Affiliation recommendation using auxiliary networks. - Vishvas Vasuki; Nagarajan Natarajan; Zhengdong Lu; Inderjit S. Dhillon (RecSys, 2010)

Exploiting longer cycles for link prediction in signed networks. - Kai-Yang Chiang; Nagarajan Natarajan; Ambuj Tewari; Inderjit S. Dhillon (CIKM, 2011)

Scalable Affiliation Recommendation using Auxiliary Networks. - Vishvas Vasuki; Nagarajan Natarajan; Zhengdong Lu; Berkant Savas; Inderjit S. Dhillon (ACM Trans. Intell. Syst. Technol., 2011)

Community detection in content-sharing social networks. - Nagarajan Natarajan; Prithviraj Sen; Vineet Chaoji (ASONAM, 2013)

Learning with Noisy Labels. - Nagarajan Natarajan; Inderjit S. Dhillon; Pradeep Ravikumar; Ambuj Tewari (NIPS, 2013)

Which app will you use next?: collaborative filtering with interactional context. - Nagarajan Natarajan; Donghyuk Shin; Inderjit S. Dhillon (RecSys, 2013)

Consistent Binary Classification with Generalized Performance Metrics. - Oluwasanmi Koyejo; Nagarajan Natarajan; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2014)

Inductive matrix completion for predicting gene-disease associations. - Nagarajan Natarajan; Inderjit S. Dhillon (Bioinform., 2014)

Prediction and clustering in signed networks: a local to global perspective. - Kai-Yang Chiang; Cho-Jui Hsieh; Nagarajan Natarajan; Inderjit S. Dhillon; Ambuj Tewari (J. Mach. Learn. Res., 2014)

PU matrix completion with graph information. - Nagarajan Natarajan; Nikhil Rao 001; Inderjit S. Dhillon (CAMSAP, 2015)

PU Learning for Matrix Completion. - Cho-Jui Hsieh; Nagarajan Natarajan; Inderjit S. Dhillon (ICML, 2015)

Predtron: A Family of Online Algorithms for General Prediction Problems. - Prateek Jain 002; Nagarajan Natarajan; Ambuj Tewari (NIPS, 2015)

Consistent Multilabel Classification. - Oluwasanmi Koyejo; Nagarajan Natarajan; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2015)

Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics. - Nagarajan Natarajan; Oluwasanmi Koyejo; Pradeep Ravikumar; Inderjit S. Dhillon (CoRR, 2015)

Optimal Classification with Multivariate Losses. - Nagarajan Natarajan; Oluwasanmi Koyejo; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2016)

Regret Bounds for Non-decomposable Metrics with Missing Labels. - Nagarajan Natarajan; Prateek Jain 002 (NIPS, 2016)

Learning from Binary Labels with Instance-Dependent Corruption. - Aditya Krishna Menon; Brendan van Rooyen; Nagarajan Natarajan (CoRR, 2016)

Active Heteroscedastic Regression. - Kamalika Chaudhuri; Prateek Jain 002; Nagarajan Natarajan (ICML, 2017)

Consistency Analysis for Binary Classification Revisited. - Krzysztof Dembczynski; Wojciech Kotlowski; Oluwasanmi Koyejo; Nagarajan Natarajan (ICML, 2017)

Leveraging Distributional Semantics for Multi-Label Learning. - Rahul Wadbude; Vivek Gupta 001; Piyush Rai; Nagarajan Natarajan; Harish Karnick (CoRR, 2017)

Cost-Sensitive Learning with Noisy Labels. - Nagarajan Natarajan; Inderjit S. Dhillon; Pradeep Ravikumar; Ambuj Tewari (J. Mach. Learn. Res., 2017)

Learning from binary labels with instance-dependent noise. - Aditya Krishna Menon; Brendan van Rooyen; Nagarajan Natarajan (Mach. Learn., 2018)

