Travelled to:1 × Australia
1 × Canada
1 × Finland
1 × France
7 × USA
Collaborated with:J.Sun K.P.Bennett R.B.Rao T.Xu G.Fung ∅ M.Dundar H.R.Kranzler K.Yu V.Tresp T.Zhang M.Salganicoff J.Lu V.C.Raykar B.Krishnapuram N.Obuchowski D.P.Naidich J.Ye T.Xiong Q.Li R.Janardan V.Cherkassky C.Kambhamettu S.Periaswamy K.Okada T.Kubota
Talks about:learn (4) featur (3) discrimin (2) select (2) linear (2) kernel (2) detect (2) spars (2) multi (2) lung (2)
Person: Jinbo Bi
DBLP: Bi:Jinbo
Contributed to:
2015
2015201320082007
200620062006200420042003Wrote 12 papers:
- ICML-2015-SunLXB #clustering #multi
- Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization (JS, JL, TX, JB), pp. 757–766.
- KDD-2015-XuSB #learning #predict
- Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction (TX, JS, JB), pp. 1345–1354.
- KDD-2013-SunBK #identification #optimisation #polynomial
- Quadratic optimization to identify highly heritable quantitative traits from complex phenotypic features (JS, JB, HRK), pp. 811–819.
- ICML-2008-RaykarKBDR #automation #feature model #induction #learning #multi
- Bayesian multiple instance learning: automatic feature selection and inductive transfer (VCR, BK, JB, MD, RBR), pp. 808–815.
- KDD-2007-RaoBFSON #detection #machine learning #named
- LungCAD: a clinically approved, machine learning system for lung cancer detection (RBR, JB, GF, MS, NO, DPN), pp. 1033–1037.
- CIKM-2006-YeXLJBCK #analysis #linear #performance
- Efficient model selection for regularized linear discriminant analysis (JY, TX, QL, RJ, JB, VC, CK), pp. 532–539.
- ICML-2006-YuBT #design #learning
- Active learning via transductive experimental design (KY, JB, VT), pp. 1081–1088.
- KDD-2006-BiPOKFSR #classification #detection #symmetry
- Computer aided detection via asymmetric cascade of sparse hyperplane classifiers (JB, SP, KO, TK, GF, MS, RBR), pp. 837–844.
- ICML-2004-FungDBR #algorithm #kernel #performance #using
- A fast iterative algorithm for fisher discriminant using heterogeneous kernels (GF, MD, JB, RBR).
- KDD-2004-BiZB #kernel
- Column-generation boosting methods for mixture of kernels (JB, TZ, KPB), pp. 521–526.
- ICML-2003-Bi #multi #programming
- Multi-Objective Programming in SVMs (JB), pp. 35–42.
- ICML-2003-BiB #fault
- Regression Error Characteristic Curves (JB, KPB), pp. 43–50.