Image registration robust to sparse large errors. - Jing Liu 009; Marian Chuang; Andrew D. Chisholm; Pamela C. Cosman (EMBC, 2015)

Sparsity regularized Principal Component Pursuit. - Jing Liu 009; Pamela C. Cosman; Bhaskar D. Rao (ICASSP, 2017)

Robust Linear Regression via ℓ0 Regularization. - Jing Liu 009; Pamela C. Cosman; Bhaskar D. Rao (IEEE Trans. Signal Process., 2018)

Sparse Bayesian Learning for Robust PCA. - Jing Liu 009; Yacong Ding; Bhaskar Rao 001 (ICASSP, 2019)

Robust PCA via ℓ0-ℓ1 Regularization. - Jing Liu 009; Bhaskar D. Rao (IEEE Trans. Signal Process., 2019)

Sparse Bayesian Learning for Robust PCA: Algorithms and Analyses. - Jing Liu 009; Bhaskar D. Rao (IEEE Trans. Signal Process., 2019)

Stabilizing Subject Transfer in EEG Classification with Divergence Estimation. - Niklas Smedemark-Margulies; Ye Wang 001; Toshiaki Koike-Akino; Jing Liu 009; Kieran Parsons; Yunus Bicer; Deniz Erdogmus (CoRR, 2023)

SuperLoRA: Parameter-Efficient Unified Adaptation of Large Foundation Models. - Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Pu (Perry) Wang; Matthew Brand; Guanghui Wang 001; Toshiaki Koike-Akino (BMVC, 2024)

Analyzing Inference Privacy Risks Through Gradients In Machine Learning. - Zhuohang Li; Andrew Lowy; Jing Liu 009; Toshiaki Koike-Akino; Kieran Parsons; Bradley A. Malin; Ye Wang 001 (CCS, 2024)

SuperLoRA: Parameter-Efficient Unified Adaptation for Large Vision Models. - Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Pu (Perry) Wang; Matthew Brand; Guanghui Wang 001; Toshiaki Koike-Akino (CVPR Workshops, 2024)

Random Channel Ablation for Robust Hand Gesture Classification with Multimodal Biosignals. - Keshav Bimbraw; Jing Liu 009; Ye Wang 001; Toshiaki Koike-Akino (EMBC, 2024)

Why Does Differential Privacy with Large Epsilon Defend Against Practical Membership Inference Attacks? - Andrew Lowy; Zhuohang Li; Jing Liu 009; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (CoRR, 2024)

SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules. - Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Pu (Perry) Wang; Matthew Brand; Guanghui Wang 001; Toshiaki Koike-Akino (CoRR, 2024)

Efficient Differentially Private Fine-Tuning of Diffusion Models. - Jing Liu 009; Andrew Lowy; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (CoRR, 2024)

GPT Sonograpy: Hand Gesture Decoding from Forearm Ultrasound Images via VLM. - Keshav Bimbraw; Ye Wang 001; Jing Liu 009; Toshiaki Koike-Akino (CoRR, 2024)

Variational Randomized Smoothing for Sample-Wise Adversarial Robustness. - Ryo Hase; Ye Wang 001; Toshiaki Koike-Akino; Jing Liu 009; Kieran Parsons (CoRR, 2024)

Exploring User-level Gradient Inversion with a Diffusion Prior. - Zhuohang Li; Andrew Lowy; Jing Liu 009; Toshiaki Koike-Akino; Bradley A. Malin; Kieran Parsons; Ye Wang 001 (CoRR, 2024)

Quantum Diffusion Models for Few-Shot Learning. - Ruhan Wang; Ye Wang 001; Jing Liu 009; Toshiaki Koike-Akino (CoRR, 2024)

Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage. - Md. Rafi Ur Rashid; Jing Liu 009; Toshiaki Koike-Akino; Ye Wang 001; Shagufta Mehnaz (AAAI, 2025)

Smoothed Embeddings for Robust Language Models. - Ryo Hase; Md. Rafi Ur Rashid; Ashley Lewis; Jing Liu 009; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (CoRR, 2025)

Winning Big with Small Models: Knowledge Distillation vs. Self-Training for Reducing Hallucination in QA Agents. - Ashley Lewis; Michael White; Jing Liu 009; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (CoRR, 2025)

LatentLLM: Attention-Aware Joint Tensor Compression. - Toshiaki Koike-Akino; Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Pu Wang 004; Matthew Brand (CoRR, 2025)

μ-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts. - Toshiaki Koike-Akino; Jing Liu 009; Ye Wang 001 (CoRR, 2025)

TuneComp: Joint Fine-tuning and Compression for Large Foundation Models. - Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Matthew Brand; Pu Wang 004; Toshiaki Koike-Akino (CoRR, 2025)

Probabilistic Forecasting for Building Energy Systems using Time-Series Foundation Models. - Young Jin Park; François G. Germain; Jing Liu 009; Ye Wang 001; Toshiaki Koike-Akino; Gordon Wichern; Navid Azizan; Christopher R. Laughman; Ankush Chakrabarty (CoRR, 2025)

AWP: Activation-Aware Weight Pruning and Quantization with Projected Gradient Descent. - Jing Liu 009; Toshiaki Koike-Akino; Ye Wang 001; Hassan Mansour; Matthew Brand (CoRR, 2025)