`Travelled to:`

1 × China

1 × France

1 × Switzerland

6 × USA

`Collaborated with:`

S.Arora M.Ester J.Zou W.Jin A.Moitra Q.Huang S.M.Kakade F.Moser R.Frostig S.Kakade A.Sidford A.Bhaskara T.Ma R.Kannan I.Davidson Z.Hu D.Chan O.Gershony T.Hesterberg D.Lambert Y.Halpern D.M.Mimno D.Sontag Y.Wu M.Zhu

`Talks about:`

algorithm (3) provabl (3) cluster (3) learn (3) guarante (2) matrix (2) factor (2) model (2) data (2) new (2)

## Person: Rong Ge

### DBLP: Ge:Rong

### Contributed to:

### Wrote 11 papers:

- ICML-2015-FrostigGKS #algorithm #approximate #empirical #named #performance #probability
- Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization (RF, RG, SK, AS), pp. 2540–2548.
- ICML-2015-GeZ #matrix
- Intersecting Faces: Non-negative Matrix Factorization With New Guarantees (RG, JZ), pp. 2295–2303.
- STOC-2015-GeHK #learning
- Learning Mixtures of Gaussians in High Dimensions (RG, QH, SMK), pp. 761–770.
- ICML-c1-2014-AroraBGM #bound #learning
- Provable Bounds for Learning Some Deep Representations (SA, AB, RG, TM), pp. 584–592.
- ICML-c2-2013-AroraGHMMSWZ #algorithm #modelling #topic
- A Practical Algorithm for Topic Modeling with Provable Guarantees (SA, RG, YH, DMM, AM, DS, YW, MZ), pp. 280–288.
- STOC-2012-AroraGKM #matrix
- Computing a nonnegative matrix factorization — provably (SA, RG, RK, AM), pp. 145–162.
- ICALP-v1-2011-AroraG #algorithm #fault #learning
- New Algorithms for Learning in Presence of Errors (SA, RG), pp. 403–415.
- KDD-2010-ChanGGHL #modelling #online #pipes and filters #scalability
- Evaluating online ad campaigns in a pipeline: causal models at scale (DC, RG, OG, TH, DL), pp. 7–16.
- KDD-2007-GeEJD #clustering #constraints
- Constraint-driven clustering (RG, ME, WJ, ID), pp. 320–329.
- KDD-2007-MoserGE #analysis #clustering #specification
- Joint cluster analysis of attribute and relationship data withouta-priori specification of the number of clusters (FM, RG, ME), pp. 510–519.
- KDD-2004-EsterGJH #data mining #mining #problem #segmentation
- A microeconomic data mining problem: customer-oriented catalog segmentation (ME, RG, WJ, ZH), pp. 557–562.