Publications

13 / 3,734 publications found.


  •  Wang, R., Wang, Y., Liu, J., Koike-Akino, T., "Quantum Diffusion Models for Few-Shot Learning", arXiv, November 2024.
    BibTeX arXiv
    • @article{Wang2024nov,
    • author = {Wang, Ruhan and Wang, Ye and Liu, Jing and Koike-Akino, Toshiaki}},
    • title = {Quantum Diffusion Models for Few-Shot Learning},
    • journal = {arXiv},
    • year = 2024,
    • month = nov,
    • url = {https://arxiv.org/abs/2411.04217}
    • }
  •  Li, Z., Lowy, A., Liu, J., Koike-Akino, T., Parsons, K., Malin, B., Wang, Y., "Analyzing Inference Privacy Risks Through Gradients In Machine Learning", ACM Conference on Computer and Communications Security (CCS), October 2024.
    BibTeX TR2024-141 PDF
    • @inproceedings{Li2024oct,
    • author = {Li, Zhuohang and Lowy, Andrew and Liu, Jing and Koike-Akino, Toshiaki and Parsons, Kieran and Malin, Bradley and Wang, Ye}},
    • title = {Analyzing Inference Privacy Risks Through Gradients In Machine Learning},
    • booktitle = {ACM Conference on Computer and Communications Security (CCS)},
    • year = 2024,
    • month = oct,
    • url = {https://www.merl.com/publications/TR2024-141}
    • }
  •  Rashid, M.R.U., Liu, J., Koike-Akino, T., Mehnaz, S., Wang, Y., "Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage", arXiv, August 2024.
    BibTeX arXiv
    • @article{Rashid2024aug,
    • author = {Rashid, Md Rafi Ur and Liu, Jing and Koike-Akino, Toshiaki and Mehnaz, Shagufta and Wang, Ye}},
    • title = {Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage},
    • journal = {arXiv},
    • year = 2024,
    • month = aug,
    • url = {https://arxiv.org/abs/2408.17354}
    • }
  •  Liu, J., Lowy, A., Koike-Akino, T., Parsons, K., Wang, Y., "Efficient Differentially Private Fine-Tuning of Diffusion Models", International Conference on Machine Learning (ICML) workshop (Next Generation of AI Safety), July 2024.
    BibTeX TR2024-104 PDF
    • @inproceedings{Liu2024jul,
    • author = {Liu, Jing and Lowy, Andrew and Koike-Akino, Toshiaki and Parsons, Kieran and Wang, Ye}},
    • title = {Efficient Differentially Private Fine-Tuning of Diffusion Models},
    • booktitle = {International Conference on Machine Learning (ICML) workshop (Next Generation of AI Safety)},
    • year = 2024,
    • month = jul,
    • url = {https://www.merl.com/publications/TR2024-104}
    • }
  •  Bimbraw, K., Liu, J., Wang, Y., Koike-Akino, T., "Random Channel Ablation for Robust Hand Gesture Classification with Multimodal Biosignals", International Conference of the IEEE Engineering in Medicine and Biology Society, July 2024.
    BibTeX TR2024-103 PDF
    • @inproceedings{Bimbraw2024jul3,
    • author = {Bimbraw, Keshav and Liu, Jing and Wang, Ye and Koike-Akino, Toshiaki}},
    • title = {Random Channel Ablation for Robust Hand Gesture Classification with Multimodal Biosignals},
    • booktitle = {International Conference of the IEEE Engineering in Medicine and Biology Society},
    • year = 2024,
    • month = jul,
    • url = {https://www.merl.com/publications/TR2024-103}
    • }
  •  Hase, R., Wang, Y., Koike-Akino, T., Liu, J., Parsons, K., "Variational Randomized Smoothing for Sample-Wise Adversarial Robustness", arXiv, July 2024.
    BibTeX arXiv
    • @article{Hase2024jul,
    • author = {Hase, Ryo and Wang, Ye and Koike-Akino, Toshiaki and Liu, Jing and Parsons, Kieran}},
    • title = {Variational Randomized Smoothing for Sample-Wise Adversarial Robustness},
    • journal = {arXiv},
    • year = 2024,
    • month = jul,
    • url = {https://arxiv.org/abs/2407.11844}
    • }
  •  Bimbraw, K., Wang, Y., Liu, J., Koike-Akino, T., "GPT Sonograpy: Hand Gesture Decoding from Forearm Ultrasound Images via VLM", arXiv, July 2024.
