3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2021
Learning Accurate and Interpretable Decision Rule Sets from Neural Networks
Litao Qiao, Weijia Wang, Bill Lin
This paper proposes a new paradigm for learning a set of independent logical rules in disjunctive normal form as an interpretable model for classification. We consider the problem…
cs.LG2020
Differentially-private Federated Neural Architecture Search
Ishika Singh, Haoyi Zhou, Kunlin Yang +3
Neural architecture search, which aims to automatically search for architectures (e.g., convolution, max pooling) of neural networks that maximize validation performance, has achie…
cs.LG2020★ 3 cited
Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models
Siavash Khodadadeh, Sharare Zehtabian, Saeed Vahidian +3
Unsupervised meta-learning approaches rely on synthetic meta-tasks that are created using techniques such as random selection, clustering and/or augmentation. Unfortunately, cluste…