71 citations · 416 across the 50 of their papers we have counts for
5 papers · 1 filter
Graph Convolution with Low-rank Learnable Local Filters
Xiuyuan Cheng, Zichen Miao, Qiang Qiu
Geometric variations like rotation, scaling, and viewpoint changes pose a significant challenge to visual understanding. One common solution is to directly model certain intrinsic…
Learning to Collaborate for User-Controlled Privacy
Martin Bertran, Natalia Martinez, Afroditi Papadaki +3
It is becoming increasingly clear that users should own and control their data. Utility providers are also becoming more interested in guaranteeing data privacy. As such, users and…
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
Qiang Qiu, Xiuyuan Cheng, Robert Calderbank +1
Filters in a Convolutional Neural Network (CNN) contain model parameters learned from enormous amounts of data. In this paper, we suggest to decompose convolutional filters in CNN…
Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems
Jure Sokolic, Qiang Qiu, Miguel R. D. Rodrigues +1
Security, privacy, and fairness have become critical in the era of data science and machine learning. More and more we see that achieving universally secure, private, and fair syst…
The Role of Principal Angles in Subspace Classification
Jiaji Huang, Qiang Qiu, Robert Calderbank
Subspace models play an important role in a wide range of signal processing tasks, and this paper explores how the pairwise geometry of subspaces influences the probability of misc…