113 citations · 230 across the 8 of their papers we have counts for
8 papers
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
Jiong Zhang, Hsiang-fu Yu, Inderjit S. Dhillon
Deep neural networks have yielded superior performance in many applications; however, the gradient computation in a deep model with millions of instances lead to a lengthy training…
Minimal Paths for Tubular Structure Segmentation with Coherence Penalty and Adaptive Anisotropy
Da Chen, Jiong Zhang, Laurent D. Cohen
The minimal path method has proven to be particularly useful and efficient in tubular structure segmentation applications. In this paper, we propose a new minimal path model associ…
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
Jiong Zhang, Qi Lei, Inderjit S. Dhillon
Vanishing and exploding gradients are two of the main obstacles in training deep neural networks, especially in capturing long range dependencies in recurrent neural networks~(RNNs…
Learning Long Term Dependencies via Fourier Recurrent Units
Jiong Zhang, Yibo Lin, Zhao Song +1
It is a known fact that training recurrent neural networks for tasks that have long term dependencies is challenging. One of the main reasons is the vanishing or exploding gradient…
Retinal Microaneurysms Detection using Local Convergence Index Features
Behdad Dashtbozorg, Jiong Zhang, Bart M. ter Haar Romeny
Retinal microaneurysms are the earliest clinical sign of diabetic retinopathy disease. Detection of microaneurysms is crucial for the early diagnosis of diabetic retinopathy and pr…
Retrieving challenging vessel connections in retinal images by line co-occurrence statistics
Samaneh Abbasi-Sureshjani, Jiong Zhang, Remco Duits +1
Natural images contain often curvilinear structures, which might be disconnected, or partly occluded. Recovering the missing connection of disconnected structures is an open issue…
Extreme Stochastic Variational Inference: Distributed and Asynchronous
Jiong Zhang, Parameswaran Raman, Shihao Ji +3
Stochastic variational inference (SVI), the state-of-the-art algorithm for scaling variational inference to large-datasets, is inherently serial. Moreover, it requires the paramete…
Numerical Approaches for Linear Left-invariant Diffusions on SE(2), their Comparison to Exact Solutions, and their Applications in Retinal Imaging
Jiong Zhang, Remco Duits, Gonzalo Sanguinetti +1
Left-invariant PDE-evolutions on the roto-translation group (and their resolvent equations) have been widely studied in the fields of cortical modeling and image analysis.…