20 citations · 40 across the 5 of their papers we have counts for
5 papers
Adaptive wavelet distillation from neural networks through interpretations
Wooseok Ha, Chandan Singh, Francois Lanusse +2
Recent deep-learning models have achieved impressive prediction performance, but often sacrifice interpretability and computational efficiency. Interpretability is crucial in many…
On Leveraging Unlabeled Data for Concurrent Positive-Unlabeled Classification and Robust Generation
Bing Yu, Ke Sun, He Wang +2
The scarcity of class-labeled data is a ubiquitous bottleneck in many machine learning problems. While abundant unlabeled data typically exist and provide a potential solution, it…
Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy
Ke Sun, Bing Yu, Zhouchen Lin +1
Regularization plays a crucial role in machine learning models, especially for deep neural networks. The existing regularization techniques mainly rely on the i.i.d. assumption and…
Interpreting Convolutional Neural Networks Through Compression
Reza Abbasi-Asl, Bin Yu
Convolutional neural networks (CNNs) achieve state-of-the-art performance in a wide variety of tasks in computer vision. However, interpreting CNNs still remains a challenge. This…
Structural Compression of Convolutional Neural Networks
Reza Abbasi-Asl, Bin Yu
Deep convolutional neural networks (CNNs) have been successful in many tasks in machine vision, however, millions of weights in the form of thousands of convolutional filters in CN…