Harikrishna Narasimhan

According to our database, Harikrishna Narasimhan authored at least 57 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Optimal Auctions through Deep Learning: Advances in Differentiable Economics.

Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath

J. ACM, 2024

Metric-aware LLM inference.

Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar

CoRR, 2024

2023

Learning to reject meets OOD detection: Are all abstentions created equal?

Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar

CoRR, 2023

Robust distillation for worst-class performance: on the interplay between teacher and student objectives.

Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon

Proceedings of the Uncertainty in Artificial Intelligence, 2023

When Does Confidence-Based Cascade Deferral Suffice?

Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distributionally Robust Post-hoc Classifiers under Prior Shifts.

Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Consistent Multiclass Algorithms for Complex Metrics and Constraints.

Harikrishna Narasimhan, Harish G. Ramaswamy, Shiv Kumar Tavker, Drona Khurana, Praneeth Netrapalli, Shivani Agarwal

CoRR, 2022

Robust Distillation for Worst-class Performance.

Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon

CoRR, 2022

Quadratic metric elicitation for fairness and beyond.

Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Post-hoc estimators for learning to defer to an expert.

Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Churn Reduction via Distillation.

Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Distilling Double Descent.

Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou

CoRR, 2021

Optimal auctions through deep learning.

Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath

Commun. ACM, 2021

Training Over-parameterized Models with Non-decomposable Objectives.

Harikrishna Narasimhan, Aditya Krishna Menon

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Implicit rate-constrained optimization of non-decomposable objectives.

Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter

Proceedings of the 38th International Conference on Machine Learning, 2021

Optimizing Black-box Metrics with Iterative Example Weighting.

Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Quadratic Metric Elicitation with Application to Fairness.

Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo

CoRR, 2020

Robust Optimization for Fairness with Noisy Protected Groups.

Serena Lutong Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Consistent Plug-in Classifiers for Complex Objectives and Constraints.

Shiv Kumar Tavker, Harish Guruprasad Ramaswamy, Harikrishna Narasimhan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Approximate Heavily-Constrained Learning with Lagrange Multiplier Models.

Harikrishna Narasimhan, Andrew Cotter, Yichen Zhou, Serena Lutong Wang, Wenshuo Guo

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fair Performance Metric Elicitation.

Gaurush Hiranandani, Harikrishna Narasimhan, Oluwasanmi Koyejo

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimizing Black-box Metrics with Adaptive Surrogates.

Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya R. Gupta

Proceedings of the 37th International Conference on Machine Learning, 2020

Pairwise Fairness for Ranking and Regression.

Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Serena Lutong Wang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Optimizing Generalized Rate Metrics through Game Equilibrium.

Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta

CoRR, 2019

Optimizing Generalized Rate Metrics with Three Players.

Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Making Stochastic Classifiers Deterministic.

Andrew Cotter, Maya R. Gupta, Harikrishna Narasimhan

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Metric-Optimized Example Weights.

Sen Zhao, Mahdi Milani Fard, Harikrishna Narasimhan, Maya R. Gupta

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Deep Learning for Multi-Facility Location Mechanism Design.

Noah Golowich, Harikrishna Narasimhan, David C. Parkes

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Deep Learning for Revenue-Optimal Auctions with Budgets.

Zhe Feng, Harikrishna Narasimhan, David C. Parkes

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Learning with Complex Loss Functions and Constraints.

Harikrishna Narasimhan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Support Vector Algorithms for Optimizing the Partial Area under the ROC Curve.

Harikrishna Narasimhan, Shivani Agarwal

Neural Comput., 2017

Optimal Auctions through Deep Learning.

Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes

CoRR, 2017

2016

Stochastic Optimization Techniques for Quantification Performance Measures.

Shuai Li, Harikrishna Narasimhan, Purushottam Kar, Sanjay Chawla, Fabrizio Sebastiani

CoRR, 2016

A General Statistical Framework for Designing Strategy-proof Assignment Mechanisms.

