3 papers
cs.CR2025
MAUI: Reconstructing Private Client Data in Federated Transfer Learning
Ahaan Dabholkar, Atul Sharma, Z. Berkay Celik +1
Recent works in federated learning (FL) have shown the utility of leveraging transfer learning for balancing the benefits of FL and centralized learning. In this setting, federated…
cs.CV2025
Vision-Only Gaussian Splatting for Collaborative Semantic Occupancy Prediction
Cheng Chen, Hao Huang, Saurabh Bagchi
Collaborative perception enables connected vehicles to share information, overcoming occlusions and extending the limited sensing range inherent in single-agent (non-collaborative)…
cs.LG2025
Are Fast Methods Stable in Adversarially Robust Transfer Learning?
Joshua C. Zhao, Saurabh Bagchi
Transfer learning is often used to decrease the computational cost of model training, as fine-tuning a model allows a downstream task to leverage the features learned from the pre-…