Model Selection with Nonlinear Embedding for Unsupervised Domain Adaptation

no code implementations • 23 Jun 2017 • Hemanth Venkateswara, Shayok Chakraborty, Troy McDaniel, Sethuraman Panchanathan

To determine the parameters in the NET model (and in other unsupervised domain adaptation models), we introduce a validation procedure by sampling source data points that are similar in distribution to the target data.

General Classification Model Selection +1