12 citations · 46 across the 10 of their papers we have counts for
11 papers
Transition Matrix Representation of Trees with Transposed Convolutions
Jaemin Yoo, Lee Sael
How can we effectively find the best structures in tree models? Tree models have been favored over complex black box models in domains where interpretability is crucial for making…
Fast and Accurate Pseudoinverse with Sparse Matrix Reordering and Incremental Approach
Jinhong Jung, Lee Sael
How can we compute the pseudoinverse of a sparse feature matrix efficiently and accurately for solving optimization problems? A pseudoinverse is a generalization of a matrix invers…
VeST: Very Sparse Tucker Factorization of Large-Scale Tensors
Moonjeong Park, Jun-Gi Jang, Lee Sael
Given a large tensor, how can we decompose it to sparse core tensor and factor matrices such that it is easier to interpret the results? How can we do this without reducing the acc…
GIFT: Guided and Interpretable Factorization for Tensors - An Application to Large-Scale Multi-platform Cancer Analysis
Jungwoo Lee, Sejoon Oh, Lee Sael
Given multi-platform genome data with prior knowledge of functional gene sets, how can we extract interpretable latent relationships between patients and genes? More specifically,…
SNeCT: Scalable network constrained Tucker decomposition for integrative multi-platform data analysis
Dongjin Choi, Lee Sael
Motivation: How do we integratively analyze large-scale multi-platform genomic data that are high dimensional and sparse? Furthermore, how can we incorporate prior knowledge, such…
Feature versus Raw Sequence: Deep Learning Comparative Study on Predicting Pre-miRNA
Jaya Thomas, Sonia Thomas, Lee Sael
Should we input known genome sequence features or input sequence itself in deep learning framework? As deep learning more popular in various applications, researchers often come to…