Evolving player-specific content for level based arcade games. - Sanjeev Satheesh; Harikrishna Narasimhan; Pramala Senthil (FDG, 2009)

Parallel Artificial Bee Colony (PABC) Algorithm. - Harikrishna Narasimhan (NaBIC, 2009)

A Randomized Iterative Improvement Algorithm for Photomosaic Generation. - Harikrishna Narasimhan; Sanjeev Satheesh (NaBIC, 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)

Automatic summarization of cricket video events using genetic algorithm. - Harikrishna Narasimhan; Sanjeev Satheesh; Dinesh Sriram (GECCO (Companion), 2010)

Towards a Cooperative Defense Model Against Network Security Attacks. - Harikrishna Narasimhan; Venkatanathan Varadarajan; C. Pandu Rangan (WEIS, 2010)

On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance. - Aditya Krishna Menon; Harikrishna Narasimhan; Shivani Agarwal 001; Sanjay Chawla (ICML (3), 2013)

A Structural SVM Based Approach for Optimizing Partial AUC. - Harikrishna Narasimhan; Shivani Agarwal 001 (ICML (1), 2013)

SVMpAUCtight: a new support vector method for optimizing partial AUC based on a tight convex upper bound. - Harikrishna Narasimhan; Shivani Agarwal 001 (KDD, 2013)

On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation. - Harikrishna Narasimhan; Shivani Agarwal 001 (NIPS, 2013)

GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare. - Arpit Agarwal; Harikrishna Narasimhan; Shivaram Kalyanakrishnan; Shivani Agarwal 001 (ICML, 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 001 (ICMLA, 2014)

Online and Stochastic Gradient Methods for Non-decomposable Loss Functions. - Purushottam Kar; Harikrishna Narasimhan; Prateek Jain 002 (NIPS, 2014)

On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures. - Harikrishna Narasimhan; Rohit Vaish; Shivani Agarwal 001 (NIPS, 2014)

Surrogate Functions for Maximizing Precision at the Top. - Purushottam Kar; Harikrishna Narasimhan; Prateek Jain 002 (ICML, 2015)

Optimizing Non-decomposable Performance Measures: A Tale of Two Classes. - Harikrishna Narasimhan; Purushottam Kar; Prateek Jain 002 (ICML, 2015)

Consistent Multiclass Algorithms for Complex Performance Measures. - Harikrishna Narasimhan; Harish G. Ramaswamy; Aadirupa Saha; Shivani Agarwal 001 (ICML, 2015)

Learnability of Influence in Networks. - Harikrishna Narasimhan; David C. Parkes; Yaron Singer (NIPS, 2015)

Bayes Optimal Feature Selection for Supervised Learning with General Performance Measures. - C. G. Saneem Ahmed; Harikrishna Narasimhan; Shivani Agarwal 001 (UAI, 2015)

Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics. - Harish G. Ramaswamy; Harikrishna Narasimhan; Shivani Agarwal 001 (CoRR, 2015)

Optimizing the Multiclass F-Measure via Biconcave Programming. - Harikrishna Narasimhan; Weiwei Pan; Purushottam Kar; Pavlos Protopapas; Harish G. Ramaswamy (ICDM, 2016)

Automated Mechanism Design without Money via Machine Learning. - Harikrishna Narasimhan; Shivani Agarwal 001; David C. Parkes (IJCAI, 2016)

Online Optimization Methods for the Quantification Problem. - Purushottam Kar; Shuai Li 011; Harikrishna Narasimhan; Sanjay Chawla; Fabrizio Sebastiani 001 (KDD, 2016)

A General Statistical Framework for Designing Strategy-proof Assignment Mechanisms. - Harikrishna Narasimhan; David C. Parkes (UAI, 2016)

Stochastic Optimization Techniques for Quantification Performance Measures. - Shuai Li 011; Harikrishna Narasimhan; Purushottam Kar; Sanjay Chawla; Fabrizio Sebastiani 001 (CoRR, 2016)

Optimal Auctions through Deep Learning. - Paul Dütting; Zhe Feng 004; Harikrishna Narasimhan; David C. Parkes (CoRR, 2017)

Support Vector Algorithms for Optimizing the Partial Area under the ROC Curve. - Harikrishna Narasimhan; Shivani Agarwal 001 (Neural Comput., 2017)

