS (2023)
Erum Mushtaq, Yavuz Faruk Bakman, Jie Ding, Salman Avestimehr
Federated Alternate Training (Fat): Leveraging Unannotated Data Silos in Federated Segmentation for Medical Imaging. ISBI (2023)
Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh
Pruning Deep Neural Networks from a Sparsity Perspective. CoRR (2023)
Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh
Pruning Deep Neural Networks from a Sparsity Perspective. ICLR (2023)
Christophe Dupuy, Jimit Majmudar, Jixuan Wang, Tanya G. Roosta, Rahul Gupta, Clement Chung, Jie Ding, Salman Avestimehr
Quantifying Catastrophic Forgetting in Continual Federated Learning. ICASSP (2023)
Suya Wu, Enmao Diao, Jie Ding, Taposh Banerjee, Vahid Tarokh
Robust Quickest Change Detection for Unnormalized Models. UAI (2023)
Erum Mushtaq, Yavuz Faruk Bakman, Jie Ding, Salman Avestimehr
Federated Alternate Training (FAT): Leveraging Unannotated Data Silos in Federated Segmentation for Medical Imaging. CoRR (2023)
Gen Li, Jie Ding
Towards Understanding Variation-Constrained Deep Neural Networks. IEEE Trans. Signal Process. 71 (2023)
Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou
Assisted Learning for Organizations with Limited Imbalanced Data. Trans. Mach. Learn. Res. 2023 (2023)
Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
A Unified Detection Framework for Inference-Stage Backdoor Defenses. NeurIPS (2023)
Gen Li, Ganghua Wang, Jie Ding
Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization. IEEE Trans. Inf. Theory 69 (9) (2023)
Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
Understanding Backdoor Attacks through the Adaptability Hypothesis. ICML (2023)
Cheng Chen, Jiawei Zhang, Jie Ding, Yi Zhou
Assisted Unsupervised Domain Adaptation. ISIT (2023)
Chedi Morchdi, Yi Zhou, Jie Ding, Bei Wang
Exploring Gradient Oscillation in Deep Neural Network Training. Allerton (2023)
Ahmad Faraz Khan, Xinran Wang, Qi Le, Azal Ahmad Khan, Haider Ali, Jie Ding, Ali Butt, Ali Anwar
PI-FL: Personalized and Incentivized Federated Learning. CoRR (2023)
Xinran Wang, Qi Le, Ahmad Faraz Khan, Jie Ding, Ali Anwar
A Framework for Incentivized Collaborative Learning. CoRR (2023)
Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
Quickest Change Detection for Unnormalized Statistical Models. CoRR (2023)
Enmao Diao, Jie Ding, Vahid Tarokh
Multimodal Controller for Generative Models. CVMI (2022)
Enmao Diao, Jie Ding, Vahid Tarokh
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations. NeurIPS (2022)
Mohammadreza Soltani, Suya Wu, Yuerong Li, Jie Ding, Vahid Tarokh
On The Energy Statistics of Feature Maps in Pruning of Neural Networks with Skip-Connections. DCC (2022)
Qi Le, Enmao Diao, Xinran Wang, Ali Anwar, Vahid Tarokh, Jie Ding
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders. IEEECONF (2022)
Jie Ding, Bangjun Ding
Interval Privacy: A Framework for Privacy-Preserving Data Collection. IEEE Trans. Signal Process. 70 (2022)
Suya Wu, Enmao Diao, Khalil Elkhalil, Jie Ding, Vahid Tarokh
Score-Based Hypothesis Testing for Unnormalized Models. IEEE Access 10 (2022)
Xun Xian, Mingyi Hong, Jie Ding
Mismatched Supervised Learning. ICASSP (2022)
Qi Le, Enmao Diao, Xinran Wang, Ali Anwar, Vahid Tarokh, Jie Ding
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders. CoRR (2022)
Xinran Wang, Jiawei Zhang, Mingyi Hong, Yuhong Yang, Jie Ding
Parallel Assisted Learning. IEEE Trans. Signal Process. 70 (2022)
Xun Xian, Mingyi Hong, Jie Ding
Understanding Model Extraction Games. TPS-ISA (2022)
Gen Li, Yuantao Gu, Jie Ding
$\ell _1$ Regularization in Two-Layer Neural Networks. IEEE Signal Process. Lett. 29 (2022)
Mohammadreza Soltani, Suya Wu, Yuerong Li, Jie Ding, Vahid Tarokh
