9 citations · 26 across the 17 of their papers we have counts for
6 papers · 1 filter
TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks
Khondoker Murad Hossain, Tim Oates
As deep neural networks and the datasets used to train them get larger, the default approach to integrating them into research and commercial projects is to download a pre-trained…
Why Batch Normalization Damage Federated Learning on Non-IID Data?
Yanmeng Wang, Qingjiang Shi, Tsung-Hui Chang
As a promising distributed learning paradigm, federated learning (FL) involves training deep neural network (DNN) models at the network edge while protecting the privacy of the edg…
Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognition
Yihong Dong, Ying Peng, Muqiao Yang +2
Deep neural networks have been shown as a class of useful tools for addressing signal recognition issues in recent years, especially for identifying the nonlinear feature structure…
An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization
Lunchen Xie, Jiaqi Liu, Songtao Lu +2
XGBoost is one of the most widely used machine learning models in the industry due to its superior learning accuracy and efficiency. Targeting at data isolation issues in the big d…
Towards Flexible Sparsity-Aware Modeling: Automatic Tensor Rank Learning Using The Generalized Hyperbolic Prior
Lei Cheng, Zhongtao Chen, Qingjiang Shi +2
Tensor rank learning for canonical polyadic decomposition (CPD) has long been deemed as an essential yet challenging problem. In particular, since the tensor rank controls the comp…
Optimally Combining Classifiers for Semi-Supervised Learning
Zhiguo Wang, Liusha Yang, Feng Yin +3
This paper considers semi-supervised learning for tabular data. It is widely known that Xgboost based on tree model works well on the heterogeneous features while transductive supp…