`Travelled to:`

3 × China

5 × USA

`Collaborated with:`

H.Huang H.Wang C.H.Q.Ding Y.Huang J.Yuan X.Wang D.Wang M.Qian C.Zhang X.Cai J.Huang Y.Tu D.Luo

`Talks about:`

learn (4) cluster (3) robust (3) linear (3) discrimin (2) supervis (2) regress (2) analysi (2) multi (2) adapt (2)

## Person: Feiping Nie

### DBLP: Nie:Feiping

### Contributed to:

### Wrote 12 papers:

- ICML-c2-2014-NieHH #linear
- Linear Time Solver for Primal SVM (FN, YH, HH), pp. 505–513.
- ICML-c2-2014-NieYH #analysis #component #robust
- Optimal Mean Robust Principal Component Analysis (FN, JY, HH), pp. 1062–1070.
- ICML-c2-2014-WangNH #distance #learning #metric #robust
- Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization (HW, FN, HH), pp. 1836–1844.
- KDD-2014-NieWH #adaptation #clustering
- Clustering and projected clustering with adaptive neighbors (FN, XW, HH), pp. 977–986.
- KDD-2014-WangNH #adaptation #induction #learning #scalability
- Large-scale adaptive semi-supervised learning via unified inductive and transductive model (DW, FN, HH), pp. 482–491.
- ICML-c3-2013-WangNH #learning #robust #self
- Robust and Discriminative Self-Taught Learning (HW, FN, HH), pp. 298–306.
- ICML-c3-2013-WangNH13a #clustering #learning #multi
- Multi-View Clustering and Feature Learning via Structured Sparsity (HW, FN, HH), pp. 352–360.
- KDD-2013-CaiQ #analysis #linear #on the #rank
- On the equivalent of low-rank linear regressions and linear discriminant analysis based regressions (XC, CHQD, FN, HH), pp. 1124–1132.
- CIKM-2012-HuangNHT #network #predict #social #trust
- Trust prediction via aggregating heterogeneous social networks (JH, FN, HH, YCT), pp. 1774–1778.
- ICML-2011-LuoDNH #graph
- Cauchy Graph Embedding (DL, CHQD, FN, HH), pp. 553–560.
- SIGIR-2011-WangHND #classification #information management #matrix #using #web
- Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization (HW, HH, FN, CHQD), pp. 933–942.
- CIKM-2009-QianNZ #multi #performance
- Efficient multi-class unlabeled constrained semi-supervised SVM (MQ, FN, CZ), pp. 1665–1668.