123 citations · 158 across the 8 of their papers we have counts for
5 papers · 1 filter
Improve Unsupervised Domain Adaptation with Mixup Training
Shen Yan, Huan Song, Nanxiang Li +2
Unsupervised domain adaptation studies the problem of utilizing a relevant source domain with abundant labels to build predictive modeling for an unannotated target domain. Recent…
Designing an Effective Metric Learning Pipeline for Speaker Diarization
Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song +1
State-of-the-art speaker diarization systems utilize knowledge from external data, in the form of a pre-trained distance metric, to effectively determine relative speaker identitie…
GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models
Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Huan Song +1
Modern data analysis pipelines are becoming increasingly complex due to the presence of multi-view information sources. While graphs are effective in modeling complex relationships…
Optimizing Kernel Machines using Deep Learning
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri +1
Building highly non-linear and non-parametric models is central to several state-of-the-art machine learning systems. Kernel methods form an important class of techniques that indu…
A Deep Learning Approach To Multiple Kernel Fusion
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri +2
Kernel fusion is a popular and effective approach for combining multiple features that characterize different aspects of data. Traditional approaches for Multiple Kernel Learning (…