26 citations · 35 across the 6 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
math.OC2019★ 1 cited
Scale Invariant Power Iteration
Cheolmin Kim, Youngseok Kim, Diego Klabjan
Power iteration has been generalized to solve many interesting problems in machine learning and statistics. Despite its striking success, theoretical understanding of when and how…
cs.LG2019
Effective Network Compression Using Simulation-Guided Iterative Pruning
Dae-Woong Jeong, Jaehun Kim, Youngseok Kim +2
Existing high-performance deep learning models require very intensive computing. For this reason, it is difficult to embed a deep learning model into a system with limited resource…
stat.ME2019★ 1 cited
Bayesian Model Selection with Graph Structured Sparsity
Youngseok Kim, Chao Gao
We propose a general algorithmic framework for Bayesian model selection. A spike-and-slab Laplacian prior is introduced to model the underlying structural assumption. Using the not…