Julia Nakhleh

jnakhleh@wisc.edu

I'm a PhD candidate at the University of Wisconsin-Madison, advised by Robert D. Nowak. My interests broadly lie in the mathematical theory of neural networks and deep learning, and connections with applied and computational harmonic analysis, nonparametric regression/function estimation, and compressed sensing. My recent research projects (see Publications) have characterized the functional properties and sparsity of neural networks trained with various weight-based regularization strategies.

Publications

Julia B. Nakhleh and Robert D. Nowak. "Global Minimizers of $\ell^p$ Regularized Objectives Yield the Sparsest ReLU Networks." arXiv preprint.

Julia B. Nakhleh, Joseph Shenouda, and Robert D. Nowak. "A New Neural Kernel Regime: the Inductive Bias of Multi-Task Learning." NeurIPS 2024. [proceedings] [arXiv]

Julian J. Katz-Samuels*, Julia B. Nakhleh*, Robert D. Nowak, and Yixuan Li. "Training OOD Detectors in their Natural Habitats." ICML 2022. [proceedings] [arXiv] *equal contribution