71 citations · 351 across the 26 of their papers we have counts for
29 papers
Active Learning at the ImageNet Scale
Zeyad Ali Sami Emam, Hong-Min Chu, Ping-Yeh Chiang +4
Active learning (AL) algorithms aim to identify an optimal subset of data for annotation, such that deep neural networks (DNN) can achieve better performance when trained on this l…
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
Liam Fowl, Jonas Geiping, Wojtek Czaja +2
Federated learning has quickly gained popularity with its promises of increased user privacy and efficiency. Previous works have shown that federated gradient updates contain infor…
Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release
Liam Fowl, Ping-yeh Chiang, Micah Goldblum +4
Large organizations such as social media companies continually release data, for example user images. At the same time, these organizations leverage their massive corpora of releas…
Exploring the high dimensional geometry of HSI features
Wojciech Czaja, Ilya Kavalerov, Weilin Li
We explore feature space geometries induced by the 3-D Fourier scattering transform and deep neural network with extended attribute profiles on four standard hyperspectral images.…
Maximal function pooling with applications
Wojciech Czaja, Weilin Li, Yiran Li +1
Inspired by the Hardy-Littlewood maximal function, we propose a novel pooling strategy which is called maxfun pooling. It is presented both as a viable alternative to some of the m…
Cortical Features for Defense Against Adversarial Audio Attacks
Ilya Kavalerov, Ruijie Zheng, Wojciech Czaja +1
We propose using a computational model of the auditory cortex as a defense against adversarial attacks on audio. We apply several white-box iterative optimization-based adversarial…