Learning with Complex Loss Functions and Constraints. - Harikrishna Narasimhan (AISTATS, 2018)

Deep Learning for Revenue-Optimal Auctions with Budgets. - Zhe Feng 004; Harikrishna Narasimhan; David C. Parkes (AAMAS, 2018)

Deep Learning for Multi-Facility Location Mechanism Design. - Noah Golowich; Harikrishna Narasimhan; David C. Parkes (IJCAI, 2018)

Metric-Optimized Example Weights. - Sen Zhao; Mahdi Milani Fard; Harikrishna Narasimhan; Maya R. Gupta (ICML, 2019)

On Making Stochastic Classifiers Deterministic. - Andrew Cotter; Maya R. Gupta; Harikrishna Narasimhan (NeurIPS, 2019)

Optimizing Generalized Rate Metrics with Three Players. - Harikrishna Narasimhan; Andrew Cotter; Maya R. Gupta (NeurIPS, 2019)

Optimizing Generalized Rate Metrics through Game Equilibrium. - Harikrishna Narasimhan; Andrew Cotter; Maya R. Gupta (CoRR, 2019)

Pairwise Fairness for Ranking and Regression. - Harikrishna Narasimhan; Andrew Cotter; Maya R. Gupta; Serena Lutong Wang (AAAI, 2020)

Optimizing Black-box Metrics with Adaptive Surrogates. - Qijia Jiang; Olaoluwa Adigun; Harikrishna Narasimhan; Mahdi Milani Fard; Maya R. Gupta (ICML, 2020)

Fair Performance Metric Elicitation. - Gaurush Hiranandani; Harikrishna Narasimhan; Oluwasanmi Koyejo (NeurIPS, 2020)

Approximate Heavily-Constrained Learning with Lagrange Multiplier Models. - Harikrishna Narasimhan; Andrew Cotter; Yichen Zhou; Serena Lutong Wang; Wenshuo Guo (NeurIPS, 2020)

Consistent Plug-in Classifiers for Complex Objectives and Constraints. - Shiv Kumar Tavker; Harish Guruprasad Ramaswamy; Harikrishna Narasimhan (NeurIPS, 2020)

Robust Optimization for Fairness with Noisy Protected Groups. - Serena Lutong Wang; Wenshuo Guo; Harikrishna Narasimhan; Andrew Cotter; Maya R. Gupta; Michael I. Jordan (NeurIPS, 2020)

Quadratic Metric Elicitation with Application to Fairness. - Gaurush Hiranandani; Jatin Mathur; Harikrishna Narasimhan; Oluwasanmi Koyejo (CoRR, 2020)

Optimizing Black-box Metrics with Iterative Example Weighting. - Gaurush Hiranandani; Jatin Mathur; Harikrishna Narasimhan; Mahdi Milani Fard; Sanmi Koyejo (ICML, 2021)

Implicit rate-constrained optimization of non-decomposable objectives. - Abhishek Kumar; Harikrishna Narasimhan; Andrew Cotter (ICML, 2021)

Training Over-parameterized Models with Non-decomposable Objectives. - Harikrishna Narasimhan; Aditya Krishna Menon (NeurIPS, 2021)

Optimal auctions through deep learning. - Paul Dütting; Zhe Feng 004; Harikrishna Narasimhan; David C. Parkes; Sai Srivatsa Ravindranath (Commun. ACM, 2021)

Distilling Double Descent. - Andrew Cotter; Aditya Krishna Menon; Harikrishna Narasimhan; Ankit Singh Rawat; Sashank J. Reddi; Yichen Zhou (CoRR, 2021)

Churn Reduction via Distillation. - Heinrich Jiang; Harikrishna Narasimhan; Dara Bahri; Andrew Cotter; Afshin Rostamizadeh (ICLR, 2022)

Post-hoc estimators for learning to defer to an expert. - Harikrishna Narasimhan; Wittawat Jitkrittum; Aditya Krishna Menon; Ankit Singh Rawat; Sanjiv Kumar (NeurIPS, 2022)

Quadratic metric elicitation for fairness and beyond. - Gaurush Hiranandani; Jatin Mathur; Harikrishna Narasimhan; Oluwasanmi Koyejo (UAI, 2022)

