`Travelled to:`

1 × Finland

1 × Germany

1 × India

1 × Italy

2 × Australia

5 × USA

`Collaborated with:`

V.Sindhwani W.Chu C.Lin ∅ K.R.K.Murthy C.S.Sundaresan C.J.Ong C.Hsieh K.Chang S.Sundararajan R.C.Weng O.Chapelle K.Duan S.K.Shevade A.N.Poo V.Nair A.Raul S.Khanduja V.Bahirwani S.Sellamanickam S.Herbert S.Dhulipalla M.Shi D.S.Edwin R.Menon L.Shen J.Y.K.Lim H.T.Loh

`Talks about:`

regress (4) scale (4) larg (4) method (3) linear (3) svms (3) dual (3) supervis (2) approach (2) support (2)

## Person: S. Sathiya Keerthi

### DBLP: Keerthi:S=_Sathiya

### Contributed to:

### Wrote 13 papers:

- KDD-2015-NairRKBSKHD #detection #learning #monitoring
- Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues (VN, AR, SK, VB, SS, SSK, SH, SD), pp. 2029–2038.
- ICML-2008-HsiehCLKS #coordination #linear #scalability
- A dual coordinate descent method for large-scale linear SVM (CJH, KWC, CJL, SSK, SS), pp. 408–415.
- KDD-2008-KeerthiSCHL #linear #multi #scalability
- A sequential dual method for large scale multi-class linear svms (SSK, SS, KWC, CJH, CJL), pp. 408–416.
- ICML-2007-LinWK #scalability #trust
- Trust region Newton methods for large-scale logistic regression (CJL, RCW, SSK), pp. 561–568.
- ICML-2006-SindhwaniKC #kernel
- Deterministic annealing for semi-supervised kernel machines (VS, SSK, OC), pp. 841–848.
- SIGIR-2006-SindhwaniK #linear #scalability
- Large scale semi-supervised linear SVMs (VS, SSK), pp. 477–484.
- ICML-2005-ChuK
- New approaches to support vector ordinal regression (WC, SSK), pp. 145–152.
- ICML-2005-Keerthi #classification #effectiveness #feature model
- Generalized LARS as an effective feature selection tool for text classification with SVMs (SSK), pp. 417–424.
- ECIR-2003-ShiEMSLLKO #approach #machine learning
- A Machine Learning Approach for the Curation of Biomedical Literature (MS, DSE, RM, LS, JYKL, HTL, SSK, CJO), pp. 597–604.
- ICML-2002-KeerthiDSP #algorithm #kernel #performance
- A Fast Dual Algorithm for Kernel Logistic Regression (SSK, KD, SKS, ANP), pp. 299–306.
- ICML-2001-ChuKO #framework
- A Unified Loss Function in Bayesian Framework for Support Vector Regression (WC, SSK, CJO), pp. 51–58.
- ICDAR-1999-MurthyK #information management
- Context Filters for Document-based Information Filtering (KRKM, SSK), pp. 709–712.
- ICDAR-1999-SundaresanK #case study #recognition
- A Study of Representations for Pen based Handwriting Recognition of Tamil Characters (CSS, SSK), pp. 422–425.