665 citations · 1.3k across the 20 of their papers we have counts for
4 papers · 1 filter
Regularizing Second-Order Influences for Continual Learning
Zhicheng Sun, Yadong Mu, Gang Hua
Continual learning aims to learn on non-stationary data streams without catastrophically forgetting previous knowledge. Prevalent replay-based methods address this challenge by reh…
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai +3
Convolutional Neural Networks (CNNs) are known to rely more on local texture rather than global shape when making decisions. Recent work also indicates a close relationship between…
Stochastic Gradient Made Stable: A Manifold Propagation Approach for Large-Scale Optimization
Yadong Mu, Wei Liu, Wei Fan
Stochastic gradient descent (SGD) holds as a classical method to build large scale machine learning models over big data. A stochastic gradient is typically calculated from a limit…
Compact Hyperplane Hashing with Bilinear Functions
Wei Liu, Jun Wang, Yadong Mu +2
Hyperplane hashing aims at rapidly searching nearest points to a hyperplane, and has shown practical impact in scaling up active learning with SVMs. Unfortunately, the existing ran…