1 × Canada
1 × Israel
8 × USA
R.Rosales R.B.Rao O.L.Mangasarian J.G.Dy J.Bi Y.Yan M.Masaeli S.Sandilya M.Salganicoff M.Dundar N.Obuchowski D.P.Naidich S.Yu S.Krishnan C.Dehing-Oberije P.Lambin S.Periaswamy K.Okada T.Kubota
machin (4) classifi (3) support (3) vector (3) learn (3) select (2) linear (2) detect (2) spars (2) lung (2)
Person: Glenn Fung
Wrote 11 papers:
- ICML-2011-YanRFD #learning
- Active Learning from Crowds (YY, RR, GF, JGD), pp. 1161–1168.
- ICML-2010-MasaeliFD #feature model #reduction
- From Transformation-Based Dimensionality Reduction to Feature Selection (MM, GF, JGD), pp. 751–758.
- KDD-2010-YanFDR #classification
- Medical coding classification by leveraging inter-code relationships (YY, GF, JGD, RR), pp. 193–202.
- KDD-2008-YuFRKRDL #analysis #privacy
- Privacy-preserving cox regression for survival analysis (SY, GF, RR, SK, RBR, CDO, PL), pp. 1034–1042.
- 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.
- 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.
- KDD-2006-RosalesF #learning #linear #metric #programming
- Learning sparse metrics via linear programming (RR, GF), pp. 367–373.
- KDD-2005-FungSR #linear
- Rule extraction from linear support vector machines (GF, SS, RBR), pp. 32–40.
- ICML-2004-FungDBR #algorithm #kernel #performance #using
- A fast iterative algorithm for fisher discriminant using heterogeneous kernels (GF, MD, JB, RBR).
- KDD-2001-FungM #classification
- Proximal support vector machine classifiers (GF, OLM), pp. 77–86.
- KDD-2000-FungM #classification
- Data selection for support vector machine classifiers (GF, OLM), pp. 64–70.