Robust Distillation for Worst-class Performance. - Serena Lutong Wang; Harikrishna Narasimhan; Yichen Zhou; Sara Hooker; Michal Lukasik; Aditya Krishna Menon (CoRR, 2022)

Consistent Multiclass Algorithms for Complex Metrics and Constraints. - Harikrishna Narasimhan; Harish G. Ramaswamy; Shiv Kumar Tavker; Drona Khurana; Praneeth Netrapalli; Shivani Agarwal 001 (CoRR, 2022)

Distributionally Robust Post-hoc Classifiers under Prior Shifts. - Jiaheng Wei; Harikrishna Narasimhan; Ehsan Amid; Wen-Sheng Chu; Yang Liu 018; Abhishek Kumar (ICLR, 2023)

When Does Confidence-Based Cascade Deferral Suffice? - Wittawat Jitkrittum; Neha Gupta; Aditya Krishna Menon; Harikrishna Narasimhan; Ankit Singh Rawat; Sanjiv Kumar (NeurIPS, 2023)

Robust distillation for worst-class performance: on the interplay between teacher and student objectives. - Serena Wang 001; Harikrishna Narasimhan; Yichen Zhou; Sara Hooker; Michal Lukasik; Aditya Krishna Menon (UAI, 2023)

Learning to reject meets OOD detection: Are all abstentions created equal? - Harikrishna Narasimhan; Aditya Krishna Menon; Wittawat Jitkrittum; Sanjiv Kumar (CoRR, 2023)

Regression Aware Inference with LLMs. - Michal Lukasik; Harikrishna Narasimhan; Aditya Krishna Menon; Felix X. Yu; Sanjiv Kumar (EMNLP (Findings), 2024)

Language Model Cascades: Token-Level Uncertainty And Beyond. - Neha Gupta; Harikrishna Narasimhan; Wittawat Jitkrittum; Ankit Singh Rawat; Aditya Krishna Menon; Sanjiv Kumar (ICLR, 2024)

Learning to Reject Meets Long-tail Learning. - Harikrishna Narasimhan; Aditya Krishna Menon; Wittawat Jitkrittum; Neha Gupta; Sanjiv Kumar (ICLR, 2024)

Plugin estimators for selective classification with out-of-distribution detection. - Harikrishna Narasimhan; Aditya Krishna Menon; Wittawat Jitkrittum; Sanjiv Kumar (ICLR, 2024)

Metric-aware LLM inference. - Michal Lukasik; Harikrishna Narasimhan; Aditya Krishna Menon; Felix X. Yu; Sanjiv Kumar (CoRR, 2024)

Cascade-Aware Training of Language Models. - Congchao Wang; Sean Augenstein; Keith Rush; Wittawat Jitkrittum; Harikrishna Narasimhan; Ankit Singh Rawat; Aditya Krishna Menon; Alec Go (CoRR, 2024)

Optimal Auctions through Deep Learning: Advances in Differentiable Economics. - Paul Dütting; Zhe Feng 004; Harikrishna Narasimhan; David C. Parkes; Sai Srivatsa Ravindranath (J. ACM, 2024)

Better autoregressive regression with LLMs via regression-aware fine-tuning. - Michal Lukasik; Zhao Meng; Harikrishna Narasimhan; Yin-Wen Chang; Aditya Krishna Menon; Felix Yu; Sanjiv Kumar (ICLR, 2025)

Faster Cascades via Speculative Decoding. - Harikrishna Narasimhan; Wittawat Jitkrittum; Ankit Singh Rawat; Seungyeon Kim 001; Neha Gupta; Aditya Krishna Menon; Sanjiv Kumar (ICLR, 2025)

Universal Model Routing for Efficient LLM Inference. - Wittawat Jitkrittum; Harikrishna Narasimhan; Ankit Singh Rawat; Jeevesh Juneja; Zifeng Wang; Chen-Yu Lee; Pradeep Shenoy; Rina Panigrahy; Aditya Krishna Menon; Sanjiv Kumar (CoRR, 2025)

Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation. - Michal Lukasik; Lin Chen; Harikrishna Narasimhan; Aditya Krishna Menon; Wittawat Jitkrittum; Felix X. Yu; Sashank J. Reddi; Gang Fu; MohammadHossein Bateni; Sanjiv Kumar (CoRR, 2025)