Distributional Semantics Meets Multi-Label Learning. - Vivek Gupta 001; Rahul Wadbude; Nagarajan Natarajan; Harish Karnick; Prateek Jain 002; Piyush Rai (AAAI, 2019)

Learning Natural Programs from a Few Examples in Real-Time. - Nagarajan Natarajan; Danny Simmons; Naren Datha; Prateek Jain 002; Sumit Gulwani (AISTATS, 2019)

OASIS: ILP-Guided Synthesis of Loop Invariants. - Sahil Bhatia; Saswat Padhi; Nagarajan Natarajan; Rahul Sharma 001; Prateek Jain 002 (CoRR, 2019)

iBox: Internet in a Box. - Sachin Ashok; Sai Surya Duvvuri; Nagarajan Natarajan; Venkata N. Padmanabhan; Sundararajan Sellamanickam; Johannes Gehrke (HotNets, 2020)

Programming by Rewards. - Nagarajan Natarajan; Ajaykrishna Karthikeyan; Prateek Jain 002; Ivan Radicek; Sriram K. Rajamani; Sumit Gulwani; Johannes Gehrke (CoRR, 2020)

Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization. - Aadirupa Saha; Nagarajan Natarajan; Praneeth Netrapalli; Prateek Jain 002 (ICML, 2021)

Jigsaw: Large Language Models meet Program Synthesis. - Naman Jain; Skanda Vaidyanath; Arun Iyer; Nagarajan Natarajan; Suresh Parthasarathy; Sriram K. Rajamani; Rahul Sharma 001 (ICSE, 2022)

Data-Driven Network Path Simulation with iBox. - Sachin Ashok; Shubham Tiwari; Nagarajan Natarajan; Venkata N. Padmanabhan; Sundararajan Sellamanickam (Proc. ACM Meas. Anal. Comput. Syst., 2022)

Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent. - Ajaykrishna Karthikeyan; Naman Jain; Nagarajan Natarajan; Prateek Jain 002 (Trans. Mach. Learn. Res., 2022)

Simulating Network Paths with Recurrent Buffering Units. - Divyam Anshumaan; Sriram Balasubramanian; Shubham Tiwari; Nagarajan Natarajan; Sundararajan Sellamanickam; Venkat N. Padmanabhan (AAAI, 2023)

Don't Forget the User: It's Time to Rethink Network Measurements. - Aryan Taneja; Rahul Bothra; Debopam Bhattacherjee; Rohan Gandhi; Venkata N. Padmanabhan; Ranjita Bhagwan; Nagarajan Natarajan; Saikat Guha 002; Ross Cutler (HotNets, 2023)

SelfTune: Tuning Cluster Managers. - Ajaykrishna Karthikeyan; Nagarajan Natarajan; Gagan Somashekar; Lei Zhao; Ranjita Bhagwan; Rodrigo Fonseca; Tatiana Racheva; Yogesh Bansal (NSDI, 2023)

Combinatorial categorized bandits with expert rankings. - Sayak Ray Chowdhury; Gaurav Sinha 001; Nagarajan Natarajan; Amit Sharma (UAI, 2023)

StaticFixer: From Static Analysis to Static Repair. - Naman Jain; Shubham Gandhi; Atharv Sonwane; Aditya Kanade 001; Nagarajan Natarajan; Suresh Parthasarathy; Sriram K. Rajamani; Rahul Sharma 001 (CoRR, 2023)

Frustrated with Code Quality Issues? LLMs can Help! - Nalin Wadhwa; Jui Pradhan; Atharv Sonwane; Surya Prakash Sahu; Nagarajan Natarajan; Aditya Kanade 001; Suresh Parthasarathy; Sriram K. Rajamani (CoRR, 2023)

GAR-meets-RAG Paradigm for Zero-Shot Information Retrieval. - Daman Arora; Anush Kini; Sayak Ray Chowdhury; Nagarajan Natarajan; Gaurav Sinha 001; Amit Sharma (CoRR, 2023)

