177 citations · 439 across the 15 of their papers we have counts for
4 papers · 1 filter
Dimensionality-Driven Learning with Noisy Labels
Xingjun Ma, Yisen Wang, Michael E. Houle +5
Datasets with significant proportions of noisy (incorrect) class labels present challenges for training accurate Deep Neural Networks (DNNs). We propose a new perspective for under…
Learning Deep Hidden Nonlinear Dynamics from Aggregate Data
Yisen Wang, Bo Dai, Lingkai Kong +3
Learning nonlinear dynamics from diffusion data is a challenging problem since the individuals observed may be different at different time points, generally following an aggregate…
Iterative Learning with Open-set Noisy Labels
Yisen Wang, Weiyang Liu, Xingjun Ma +4
Large-scale datasets possessing clean label annotations are crucial for training Convolutional Neural Networks (CNNs). However, labeling large-scale data can be very costly and err…
Online Cluster Validity Indices for Streaming Data
Masud Moshtaghi, James C. Bezdek, Sarah M. Erfani +2
Cluster analysis is used to explore structure in unlabeled data sets in a wide range of applications. An important part of cluster analysis is validating the quality of computation…