15 citations · 48 across the 15 of their papers we have counts for
9 papers · 1 filter
Learning Set Functions with Implicit Differentiation
Gözde Özcan, Chengzhi Shi, Stratis Ioannidis
Ou et al. (2022) introduce the problem of learning set functions from data generated by a so-called optimal subset oracle. Their approach approximates the underlying utility functi…
T-PRIME: Transformer-based Protocol Identification for Machine-learning at the Edge
Mauro Belgiovine, Joshua Groen, Miquel Sirera +5
Spectrum sharing allows different protocols of the same standard (e.g., 802.11 family) or different standards (e.g., LTE and DVB) to coexist in overlapping frequency bands. As this…
SmoothHess: ReLU Network Feature Interactions via Stein's Lemma
Max Torop, Aria Masoomi, Davin Hill +3
Several recent methods for interpretability model feature interactions by looking at the Hessian of a neural network. This poses a challenge for ReLU networks, which are piecewise-…
Towards Bias Correction of FedAvg over Nonuniform and Time-Varying Communications
Ming Xiang, Stratis Ioannidis, Edmund Yeh +2
Federated learning (FL) is a decentralized learning framework wherein a parameter server (PS) and a collection of clients collaboratively train a model via minimizing a global obje…
DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning
Zifeng Wang, Zheng Zhan, Yifan Gong +4
Rehearsal-based approaches are a mainstay of continual learning (CL). They mitigate the catastrophic forgetting problem by maintaining a small fixed-size buffer with a subset of da…
Explanations of Black-Box Models based on Directional Feature Interactions
Aria Masoomi, Davin Hill, Zhonghui Xu +5
As machine learning algorithms are deployed ubiquitously to a variety of domains, it is imperative to make these often black-box models transparent. Several recent works explain bl…