Shivani Agarwal

According to our database1, Shivani Agarwal authored at least 50 papers between 2002 and 2018.

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Bibliography

2018
Accelerated Spectral Ranking.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Support Vector Algorithms for Optimizing the Partial Area under the ROC Curve.
Neural Computation, 2017

Learning with Limited Rounds of Adaptivity: Coin Tossing, Multi-Armed Bandits, and Ranking from Pairwise Comparisons.
Proceedings of the 30th Conference on Learning Theory, 2017

Predicting Startup Crowdfunding Success through Longitudinal Social Engagement Analysis.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016
Convex Calibration Dimension for Multiclass Loss Matrices.
Journal of Machine Learning Research, 2016

Support Vector Algorithms for Optimizing the Partial Area Under the ROC Curve.
CoRR, 2016

Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Automated Mechanism Design without Money via Machine Learning.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

On Ranking and Choice Models.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

When can we rank well from comparisons of \(O(n\log(n))\) non-actively chosen pairs?
Proceedings of the 29th Conference on Learning Theory, 2016

On the Computational Hardness of Manipulating Pairwise Voting Rules.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

2015
Consistent Algorithms for Multiclass Classification with a Reject Option.
CoRR, 2015

Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics.
CoRR, 2015

Bayes Optimal Feature Selection for Supervised Learning with General Performance Measures.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Convex Calibrated Surrogates for Hierarchical Classification.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Consistent Multiclass Algorithms for Complex Performance Measures.
Proceedings of the 32nd International Conference on Machine Learning, 2015

On Consistent Surrogate Risk Minimization and Property Elicitation.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Surrogate regret bounds for bipartite ranking via strongly proper losses.
Journal of Machine Learning Research, 2014

Convex Calibration Dimension for Multiclass Loss Matrices.
CoRR, 2014

Online Decision-Making in General Combinatorial Spaces.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Score Systems for Patient Mortality Prediction in Intensive Care Units via Orthogonal Matching Pursuit.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data.
Proceedings of the 31th International Conference on Machine Learning, 2014

GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare.
Proceedings of the 31th International Conference on Machine Learning, 2014

On the Consistency of Output Code Based Learning Algorithms for Multiclass Learning Problems.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

SVMpAUCtight: a new support vector method for optimizing partial AUC based on a tight convex upper bound.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

A Structural SVM Based Approach for Optimizing Partial AUC.
Proceedings of the 30th International Conference on Machine Learning, 2013

On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance.
Proceedings of the 30th International Conference on Machine Learning, 2013

Surrogate Regret Bounds for the Area Under the ROC Curve via Strongly Proper Losses.
Proceedings of the COLT 2013, 2013

2012
A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses
CoRR, 2012

Classification Calibration Dimension for General Multiclass Losses.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
The Infinite Push: A New Support Vector Ranking Algorithm that Directly Optimizes Accuracy at the Absolute Top of the List.
Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

2010
Learning to rank on graphs.
Machine Learning, 2010

Ranking Chemical Structures for Drug Discovery: A New Machine Learning Approach.
Journal of Chemical Information and Modeling, 2010

Maximum Margin Ranking Algorithms for Information Retrieval.
Proceedings of the Advances in Information Retrieval, 2010

2009
Generalization Bounds for Ranking Algorithms via Algorithmic Stability.
Journal of Machine Learning Research, 2009

2008
Generalization Bounds for Some Ordinal Regression Algorithms.
Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

2006
Ranking on graph data.
Proceedings of the Machine Learning, 2006

2005
Generalization Bounds for the Area Under the ROC Curve.
Journal of Machine Learning Research, 2005

Learnability of Bipartite Ranking Functions.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

Stability and Generalization of Bipartite Ranking Algorithms.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

A Uniform Convergence Bound for the Area Under the ROC Curve.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Learning to Detect Objects in Images via a Sparse, Part-Based Representation.
IEEE Trans. Pattern Anal. Mach. Intell., 2004

A Large Deviation Bound for the Area Under the ROC Curve.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2002
Fusion of Global and Local Information for Object Detection.
Proceedings of the 16th International Conference on Pattern Recognition, 2002

Learning a Sparse Representation for Object Detection.
Proceedings of the Computer Vision, 2002


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