On The Energy Statistics of Feature Maps in Pruning of Neural Networks with Skip-Connections. CoRR (2022)
Wenjing Yang, Ganghua Wang, Enmao Diao, Vahid Tarokh, Jie Ding, Yuhong Yang
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation. CoRR (2022)
Xun Xian, Mingyi Hong, Jie Ding
A Framework for Understanding Model Extraction Attack and Defense. CoRR (2022)
Enmao Diao, Jie Ding, Vahid Tarokh
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training. NeurIPS (2022)
Xingzi Xu, Ali Hasan, Khalil Elkhalil, Jie Ding, Vahid Tarokh
Characteristic Neural Ordinary Differential Equations. CoRR (2021)
Mohammadreza Soltani, Suya Wu, Yuerong Li, Robert J. Ravier, Jie Ding, Vahid Tarokh
Compressing Deep Networks Using Fisher Score of Feature Maps. DCC (2021)
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
Information Laundering for Model Privacy. ICLR (2021)
Jiaying Zhou, Xun Xian, Na Li, Jie Ding
Assisted Learning: Cooperative AI with Autonomy. ICASSP (2021)
Enmao Diao, Jie Ding, Vahid Tarokh
Gradient Assisted Learning. CoRR (2021)
Jiaying Zhou, Jie Ding, Kean Ming Tan, Vahid Tarokh
Model Linkage Selection for Cooperative Learning. J. Mach. Learn. Res. 22 (2021)
Enmao Diao, Jie Ding, Vahid Tarokh
SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients. CoRR (2021)
Yunxiang Lu, Min Xiao, Jinling Liang, Jie Ding, Ying Zhou, Youhong Wan, Chunxia Fan
Hybrid Control Synthesis for Turing Instability and Hopf Bifurcation of Marine Planktonic Ecosystems With Diffusion. IEEE Access 9 (2021)
Enmao Diao, Vahid Tarokh, Jie Ding
Privacy-Preserving Multi-Target Multi-Domain Recommender Systems with Assisted AutoEncoders. CoRR (2021)
Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou
Assisted Learning for Organizations with Limited Data. CoRR (2021)
Enmao Diao, Jie Ding, Vahid Tarokh
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients. ICLR (2021)
Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh
On Statistical Efficiency in Learning. IEEE Trans. Inf. Theory 67 (4) (2021)
Jiawei Zhang, Jie Ding, Yuhong Yang
Targeted Cross-Validation. CoRR (2021)
Khalil Elkhalil, Ali Hasan, Jie Ding, Sina Farsiu, Vahid Tarokh
Fisher Auto-Encoders. AISTATS (2021)
Jiaying Zhou, Xun Xian, Na Li, Jie Ding
ASCII: ASsisted Classification with Ignorance Interchange. CoRR (2020)
Enmao Diao, Jie Ding, Vahid Tarokh
DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression. DCC (2020)
Xun Xian, Xinran Wang, Jie Ding, Reza Ghanadan
Assisted Learning: A Framework for Multi-Organization Learning. NeurIPS (2020)
Cat P. Le, Yi Zhou, Jie Ding, Vahid Tarokh
Supervised Encoding for Discrete Representation Learning. ICASSP (2020)
Suya Wu, Enmao Diao, Jie Ding, Vahid Tarokh
Deep Clustering of Compressed Variational Embeddings. DCC (2020)
Enmao Diao, Jie Ding, Vahid Tarokh
Multimodal Controller for Generative Models. CoRR (2020)
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
Information Laundering for Model Privacy. CoRR (2020)
Jianyou Wang, Michael Xue, Ryan Culhane, Enmao Diao, Jie Ding, Vahid Tarokh
Speech Emotion Recognition with Dual-Sequence LSTM Architecture. ICASSP (2020)
Xun Xian, Xinran Wang, Mingyi Hong, Jie Ding, Reza Ghanadan
Imitation Privacy. CoRR (2020)
Mohammadreza Soltani, Suya Wu, Jie Ding, Robert J. Ravier, Vahid Tarokh
On the Information of Feature Maps and Pruning of Deep Neural Networks. ICPR (2020)
Khalil Elkhalil, Ali Hasan, Jie Ding, Sina Farsiu, Vahid Tarokh
Fisher Auto-Encoders. CoRR (2020)
Xun Xian, Xinran Wang, Jie Ding, Reza Ghanadan
Assisted Learning and Imitation Privacy. CoRR (2020)
Chris Cannella, Jie Ding, Mohammadreza Soltani, Yi Zhou, Vahid Tarokh
Perception-Distortion Trade-Off with Restricted Boltzmann Machines. ICASSP (2020)
