BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
Travelled to:
1 × China
1 × France
3 × USA
Collaborated with:
S.Agarwal P.Kar P.Jain S.Satheesh Pramala Senthil H.G.Ramaswamy A.Saha A.Agarwal S.Kalyanakrishnan A.K.Menon S.Chawla
Talks about:
class (4) optim (3) base (3) algorithm (2) perform (2) partial (2) consist (2) measur (2) binari (2) auc (2)

Person: Harikrishna Narasimhan

DBLP DBLP: Narasimhan:Harikrishna

Contributed to:

ICML 20152015
ICML c2 20142014
ICML c1 20132013
ICML c3 20132013
KDD 20132013
FDG 20092009

Wrote 8 papers:

ICML-2015-KarN0 #precise
Surrogate Functions for Maximizing Precision at the Top (PK, HN, PJ), pp. 189–198.
ICML-2015-NarasimhanK0 #metric #optimisation #performance
Optimizing Non-decomposable Performance Measures: A Tale of Two Classes (HN, PK, PJ), pp. 199–208.
ICML-2015-NarasimhanRS0 #algorithm #consistency #metric #multi #performance
Consistent Multiclass Algorithms for Complex Performance Measures (HN, HGR, AS, SA), pp. 2398–2407.
ICML-c2-2014-0001NKA #estimation #probability
GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare (AA, HN, SK, SA), pp. 1989–1997.
ICML-c1-2013-NarasimhanA #approach #optimisation
A Structural SVM Based Approach for Optimizing Partial AUC (HN, SA), pp. 516–524.
ICML-c3-2013-MenonNAC #algorithm #classification #consistency #on the #statistics
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance (AKM, HN, SA, SC), pp. 603–611.
KDD-2013-NarasimhanA #bound #named #optimisation
SVMpAUCtight: a new support vector method for optimizing partial AUC based on a tight convex upper bound (HN, SA), pp. 167–175.
FDG-2009-SatheeshNS #evolution #game studies
Evolving player-specific content for level based arcade games (SS, HN, PS), pp. 329–330.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.