3 papers
cs.LG2025
Private Model Personalization Revisited
Conor Snedeker, Xinyu Zhou, Raef Bassily
We study model personalization under user-level differential privacy (DP) in the shared representation framework. In this problem, there are users whose data is statistically h…
cs.DC2025
Environment-Aware Dynamic Pruning for Pipelined Edge Inference
Austin O'Quinn, Conor Snedeker, Siyuan Zhang +1
IoT and edge-based inference systems require unique solutions to overcome resource limitations and unpredictable environments. In this paper, we propose an environment-aware dynami…
cs.LG2022
Limit Cycles of AdaBoost
Conor Snedeker
The iterative weight update for the AdaBoost machine learning algorithm may be realized as a dynamical map on a probability simplex. When learning a low-dimensional data set this a…