10 citations · 31 across the 5 of their papers we have counts for
4 papers · 1 filter
Bayesian Optimization with Approximate Set Kernels
Jungtaek Kim, Michael McCourt, Tackgeun You +2
We propose a practical Bayesian optimization method over sets, to minimize a black-box function that takes a set as a single input. Because set inputs are permutation-invariant, tr…
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare
Ingyo Chung, Saehoon Kim, Juho Lee +3
We present a personalized and reliable prediction model for healthcare, which can provide individually tailored medical services such as diagnosis, disease treatment, and preventio…
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
Jay Heo, Hae Beom Lee, Saehoon Kim +4
Attention mechanism is effective in both focusing the deep learning models on relevant features and interpreting them. However, attentions may be unreliable since the networks that…
Adaptive Network Sparsification with Dependent Variational Beta-Bernoulli Dropout
Juho Lee, Saehoon Kim, Jaehong Yoon +3
While variational dropout approaches have been shown to be effective for network sparsification, they are still suboptimal in the sense that they set the dropout rate for each neur…