    BibTeX arXiv
    • @article{Bimbraw2024jul2,
    • author = {Bimbraw, Keshav and Wang, Ye and Liu, Jing and Koike-Akino, Toshiaki}},
    • title = {GPT Sonograpy: Hand Gesture Decoding from Forearm Ultrasound Images via VLM},
    • journal = {arXiv},
    • year = 2024,
    • month = jul,
    • url = {https://arxiv.org/abs/2407.10870}
    • }
  •  Chen, X., Liu, J., Wang, Y., Wang, P., Brand, M., Wang, G., Koike-Akino, T., "SuperLoRA: Parameter-Efficient Unified Adaptation for Large Vision Models", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), DOI: 10.1109/​CVPRW63382.2024.00804, June 2024, pp. 8050-8055.
    BibTeX TR2024-062 PDF
    • @inproceedings{Chen2024jun,
    • author = {Chen, Xiangyu and Liu, Jing and Wang, Ye and Wang, Pu and Brand, Matthew and Wang, Guanghui and Koike-Akino, Toshiaki}},
    • title = {SuperLoRA: Parameter-Efficient Unified Adaptation for Large Vision Models},
    • booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    • year = 2024,
    • pages = {8050--8055},
    • month = jun,
    • publisher = {IEEE},
    • doi = {10.1109/CVPRW63382.2024.00804},
    • url = {https://www.merl.com/publications/TR2024-062}
    • }
  •  Chen, X., Liu, J., Wang, Y., Wang, P., Brand, M., Wang, G., Koike-Akino, T., "SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules", arXiv, March 2024.
    BibTeX arXiv
    • @article{Chen2024mar,
    • author = {Chen, Xiangyu and Liu, Jing and Wang, Ye and Wang, Pu and Brand, Matthew and Wang, Guanghui and Koike-Akino, Toshiaki},
    • title = {SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules},
    • journal = {arXiv},
    • year = 2024,
    • month = mar,
    • url = {https://arxiv.org/abs/2403.11887}
    • }
  •  Lowy, A., Li, Z., Liu, J., Koike-Akino, T., Parsons, K., Wang, Y., "Why Does Differential Privacy with Large ε Defend Against Practical Membership Inference Attacks?", AAAI Workshop on Privacy-Preserving Artificial Intelligence, February 2024.
    BibTeX TR2024-009 PDF
    • @inproceedings{Lowy2024feb2,
    • author = {Lowy, Andrew and Li, Zhuohang and Liu, Jing and Koike-Akino, Toshiaki and Parsons, Kieran and Wang, Ye},
    • title = {Why Does Differential Privacy with Large ε Defend Against Practical Membership Inference Attacks?},
    • booktitle = {AAAI Workshop on Privacy-Preserving Artificial Intelligence},
    • year = 2024,
    • month = feb,
    • url = {https://www.merl.com/publications/TR2024-009}
    • }
  •  Liu, J., Koike-Akino, T., Wang, P., Brand, M., Wang, Y., Parsons, K., "LoDA: Low-Dimensional Adaptation of Large Language Models", Advances in Neural Information Processing Systems (NeurIPS) workshop, December 2023.
    BibTeX TR2023-150 PDF
    • @inproceedings{Liu2023dec,
    • author = {Liu, Jing and Koike-Akino, Toshiaki and Wang, Pu and Brand, Matthew and Wang, Ye and Parsons, Kieran},
    • title = {LoDA: Low-Dimensional Adaptation of Large Language Models},
    • booktitle = {Advances in Neural Information Processing Systems (NeurIPS) workshop},
    • year = 2023,
    • month = dec,
    • url = {https://www.merl.com/publications/TR2023-150}
    • }
  •  Li, Z., Lowy, A., Liu, J., Koike-Akino, T., Malin, B., Parsons, K., Wang, Y., "Exploring User-level Gradient Inversion with a Diffusion Prior", International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS, December 2023.
    BibTeX TR2023-149 PDF
    • @inproceedings{Li2023dec,
    • author = {Li, Zhuohang and Lowy, Andrew and Liu, Jing and Koike-Akino, Toshiaki and Malin, Bradley and Parsons, Kieran and Wang, Ye},
    • title = {Exploring User-level Gradient Inversion with a Diffusion Prior},
    • booktitle = {International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS},
    • year = 2023,
    • month = dec,
    • url = {https://www.merl.com/publications/TR2023-149}
    • }
  •  Smedemark-Margulies, N., Wang, Y., Koike-Akino, T., Liu, J., Parsons, K., Bicer, Y., Erdogmus, D., "Stabilizing Subject Transfer in EEG Classification with Divergence Estimation", arXiv, October 2023.
    BibTeX arXiv
    • @article{Smedemark-Margulies2023oct,
    • author = {Smedemark-Margulies, Niklas and Wang, Ye and Koike-Akino, Toshiaki and Liu, Jing and Parsons, Kieran and Bicer, Yunus and Erdogmus, Deniz},
    • title = {Stabilizing Subject Transfer in EEG Classification with Divergence Estimation},
    • journal = {arXiv},
    • year = 2023,
    • month = oct,
    • url = {https://arxiv.org/abs/2310.08762}
    • }