1 citations · 1 across the 7 of their papers we have counts for
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A Mini-Batch Counterexample to Last-Iterate Convergence in Definable Optimization
Weiwei Kong
We give a counterexample to the convergence conjecture in Remark 12 of [Bolte & Pauwels, 2021] for mini-batch stochastic approximation with definable potentials. The construction u…
ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities?
Peihan Liu, Lucas Rosenblatt, Weiwei Kong +7
Differentially private (DP) text synthesis promises to unlock sensitive corpora for model training, but it remains unclear whether DP synthetic data transmits genuinely new knowled…
Decomposing Private Image Generation via Coarse-to-Fine Wavelet Modeling
Jasmine Bayrooti, Weiwei Kong, Natalia Ponomareva +3
Generative models trained on sensitive image datasets risk memorizing and reproducing individual training examples, making strong privacy guarantees essential. While differential p…
JAX-Privacy: A library for differentially private machine learning
Ryan McKenna, Galen Andrew, Borja Balle +6
JAX-Privacy is a library designed to simplify the deployment of robust and performant mechanisms for differentially private machine learning. Guided by design principles of usabili…
Learning from Synthetic Data: Limitations of ERM
Kareem Amin, Alex Bie, Weiwei Kong +2
The prevalence and low cost of LLMs have led to a rise of synthetic content. From review sites to court documents, "natural" content has been contaminated by data points that appea…