98 citations · 359 across the 22 of their papers we have counts for
5 papers · 1 filter
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries
Qianjiang Hu, Xiao Wang, Wei Hu +1
Contrastive learning relies on constructing a collection of negative examples that are sufficiently hard to discriminate against positive queries when their representations are sel…
Knowledge-Enriched Distributional Model Inversion Attacks
Si Chen, Mostafa Kahla, Ruoxi Jia +1
Model inversion (MI) attacks are aimed at reconstructing training data from model parameters. Such attacks have triggered increasing concerns about privacy, especially given a grow…
Learning to Adaptively Scale Recurrent Neural Networks
Hao Hu, Liqiang Wang, Guo-Jun Qi
Recent advancements in recurrent neural network (RNN) research have demonstrated the superiority of utilizing multiscale structures in learning temporal representations of time ser…
Task-Agnostic Meta-Learning for Few-shot Learning
Muhammad Abdullah Jamal, Guo-Jun Qi, Mubarak Shah
Meta-learning approaches have been proposed to tackle the few-shot learning problem.Typically, a meta-learner is trained on a variety of tasks in the hopes of being generalizable t…
Rank Subspace Learning for Compact Hash Codes
Kai Li, Guojun Qi, Jun Ye +1
The era of Big Data has spawned unprecedented interests in developing hashing algorithms for efficient storage and fast nearest neighbor search. Most existing work learn hash funct…