Harikrishna Narasimhan, David C. Parkes

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Online Optimization Methods for the Quantification Problem.

Purushottam Kar, Shuai Li, Harikrishna Narasimhan, Sanjay Chawla, Fabrizio Sebastiani

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Automated Mechanism Design without Money via Machine Learning.

Harikrishna Narasimhan, Shivani Agarwal, David C. Parkes

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Optimizing the Multiclass F-Measure via Biconcave Programming.

Harikrishna Narasimhan, Weiwei Pan, Purushottam Kar, Pavlos Protopapas, Harish G. Ramaswamy

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015

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

Harish G. Ramaswamy, Harikrishna Narasimhan, Shivani Agarwal

CoRR, 2015

Bayes Optimal Feature Selection for Supervised Learning with General Performance Measures.

C. G. Saneem Ahmed, Harikrishna Narasimhan, Shivani Agarwal

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Learnability of Influence in Networks.

Harikrishna Narasimhan, David C. Parkes, Yaron Singer

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Consistent Multiclass Algorithms for Complex Performance Measures.

Harikrishna Narasimhan, Harish G. Ramaswamy, Aadirupa Saha, Shivani Agarwal

Proceedings of the 32nd International Conference on Machine Learning, 2015

Optimizing Non-decomposable Performance Measures: A Tale of Two Classes.

Harikrishna Narasimhan, Purushottam Kar, Prateek Jain

Proceedings of the 32nd International Conference on Machine Learning, 2015

Surrogate Functions for Maximizing Precision at the Top.

Purushottam Kar, Harikrishna Narasimhan, Prateek Jain

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures.

Harikrishna Narasimhan, Rohit Vaish, Shivani Agarwal

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Online and Stochastic Gradient Methods for Non-decomposable Loss Functions.

Purushottam Kar, Harikrishna Narasimhan, Prateek Jain

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.

Aadirupa Saha, Chandrahas Dewangan, Harikrishna Narasimhan, Sriram Sampath, Shivani Agarwal

Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare.

Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan, Shivani Agarwal

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation.

Harikrishna Narasimhan, Shivani Agarwal

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

SVM_pAUC^tight: a new support vector method for optimizing partial AUC based on a tight convex upper bound.

Harikrishna Narasimhan, Shivani Agarwal

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

A Structural SVM Based Approach for Optimizing Partial AUC.

Harikrishna Narasimhan, Shivani Agarwal

Proceedings of the 30th International Conference on Machine Learning, 2013

On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance.

Aditya Krishna Menon, Harikrishna Narasimhan, Shivani Agarwal, Sanjay Chawla

Proceedings of the 30th International Conference on Machine Learning, 2013

2010

Towards a Cooperative Defense Model Against Network Security Attacks.

Harikrishna Narasimhan, Venkatanathan Varadarajan, C. Pandu Rangan

Proceedings of the 9th Annual Workshop on the Economics of Information Security, 2010

Automatic summarization of cricket video events using genetic algorithm.

Harikrishna Narasimhan, Sanjeev Satheesh, Dinesh Sriram

Proceedings of the Genetic and Evolutionary Computation Conference, 2010

2009

Game Theoretic Resistance to Denial of Service Attacks Using Hidden Difficulty Puzzles.

Harikrishna Narasimhan, Venkatanathan Varadarajan, C. Pandu Rangan

IACR Cryptol. ePrint Arch., 2009

A Randomized Iterative Improvement Algorithm for Photomosaic Generation.

Harikrishna Narasimhan, Sanjeev Satheesh

Proceedings of the World Congress on Nature & Biologically Inspired Computing, 2009

Parallel Artificial Bee Colony (PABC) Algorithm.

Harikrishna Narasimhan

Proceedings of the World Congress on Nature & Biologically Inspired Computing, 2009

Evolving player-specific content for level based arcade games.

Sanjeev Satheesh, Harikrishna Narasimhan, Pramala Senthil

Proceedings of the 4th International Conference on Foundations of Digital Games, 2009