Chenglong Ye, Jie Ding, Reza Ghanadan
Meta Clustering for Collaborative Learning. CoRR (2020)
Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh
On Statistical Efficiency in Learning. CoRR (2020)
Jun Gao, Jie Ding
Large Deviation Principle for the Whittaker 2d Growth Model. CoRR (2020)
Enmao Diao, Jie Ding, Vahid Tarokh
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients. CoRR (2020)
Enmao Diao, Jie Ding, Vahid Tarokh
Restricted Recurrent Neural Networks. CoRR (2019)
Jie Ding, A. Robert Calderbank, Vahid Tarokh
Gradient Information for Representation and Modeling. NeurIPS (2019)
Suya Wu, Enmao Diao, Jie Ding, Vahid Tarokh
Deep Clustering of Compressed Variational Embeddings. CoRR (2019)
Enmao Diao, Jie Ding, Vahid Tarokh
Distributed Lossy Image Compression with Recurrent Networks. CoRR (2019)
Cat P. Le, Yi Zhou, Jie Ding, Vahid Tarokh
Supervised Encoding for Discrete Representation Learning. CoRR (2019)
Jianyou Wang, Michael Xue, Ryan Culhane, Enmao Diao, Jie Ding, Vahid Tarokh
Speech Emotion Recognition with Dual-Sequence LSTM Architecture. CoRR (2019)
Jie Ding, Jiawei Zhou, Vahid Tarokh
Asymptotically Optimal Prediction for Time-Varying Data Generating Processes. IEEE Trans. Inf. Theory 65 (5) (2019)
Yu Xiang, Jie Ding, Vahid Tarokh
Estimation of the Evolutionary Spectra With Application to Stationarity Test. IEEE Trans. Signal Process. 67 (5) (2019)
Enmao Diao, Jie Ding, Vahid Tarokh
Restricted Recurrent Neural Networks. IEEE BigData (2019)
Jiawei Zhang, Jie Ding, Yuhong Yang
A Binary Regression Adaptive Goodness-of-fit Test (BAGofT). CoRR (2019)
Chris Cannella, Jie Ding, Mohammadreza Soltani, Vahid Tarokh
Perception-Distortion Trade-off with Restricted Boltzmann Machines. CoRR (2019)
Shahin Shahrampour, Mohammad Noshad, Jie Ding, Vahid Tarokh
Online Learning for Multimodal Data Fusion With Application to Object Recognition. IEEE Trans. Circuits Syst. II Express Briefs (9) (2018)
Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh
A Penalized Method for the Predictive Limit of Learning. ICASSP (2018)
Yu Xiang, Jie Ding, Vahid Tarokh
Evolutionary Spectra Based on the Multitaper Method with Application To Stationarity Test. ICASSP (2018)
Jie Ding, Vahid Tarokh, Jing-Yu Yang
Bridging AIC and BIC: A New Criterion for Autoregression. IEEE Trans. Inf. Theory 64 (6) (2018)
Jie Ding, Vahid Tarokh, Yuhong Yang
Model Selection Techniques - An Overview. CoRR (2018)
Jie Ding, Shahin Shahrampour, Kathryn Heal, Vahid Tarokh
Analysis of Multistate Autoregressive Models. IEEE Trans. Signal Process. 66 (9) (2018)
Jie Ding, Vahid Tarokh, Yuhong Yang
Model Selection Techniques: An Overview. IEEE Signal Process. Mag. 35 (6) (2018)
Zhun Deng, Jie Ding, Kathryn Heal, Vahid Tarokh
The number of independent sets in hexagonal graphs. ISIT (2017)
Qiuyi Han, Jie Ding, Edoardo M. Airoldi, Vahid Tarokh
Modeling nonlinearity in multi-dimensional dependent data. GlobalSIP (2017)
Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh
Detecting structural changes in dependent data. GlobalSIP (2017)
Jie Ding, Jiawei Zhou, Vahid Tarokh
Optimal prediction of data with unknown abrupt change points. GlobalSIP (2017)
Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh
Multiple Change Point Analysis: Fast Implementation and Strong Consistency. IEEE Trans. Signal Process. 65 (17) (2017)
Qiuyi Han, Jie Ding, Edoardo M. Airoldi, Vahid Tarokh
SLANTS: Sequential Adaptive Nonlinear Modeling of Time Series. IEEE Trans. Signal Process. 65 (19) (2017)
Jie Ding, Mohammad Noshad, Vahid Tarokh
Complementary Lattice Arrays for Coded Aperture Imaging. CoRR (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jie Ding