Differentially Private Reward Estimation with Preference Feedback. - Sayak Ray Chowdhury; Xingyu Zhou 001; Nagarajan Natarajan (AISTATS, 2024)

Provably Robust DPO: Aligning Language Models with Noisy Feedback. - Sayak Ray Chowdhury; Anush Kini; Nagarajan Natarajan (ICML, 2024)

OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy. - Gagan Somashekar; Karan Tandon; Anush Kini; Chieh-Chun Chang; Petr Husak; Ranjita Bhagwan; Mayukh Das; Anshul Gandhi; Nagarajan Natarajan (NSDI, 2024)

NoFunEval: Funny How Code LMs Falter on Requirements Beyond Functional Correctness. - Manav Singhal; Tushar Aggarwal; Abhijeet Awasthi; Nagarajan Natarajan; Aditya Kanade 001 (CoRR, 2024)

Task Facet Learning: A Structured Approach to Prompt Optimization. - Gurusha Juneja; Nagarajan Natarajan; Hua Li; Jian Jiao; Amit Sharma (CoRR, 2024)

MASAI: Modular Architecture for Software-engineering AI Agents. - Daman Arora; Atharv Sonwane; Nalin Wadhwa; Abhav Mehrotra; Saiteja Utpala; Ramakrishna Bairi; Aditya Kanade 001; Nagarajan Natarajan (CoRR, 2024)

CROSS-JEM: Accurate and Efficient Cross-encoders for Short-text Ranking Tasks. - Bhawna Paliwal; Deepak Saini; Mudit Dhawan; Siddarth Asokan; Nagarajan Natarajan; Surbhi Aggarwal; Pankaj Malhotra; Jian Jiao 007; Manik Varma (CoRR, 2024)

ASTRA: Accurate and Scalable ANNS-based Training of Extreme Classifiers. - Sonu Mehta; Jayashree Mohan; Nagarajan Natarajan; Ramachandran Ramjee; Manik Varma (CoRR, 2024)

Plan⨉RAG: Planning-guided Retrieval Augmented Generation. - Prakhar Verma; Sukruta Prakash Midigeshi; Gaurav Sinha 001; Arno Solin; Nagarajan Natarajan; Amit Sharma (CoRR, 2024)

CORE: Resolving Code Quality Issues using LLMs. - Nalin Wadhwa; Jui Pradhan; Atharv Sonwane; Surya Prakash Sahu; Nagarajan Natarajan; Aditya Kanade 001; Suresh Parthasarathy; Sriram K. Rajamani (Proc. ACM Softw. Eng., 2024)

Task Facet Learning: A Structured Approach To Prompt Optimization. - Gurusha Juneja; Gautam Jajoo; Hua Li; Jian Jiao; Nagarajan Natarajan; Amit Sharma (ACL (Findings), 2025)

Robust Learning of Diverse Code Edits. - Tushar Aggarwal; Swayam Singh; Abhijeet Awasthi; Aditya Kanade 001; Nagarajan Natarajan (CoRR, 2025)

Code Researcher: Deep Research Agent for Large Systems Code and Commit History. - Ramneet Singh; Sathvik Joel; Abhav Mehrotra; Nalin Wadhwa; Ramakrishna B. Bairi; Aditya Kanade 001; Nagarajan Natarajan (CoRR, 2025)

FrugalRAG: Learning to retrieve and reason for multi-hop QA. - Abhinav Java; Srivathsan Koundinyan; Nagarajan Natarajan; Amit Sharma (CoRR, 2025)

Characterizing Deep Research: A Benchmark and Formal Definition. - Abhinav Java; Ashmit Khandelwal; Sukruta Prakash Midigeshi; Aaron Halfaker; Amit Deshpande; Navin Goyal; Ankur Gupta; Nagarajan Natarajan; Amit Sharma (CoRR, 2025)