6 citations · 21 across the 8 of their papers we have counts for
5 papers
Datasets for Studying Generalization from Easy to Hard Examples
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta +5
We describe new datasets for studying generalization from easy to hard examples.
Guided Hyperparameter Tuning Through Visualization and Inference
Hyekang Joo, Calvin Bao, Ishan Sen +2
For deep learning practitioners, hyperparameter tuning for optimizing model performance can be a computationally expensive task. Though visualization can help practitioners relate…
Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets
Roozbeh Yousefzadeh, Furong Huang
Deep learning models extract, before a final classification layer, features or patterns which are key for their unprecedented advantageous performance. However, the process of comp…
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers
Chen Zhu, Renkun Ni, Ping-yeh Chiang +3
Convex relaxations are effective for training and certifying neural networks against norm-bounded adversarial attacks, but they leave a large gap between certifiable and empirical…
ARMA Nets: Expanding Receptive Field for Dense Prediction
Jiahao Su, Shiqi Wang, Furong Huang
Global information is essential for dense prediction problems, whose goal is to compute a discrete or continuous label for each pixel in the images. Traditional convolutional layer…