1 code implementation • NeurIPS 2021 • Yonghyeon LEE, Hyeokjun Kwon, Frank Park
Unlike existing graph-based methods that attempt to encode the training data to some prescribed latent space distribution -- one consequence being that only the encoder is the object of the regularization -- NRAE merges local connectivity information contained in the neighborhood graphs with local quadratic approximations of the decoder function to formulate a new neighborhood reconstruction loss.
no code implementations • NeurIPS 2017 • Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank Park, Daniel D. Lee
This paper shows how metric learning can be used with Nadaraya-Watson (NW) kernel regression.
no code implementations • NeurIPS 2012 • Yung-Kyun Noh, Frank Park, Daniel D. Lee
This paper sheds light on some fundamental connections of the diffusion decision making model of neuroscience and cognitive psychology with k-nearest neighbor classification.