
Lee Sael
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2020 – today
- 2021
- [j22]Jinhong Jung, Lee Sael
:
Correction to: Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach. Mach. Learn. 110(2): 449 (2021) - [j21]Jinhong Jung, Lee Sael
:
Correction to: Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach. Mach. Learn. 110(3): 619-620 (2021) - [c16]Moonjeong Park, Jun-Gi Jang, Lee Sael:
VEST: Very Sparse Tucker Factorization of Large-Scale Tensors. BigComp 2021: 172-179 - 2020
- [j20]Jinhong Jung, Lee Sael
:
Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach. Mach. Learn. 109(12): 2333-2347 (2020) - [j19]Dongjin Choi, Lee Sael:
SNeCT: Scalable Network Constrained Tucker Decomposition for Multi-Platform Data Profiling. IEEE ACM Trans. Comput. Biol. Bioinform. 17(5): 1785-1796 (2020) - [i10]Jinhong Jung, Lee Sael:
Fast and Accurate Pseudoinverse with Sparse Matrix Reordering and Incremental Approach. CoRR abs/2011.04235 (2020)
2010 – 2019
- 2019
- [j18]Yongsub Lim, In-Jae Yu
, Dongmin Seo, U Kang, Lee Sael:
PS-MCL: parallel shotgun coarsened Markov clustering of protein interaction networks. BMC Bioinform. 20-S(13): 381:1-381:12 (2019) - [j17]Sejoon Oh
, Namyong Park, Jun-Gi Jang, Lee Sael
, U Kang:
High-Performance Tucker Factorization on Heterogeneous Platforms. IEEE Trans. Parallel Distributed Syst. 30(10): 2237-2248 (2019) - [c15]Jaemin Yoo, Lee Sael:
EDiT: Interpreting Ensemble Models via Compact Soft Decision Trees. ICDM 2019: 1438-1443 - [i9]Moonjeong Park, Jun-Gi Jang, Lee Sael:
VeST: Very Sparse Tucker Factorization of Large-Scale Tensors. CoRR abs/1904.02603 (2019) - 2018
- [j16]Jungwoo Lee, Sejoon Oh
, Lee Sael
:
GIFT: Guided and Interpretable Factorization for Tensors with an application to large-scale multi-platform cancer analysis. Bioinform. 34(24): 4151-4158 (2018) - [j15]Lee Sael:
Introduction to Selected Papers from GIW2017. J. Bioinform. Comput. Biol. 16(3): 1802003:1-1802003:2 (2018) - [c14]Sejoon Oh, Namyong Park, Lee Sael, U Kang:
Scalable Tucker Factorization for Sparse Tensors - Algorithms and Discoveries. ICDE 2018: 1120-1131 - [i8]Jungwoo Lee, Sejoon Oh, Lee Sael:
GIFT: Guided and Interpretable Factorization for Tensors - An Application to Large-Scale Multi-platform Cancer Analysis. CoRR abs/1801.02769 (2018) - 2017
- [j14]Jaya Thomas, Lee Sael:
Multi-kernel LS-SVM based integration bio-clinical data analysis and application to ovarian cancer. Int. J. Data Min. Bioinform. 19(2): 150-167 (2017) - [j13]Kijung Shin, Lee Sael, U Kang:
Fully Scalable Methods for Distributed Tensor Factorization. IEEE Trans. Knowl. Data Eng. 29(1): 100-113 (2017) - [c13]Jaya Thomas, Sonia Thomas, Lee Sael:
DP-miRNA: An improved prediction of precursor microRNA using deep learning model. BigComp 2017: 96-99 - [c12]Jinhong Jung, Namyong Park, Lee Sael, U Kang:
BePI: Fast and Memory-Efficient Method for Billion-Scale Random Walk with Restart. SIGMOD Conference 2017: 789-804 - [i7]Quoc Duy Vo, Jaya Thomas, Shinyoung Cho, Pradipta De, Bong Jun Choi, Lee Sael
:
Next Generation Business Intelligence and Analytics: A Survey. CoRR abs/1704.03402 (2017) - [i6]Jaya Thomas, Lee Sael
:
Deep Neural Network Based Precursor microRNA Prediction on Eleven Species. CoRR abs/1704.03834 (2017) - [i5]Sejoon Oh, Namyong Park, Lee Sael, U Kang:
Scalable Tucker Factorization for Sparse Tensors - Algorithms and Discoveries. CoRR abs/1710.02261 (2017) - [i4]Vasundhara Dehiya, Jaya Thomas, Lee Sael:
Prior Knowledge based mutation prioritization towards causal variant finding in rare disease. CoRR abs/1710.03399 (2017) - [i3]Jungwoo Lee, Dongjin Choi, Lee Sael:
CTD: Fast, Accurate, and Interpretable Method for Static and Dynamic Tensor Decompositions. CoRR abs/1710.03608 (2017) - [i2]Jaya Thomas, Sonia Thomas, Lee Sael:
Feature versus Raw Sequence: Deep Learning Comparative Study on Predicting Pre-miRNA. CoRR abs/1710.06798 (2017) - [i1]Dongjin Choi, Lee Sael:
