Seyoung Kim

	2012
16		Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing: Smoothing Proximal Gradient Method for General Structured Sparse Learning CoRR abs/1202.3708: (2012)
15		Kyung-Ah Sohn, Seyoung Kim: Joint Estimation of Structured Sparsity and Output Structure in Multiple-Output Regression via Inverse-Covariance Regularization. Journal of Machine Learning Research - Proceedings Track 22: 1081-1089 (2012)
	2011
14		Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing: Smoothing Proximal Gradient Method for General Structured Sparse Learning. UAI 2011: 105-114
	2010
13		Seyoung Kim, Eric P. Xing: Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity. ICML 2010: 543-550
12		Kriti Puniyani, Seyoung Kim, Eric P. Xing: Multi-population GWA mapping via multi-task regularized regression. Bioinformatics [ISMB] 26(12): 208-216 (2010)
11		Xi Chen, Seyoung Kim, Qihang Lin, Jaime G. Carbonell, Eric P. Xing: Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso CoRR abs/1005.3579: (2010)
10		Xi Chen, Qihang Lin, Seyoung Kim, Javier Peña, Jaime G. Carbonell, Eric P. Xing: An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity CoRR abs/1005.4717: (2010)
9		Seyoung Kim, Padhraic Smyth, Hal S. Stern: A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data. IEEE Trans. Med. Imaging 29(6): 1260-1274 (2010)
	2009
8		Xiaolin Yang, Seyoung Kim, Eric P. Xing: Heterogeneous multitask learning with joint sparsity constraints. NIPS 2009: 2151-2159
7		Seyoung Kim, Kyung-Ah Sohn, Eric P. Xing: A multivariate regression approach to association analysis of a quantitative trait network. Bioinformatics 25(12): (2009)
	2008
6		Seyoung Kim, Eric P. Xing: Feature Selection via Block-Regularized Regression. UAI 2008: 325-332
	2006
5		Seyoung Kim, Padhraic Smyth, Hal S. Stern: A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data. MICCAI (2) 2006: 217-224
4		Seyoung Kim, Padhraic Smyth: Hierarchical Dirichlet Processes with Random Effects. NIPS 2006: 697-704
3		Seyoung Kim, Padhraic Smyth: Segmental Hidden Markov Models with Random Effects for Waveform Modeling. Journal of Machine Learning Research 7: 945-969 (2006)
	2005
2		Seyoung Kim, Padhraic Smyth, Hal S. Stern, Jessica A. Turner: Parametric Response Surface Models for Analysis of Multi-site fMRI Data. MICCAI 2005: 352-359
	2004
1		Seyoung Kim, Padhraic Smyth, Stefan Luther: Modeling Waveform Shapes with Random E ects Segmental Hidden Markov Models. UAI 2004: 309-316

Coauthor Index

1	Jaime G. Carbonell	[10] [11] [14] [16]
2	Xi Chen	[10] [11] [14] [16]
3	Qihang Lin	[10] [11] [14] [16]
4	Stefan Luther	[1]
5	Javier Peña	[10]
6	Kriti Puniyani	[12]
7	Padhraic Smyth	[1] [2] [3] [4] [5] [9]
8	Kyung-Ah Sohn	[7] [15]
9	Hal S. Stern	[2] [5] [9]
10	Jessica A. Turner	[2]
11	Eric P. Xing	[6] [7] [8] [10] [11] [12] [13] [14] [16]
12	Xiaolin Yang	[8]

Colors in the list of coauthors

Last update Fri Jun 1 15:44:53 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page