Travelled to:
1 × Canada
1 × France
1 × United Kingdom
2 × China
3 × USA
Collaborated with:
H.Narasimhan A.Rajkumar H.G.Ramaswamy M.Collins A.Tewari A.Garg T.S.Huang A.Saha S.Ghoshal L.Lim A.Agarwal S.Kalyanakrishnan A.K.Menon S.Chawla
Talks about:
algorithm (4) class (3) rank (3) statist (2) partial (2) pairwis (2) consist (2) classif (2) inform (2) convex (2)
Person: Shivani Agarwal
DBLP: Agarwal:Shivani
Contributed to:
Wrote 10 papers:
- ICML-2015-NarasimhanRS0 #algorithm #consistency #metric #multi #performance
- Consistent Multiclass Algorithms for Complex Performance Measures (HN, HGR, AS, SA), pp. 2398–2407.
- ICML-2015-RajkumarGL0 #probability #ranking #set
- Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top (AR, SG, LHL, SA), pp. 665–673.
- ICML-2015-RamaswamyT0 #classification
- Convex Calibrated Surrogates for Hierarchical Classification (HGR, AT, SA), pp. 1852–1860.
- ICML-c1-2014-RajkumarA #algorithm #convergence #rank #statistics
- A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data (AR, SA), pp. 118–126.
- 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.
- ECIR-2010-AgarwalC #algorithm #information retrieval #ranking
- Maximum Margin Ranking Algorithms for Information Retrieval (SA, MC), pp. 332–343.
- ICPR-v3-2002-GargAH #detection #information management
- Fusion of Global and Local Information for Object Detection (AG, SA, TSH), p. 723–?.