Ding, Jie

31 publications

NeurIPS 2025 Beyond Expectations: Quantile-Guided Alignment for Risk-Calibrated Language Models Xinran Wang, Jin Du, Azal Ahmad Khan, Qi Le, Enmao Diao, Jiawei Zhou, Jie Ding, Ali Anwar

TMLR 2025 Distributed Hierarchical Decomposition Framework for Multimodal Timeseries Prediction Wei Ye, Prashant Khanduri, Jiangweizhi Peng, Feng Tian, Jun Gao, Jie Ding, Zhi-Li Zhang, Mingyi Hong

AAAI 2025 Drop the Beat! Freestyler for Accompaniment Conditioned Rapping Voice Generation Ziqian Ning, Shuai Wang, Yuepeng Jiang, Jixun Yao, Lei He, Shifeng Pan, Jie Ding, Lei Xie

ICLR 2025 MAP: Multi-Human-Value Alignment Palette Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar

ICML 2025 On the Vulnerability of Applying Retrieval-Augmented Generation Within Knowledge-Intensive Application Domains Xun Xian, Ganghua Wang, Xuan Bi, Rui Zhang, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Mingyi Hong, Jie Ding

ICLR 2025 Probe Pruning: Accelerating LLMs Through Dynamic Pruning via Model-Probing Qi Le, Enmao Diao, Ziyan Wang, Xinran Wang, Jie Ding, Li Yang, Ali Anwar

UAI 2024 Base Models for Parabolic Partial Differential Equations Xingzi Xu, Ali Hasan, Jie Ding, Vahid Tarokh

ECCV 2024 CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning Erum Mushtaq, Duygu Nur Yaldiz, Yavuz Faruk Bakman, Jie Ding, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr

ICLR 2024 Demystifying Poisoning Backdoor Attacks from a Statistical Perspective Ganghua Wang, Xun Xian, Ashish Kundu, Jayanth Srinivasa, Xuan Bi, Mingyi Hong, Jie Ding

NeurIPS 2024 RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding

NeurIPS 2024 Unraveling the Gradient Descent Dynamics of Transformers Bingqing Song, Boran Han, Shuai Zhang, Jie Ding, Mingyi Hong

NeurIPS 2023 A Unified Detection Framework for Inference-Stage Backdoor Defenses Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding

TMLR 2023 Assisted Learning for Organizations with Limited Imbalanced Data Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou

ICLR 2023 Characteristic Neural Ordinary Differential Equation Xingzi Xu, Ali Hasan, Khalil Elkhalil, Jie Ding, Vahid Tarokh

TMLR 2023 Distributed Architecture Search over Heterogeneous Distributions Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr

ICLR 2023 Pruning Deep Neural Networks from a Sparsity Perspective Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh

UAI 2023 Robust Quickest Change Detection for Unnormalized Models Suya Wu, Enmao Diao, Jie Ding, Taposh Banerjee, Vahid Tarokh

AISTATS 2023 Score-Based Quickest Change Detection for Unnormalized Models Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh

ICML 2023 Understanding Backdoor Attacks Through the Adaptability Hypothesis Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding

ICMLW 2023 Visualizing and Analyzing the Topology of Neuron Activations in Deep Adversarial Training Youjia Zhou, Yi Zhou, Jie Ding, Bei Wang

NeurIPSW 2022 Building Large Machine Learning Models from Small Distributed Models: A Layer Matching Approach Xinwei Zhang, Bingqing Song, Mehrdad Honarkhah, Jie Ding, Mingyi Hong

NeurIPS 2022 GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations Enmao Diao, Jie Ding, Vahid Tarokh

NeurIPSW 2022 PerFedSI: A Framework for Personalized Federated Learning with Side Information Liam Collins, Enmao Diao, Tanya Roosta, Jie Ding, Tao Zhang

NeurIPS 2022 Self-Aware Personalized Federated Learning Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang

NeurIPS 2022 SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training Enmao Diao, Jie Ding, Vahid Tarokh

AISTATS 2021 Fisher Auto-Encoders Khalil Elkhalil, Ali Hasan, Jie Ding, Sina Farsiu, Vahid Tarokh

ICLR 2021 HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Enmao Diao, Jie Ding, Vahid Tarokh

ICLR 2021 Information Laundering for Model Privacy Xinran Wang, Yu Xiang, Jun Gao, Jie Ding

JMLR 2021 Model Linkage Selection for Cooperative Learning Jiaying Zhou, Jie Ding, Kean Ming Tan, Vahid Tarokh

NeurIPS 2020 Assisted Learning: A Framework for Multi-Organization Learning Xun Xian, Xinran Wang, Jie Ding, Reza Ghanadan

NeurIPS 2019 Gradient Information for Representation and Modeling Jie Ding, Robert Calderbank, Vahid Tarokh