SNeCT: Scalable network constrained Tucker decomposition for integrative multi-platform data analysis. CoRR abs/1711.08095 (2017) - 2016
- [j12]Sungchul Kim, Lee Sael, Hwanjo Yu:
A mutation profile for top-k patient search exploiting Gene-Ontology and orthogonal non-negative matrix factorization. Bioinform. 32(13): 2081 (2016) - [j11]Jinhong Jung, Kijung Shin, Lee Sael, U Kang:
Random Walk with Restart on Large Graphs Using Block Elimination. ACM Trans. Database Syst. 41(2): 12:1-12:43 (2016) - [j10]Inah Jeon, Evangelos E. Papalexakis
, Christos Faloutsos, Lee Sael
, U Kang:
Mining billion-scale tensors: algorithms and discoveries. VLDB J. 25(4): 519-544 (2016) - [c11]Jaya Thomas, Lee Sael:
Maximizing information through multiple kernel-based heterogeneous data integration and applications to ovarian cancer. EDB 2016: 95-98 - [c10]Byungsoo Jeon, Inah Jeon, Lee Sael, U Kang:
SCouT: Scalable coupled matrix-tensor factorization - algorithm and discoveries. ICDE 2016: 811-822 - [c9]Jinhong Jung, Woojeong Jin, Lee Sael, U Kang:
Personalized Ranking in Signed Networks Using Signed Random Walk with Restart. ICDM 2016: 973-978 - 2015
- [j9]Lee Sael
, Inah Jeon, U Kang:
Scalable Tensor Mining. Big Data Res. 2(2): 82-86 (2015) - [j8]Sungchul Kim, Lee Sael
, Hwanjo Yu:
A mutation profile for top-k patient search exploiting Gene-Ontology and orthogonal non-negative matrix factorization. Bioinform. 31(22): 3653-3659 (2015) - [j7]Sungchul Kim, Lee Sael
, Hwanjo Yu:
LMDS-based approach for efficient top-k local ligand-binding site search. Int. J. Data Min. Bioinform. 12(4): 417-433 (2015) - [c8]Jaya Thomas, Lee Sael
:
Overview of integrative analysis methods for heterogeneous data. BigComp 2015: 266-270 - [c7]Kijung Shin, Jinhong Jung, Lee Sael, U Kang:
BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs. SIGMOD Conference 2015: 1571-1585 - 2014
- [c6]Sungchul Kim, Lee Sael
, Hwanjo Yu:
Identifying Cancer Subtypes based on Somatic Mutation Profile. DTMBIO@CIKM 2014: 19-22 - [c5]Dongyeop Kang, Woosang Lim
, Kijung Shin, Lee Sael, U Kang:
Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression. CIKM 2014: 1269-1278 - 2013
- [j6]Sungchul Kim, Lee Sael, Hwanjo Yu:
Efficient protein structure search using indexing methods. BMC Medical Informatics Decis. Mak. 13(S-1): S8 (2013) - [c4]Sungchul Kim, Lee Sael, Hwanjo Yu:
Efficient local ligand-binding site search using landmark mds. DTMBIO 2013: 13-14 - [c3]Darius Coelho, Lee Sael
:
Breast and prostate cancer expression similarity analysis by iterative SVM based ensemble gene selection. DTMBIO 2013: 23-26 - [c2]Sungchul Kim, Lee Sael
, Hwanjo Yu:
Fast protein 3D surface search. ICUIMC 2013: 73 - 2012
- [j5]Lee Sael
, Daisuke Kihara:
Constructing patch-based ligand-binding pocket database for predicting function of proteins. BMC Bioinform. 13(S-2): S7 (2012) - [c1]Sungchul Kim, Lee Sael
, Hwanjo Yu:
Indexing methods for efficient protein 3D surface search. DTMBIO@CIKM 2012: 41-48 - 2010
- [j4]Lee Sael
, Daisuke Kihara:
Improved protein surface comparison and application to low-resolution protein structure data. BMC Bioinform. 11(S-11): S2 (2010) - [j3]Lee Sael
, Daisuke Kihara:
Characterization and Classification of Local Protein Surfaces Using Self-Organizing Map. Int. J. Knowl. Discov. Bioinform. 1(1): 32-47 (2010)
2000 – 2009
- 2009
- [j2]David La, Juan Esquivel-Rodríguez, Vishwesh Venkatraman
, Bin Li, Lee Sael
, Stephen Ueng, Steven Ahrendt, Daisuke Kihara:
3D-SURFER: software for high-throughput protein surface comparison and analysis. Bioinform. 25(21): 2843-2844 (2009) - [j1]Vishwesh Venkatraman
, Yifeng D. Yang, Lee Sael
, Daisuke Kihara
:
Protein-protein docking using region-based 3D Zernike descriptors. BMC Bioinform. 10: 407 (2009)
Coauthor Index

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