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Ragav Venkatesan

2 accepted papers

2019

d-SNE: Domain Adaptation Using Stochastic Neighborhood Embedding

CVPR 2019oral

On the one hand, deep neural networks are effective in learning large datasets. On the other, they are inefficient with their data usage. They often require copious amount of labeled-data to train their scads of parameters. Training larger and deeper networks is hard without appropriate regularizati…

Cited by 163PDFcodeScholar
2015

Simpler Non-Parametric Methods Provide as Good or Better Results to Multiple-Instance Learning

ICCV 2015poster

Multiple-instance learning (MIL) is a unique learning problem in which training data labels are available only for collections of objects (called bags) instead of individual objects (called instances). A plethora of approaches have been developed to solve this problem in the past years. Popular meth…

Cited by 25PDFScholar