Harikrishna Narasimhan

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 63

Top Topics

Stochastic Gradient

Top Venues

Publications

Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath
Optimal Auctions through Deep Learning: Advances in Differentiable Economics. J. ACM 71 (1) (2024)
Congchao Wang, Sean Augenstein, Keith Rush, Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Aditya Krishna Menon, Alec Go
Cascade-Aware Training of Language Models. CoRR (2024)
Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar
Faster Cascades via Speculative Decoding. CoRR (2024)
Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar
Metric-aware LLM inference. CoRR (2024)
Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Language Model Cascades: Token-level uncertainty and beyond. CoRR (2024)
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
Plugin estimators for selective classification with out-of-distribution detection. ICLR (2024)
Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Language Model Cascades: Token-Level Uncertainty And Beyond. ICLR (2024)
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar
Learning to Reject Meets Long-tail Learning. ICLR (2024)
Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
When Does Confidence-Based Cascade Deferral Suffice? NeurIPS (2023)
Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar
Distributionally Robust Post-hoc Classifiers under Prior Shifts. ICLR (2023)
Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar
When Does Confidence-Based Cascade Deferral Suffice? CoRR (2023)
Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar
Distributionally Robust Post-hoc Classifiers under Prior Shifts. CoRR (2023)
Serena Lutong Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon
Robust distillation for worst-class performance: on the interplay between teacher and student objectives. UAI (2023)
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
Learning to reject meets OOD detection: Are all abstentions created equal? CoRR (2023)
Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
Post-hoc estimators for learning to defer to an expert. NeurIPS (2022)
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo
Quadratic metric elicitation for fairness and beyond. UAI (2022)
Serena Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon
Robust Distillation for Worst-class Performance. CoRR (2022)
Harikrishna Narasimhan, Harish G. Ramaswamy, Shiv Kumar Tavker, Drona Khurana, Praneeth Netrapalli, Shivani Agarwal
Consistent Multiclass Algorithms for Complex Metrics and Constraints. CoRR (2022)
Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
Churn Reduction via Distillation. ICLR (2022)
Gaurush Hiranandani, Jatin Mathur, Oluwasanmi Koyejo, Mahdi Milani Fard, Harikrishna Narasimhan
Optimizing Black-box Metrics with Iterative Example Weighting. CoRR (2021)
Harikrishna Narasimhan, Aditya Krishna Menon
Training Over-parameterized Models with Non-decomposable Objectives. NeurIPS (2021)
Harikrishna Narasimhan, Aditya Krishna Menon
Training Over-parameterized Models with Non-decomposable Objectives. CoRR (2021)
Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou
Distilling Double Descent. CoRR (2021)
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Implicit Rate-Constrained Optimization of Non-decomposable Objectives. CoRR (2021)
Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
Churn Reduction via Distillation. CoRR (2021)
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo
Optimizing Black-box Metrics with Iterative Example Weighting. ICML (2021)
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath
Optimal auctions through deep learning. Commun. ACM 64 (8) (2021)
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Implicit rate-constrained optimization of non-decomposable objectives. ICML (2021)
Gaurush Hiranandani, Harikrishna Narasimhan, Oluwasanmi Koyejo
Fair Performance Metric Elicitation. CoRR (2020)
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo
Quadratic Metric Elicitation with Application to Fairness. CoRR (2020)
Shiv Kumar Tavker, Harish Guruprasad Ramaswamy, Harikrishna Narasimhan
Consistent Plug-in Classifiers for Complex Objectives and Constraints. NeurIPS (2020)
Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya R. Gupta
Optimizing Black-box Metrics with Adaptive Surrogates. CoRR (2020)
Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Serena Wang
Pairwise Fairness for Ranking and Regression. AAAI (2020)
Serena Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan
Robust Optimization for Fairness with Noisy Protected Groups. CoRR (2020)
Serena Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan
Robust Optimization for Fairness with Noisy Protected Groups. NeurIPS (2020)
Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya R. Gupta
Optimizing Black-box Metrics with Adaptive Surrogates. ICML (2020)
Gaurush Hiranandani, Harikrishna Narasimhan, Oluwasanmi Koyejo
Fair Performance Metric Elicitation. NeurIPS (2020)
Harikrishna Narasimhan, Andrew Cotter, Yichen Zhou, Serena Wang, Wenshuo Guo
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models. NeurIPS (2020)
Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta
Optimizing Generalized Rate Metrics with Three Players. NeurIPS (2019)
Sen Zhao, Mahdi Milani Fard, Harikrishna Narasimhan, Maya R. Gupta
Metric-Optimized Example Weights. ICML (2019)
Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta
Optimizing Generalized Rate Metrics through Game Equilibrium. CoRR (2019)
Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Serena Wang
Pairwise Fairness for Ranking and Regression. CoRR (2019)
Andrew Cotter, Maya R. Gupta, Harikrishna Narasimhan
On Making Stochastic Classifiers Deterministic. NeurIPS (2019)
Paul Duetting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath
Optimal Auctions through Deep Learning. ICML (2019)
Noah Golowich, Harikrishna Narasimhan, David C. Parkes
Deep Learning for Multi-Facility Location Mechanism Design. IJCAI (2018)
Harikrishna Narasimhan
Learning with Complex Loss Functions and Constraints. AISTATS (2018)
Zhe Feng, Harikrishna Narasimhan, David C. Parkes
Deep Learning for Revenue-Optimal Auctions with Budgets. AAMAS (2018)
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes
Optimal Auctions through Deep Learning. CoRR (2017)
Harikrishna Narasimhan, Shivani Agarwal
Support Vector Algorithms for Optimizing the Partial Area under the ROC Curve. Neural Comput. 29 (7) (2017)
Harikrishna Narasimhan, Shivani Agarwal
Support Vector Algorithms for Optimizing the Partial Area Under the ROC Curve. CoRR (2016)
Shuai Li, Harikrishna Narasimhan, Purushottam Kar, Sanjay Chawla, Fabrizio Sebastiani
Stochastic Optimization Techniques for Quantification Performance Measures. CoRR (2016)
Harikrishna Narasimhan, Weiwei Pan, Purushottam Kar, Pavlos Protopapas, Harish G. Ramaswamy
Optimizing the Multiclass F-Measure via Biconcave Programming. ICDM (2016)
Purushottam Kar, Shuai Li, Harikrishna Narasimhan, Sanjay Chawla, Fabrizio Sebastiani
Online Optimization Methods for the Quantification Problem. KDD (2016)
Harikrishna Narasimhan, Shivani Agarwal, David C. Parkes
Automated Mechanism Design without Money via Machine Learning. IJCAI (2016)
Harikrishna Narasimhan, David C. Parkes
A General Statistical Framework for Designing Strategy-proof Assignment Mechanisms. UAI (2016)
Harish G. Ramaswamy, Harikrishna Narasimhan, Shivani Agarwal
Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics. CoRR (2015)
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
Surrogate Functions for Maximizing Precision at the Top. ICML (2015)
Harikrishna Narasimhan, Purushottam Kar, Prateek Jain
Optimizing Non-decomposable Performance Measures: A Tale of Two Classes. ICML (2015)
C. G. Saneem Ahmed, Harikrishna Narasimhan, Shivani Agarwal
Bayes Optimal Feature Selection for Supervised Learning with General Performance Measures. UAI (2015)
Harikrishna Narasimhan, Purushottam Kar, Prateek Jain
Optimizing Non-decomposable Performance Measures: A Tale of Two Classes. CoRR (2015)
Harikrishna Narasimhan, David C. Parkes, Yaron Singer
Learnability of Influence in Networks. NIPS (2015)
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
Surrogate Functions for Maximizing Precision at the Top. CoRR (2015)
Harikrishna Narasimhan, Harish G. Ramaswamy, Aadirupa Saha, Shivani Agarwal
Consistent Multiclass Algorithms for Complex Performance Measures. ICML (2015)
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
Online and Stochastic Gradient Methods for Non-decomposable Loss Functions. CoRR (2014)
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
Online and Stochastic Gradient Methods for Non-decomposable Loss Functions. NIPS (2014)
Harikrishna Narasimhan, Rohit Vaish, Shivani Agarwal
On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures. NIPS (2014)
Aadirupa Saha, Chandrahas Dewangan, Harikrishna Narasimhan, Sriram Sampath, Shivani Agarwal
Learning Score Systems for Patient Mortality Prediction in Intensive Care Units via Orthogonal Matching Pursuit. ICMLA (2014)
Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan, Shivani Agarwal
GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare. ICML (2014)
Harikrishna Narasimhan, Shivani Agarwal
: a new support vector method for optimizing partial AUC based on a tight convex upper bound. KDD (2013)
Harikrishna Narasimhan, Shivani Agarwal
A Structural SVM Based Approach for Optimizing Partial AUC. ICML (1) (2013)
Harikrishna Narasimhan, Shivani Agarwal
On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation. NIPS (2013)
Aditya Krishna Menon, Harikrishna Narasimhan, Shivani Agarwal, Sanjay Chawla
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance. ICML (3) (2013)
Harikrishna Narasimhan, Venkatanathan Varadarajan, C. Pandu Rangan
Towards a Cooperative Defense Model Against Network Security Attacks. WEIS (2010)
Harikrishna Narasimhan, Venkatanathan Varadarajan, C. Pandu Rangan
Game Theoretic Resistance to Denial of Service Attacks Using Hidden Difficulty Puzzles. ISPEC (2010)
Harikrishna Narasimhan, Sanjeev Satheesh, Dinesh Sriram
Automatic summarization of cricket video events using genetic algorithm. GECCO (Companion) (2010)
Harikrishna Narasimhan
Parallel Artificial Bee Colony (PABC) Algorithm. NaBIC (2009)
Harikrishna Narasimhan, Sanjeev Satheesh
A Randomized Iterative Improvement Algorithm for Photomosaic Generation. NaBIC (2009)
Sanjeev Satheesh, Harikrishna Narasimhan, Pramala Senthil
Evolving player-specific content for level based arcade games. FDG (2009)
Harikrishna Narasimhan, Venkatanathan Varadarajan, C. Pandu Rangan
Game Theoretic Resistance to Denial of Service Attacks Using Hidden Difficulty Puzzles. IACR Cryptol. ePrint Arch. 2009 (2009)