Nagarajan Natarajan

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All published works

Action	Title	Year	Authors
+ PDF Chat	Plan$\times$RAG: Planning-guided Retrieval Augmented Generation	2024	Prakhar Verma Sukruta Prakash Midigeshi Gaurav Sinha Arno Solin Nagarajan Natarajan Amit Sharma
+ PDF Chat	ASTRA: Accurate and Scalable ANNS-based Training of Extreme Classifiers	2024	Sonu Mehta Jayashree Mohan Nagarajan Natarajan Ramachandran Ramjee Manik Varma
+ PDF Chat	CROSS-JEM: Accurate and Efficient Cross-encoders for Short-text Ranking Tasks	2024	Bhawna Paliwal Deepak Kumar Saini Mudit Dhawan Siddarth Asokan Nagarajan Natarajan Surbhi Aggarwal Pankaj Malhotra Jian Jiao Manik Varma
+ PDF Chat	MASAI: Modular Architecture for Software-engineering AI Agents	2024	Daman Arora Atharv Sonwane N. K. Wadhwa Abhav Mehrotra Saiteja Utpala Ramakrishna Bairi Aditya Kanade Nagarajan Natarajan
+ PDF Chat	Task Facet Learning: A Structured Approach to Prompt Optimization	2024	Gurusha Juneja Nagarajan Natarajan Hua Li Jian Jiao Amit Sharma
+ PDF Chat	Provably Robust DPO: Aligning Language Models with Noisy Feedback	2024	Sayak Ray Chowdhury Anush Kini Nagarajan Natarajan
+ PDF Chat	NoFunEval: Funny How Code LMs Falter on Requirements Beyond Functional Correctness	2024	Manav Singhal Tushar Aggarwal Abhijeet Awasthi Nagarajan Natarajan Aditya Kanade
+ PDF Chat	Simulating Network Paths with Recurrent Buffering Units	2023	Divyam Anshumaan Sriram Balasubramanian Shubham Tiwari Nagarajan Natarajan Sundararajan Sellamanickam Venkat N. Padmanabhan
+	StaticFixer: From Static Analysis to Static Repair	2023	Naman Jain Shubham Gandhi Atharv Sonwane Aditya Kanade Nagarajan Natarajan Suresh Parthasarathy Sriram K. Rajamani Rahul Sharma
+	Frustrated with Code Quality Issues? LLMs can Help!	2023	N. K. Wadhwa Jui Pradhan Atharv Sonwane Surya Prakash Sahu Nagarajan Natarajan Aditya Kanade Suresh Parthasarathy Sriram K. Rajamani
+	Differentially Private Reward Estimation with Preference Feedback	2023	Sayak Ray Chowdhury Xingyu Zhou Nagarajan Natarajan
+	GAR-meets-RAG Paradigm for Zero-Shot Information Retrieval	2023	Daman Arora Anush Kini Sayak Ray Chowdhury Nagarajan Natarajan Gaurav Sinha Amit Sharma
+	Simulating Network Paths with Recurrent Buffering Units	2022	Divyam Anshumaan Sriram Balasubramanian Shubham Tiwari Nagarajan Natarajan Sundararajan Sellamanickam Venkata N. Padmanabhan
+ PDF Chat	Jigsaw: Large Language Models meet Program Synthesis	2021	Naman Jain Skanda Vaidyanath Arun Iyer Nagarajan Natarajan Suresh Parthasarathy Sriram K. Rajamani Rahul Sharma
+	Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization	2021	Aadirupa Saha Nagarajan Natarajan Praneeth Netrapalli Prateek Jain
+	Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent.	2021	Ajaykrishna Karthikeyan Naman Jain Nagarajan Natarajan Prateek Jain
+	Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization	2021	Aadirupa Saha Nagarajan Natarajan Praneeth Netrapalli Prateek Jain
+	Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent	2021	Ajaykrishna Karthikeyan Naman Jain Nagarajan Natarajan Prateek Jain
+	Jigsaw: Large Language Models meet Program Synthesis	2021	Naman Jain Skanda Vaidyanath Arun Iyer Nagarajan Natarajan Suresh Parthasarathy Sriram K. Rajamani Rahul Sharma
+	Programming by Rewards.	2020	Nagarajan Natarajan Ajaykrishna Karthikeyan Prateek Jain Ivan Radiček Sriram K. Rajamani Sumit Gulwani Johannes Gehrke
+	Programming by Rewards	2020	Nagarajan Natarajan Ajaykrishna Karthikeyan Prateek Jain Ivan Radiček Sriram K. Rajamani Sumit Gulwani Johannes Gehrke
+	OASIS: ILP-Guided Synthesis of Loop Invariants.	2019	Sahil Bhatia Saswat Padhi Nagarajan Natarajan Rahul Sharma Prateek Jain
+	On Scaling Data-Driven Loop Invariant Inference	2019	Sahil Bhatia Saswat Padhi Nagarajan Natarajan Rahul Sharma Prateek Jain
+	On Scaling Data-Driven Loop Invariant Inference	2019	Sahil Bhatia Saswat Padhi Nagarajan Natarajan Rahul Sharma Prateek Jain
+	Consistency Analysis for Binary Classification Revisited	2017	Krzysztof Dembczyński Wojciech Kotłowski Oluwasanmi Koyejo Nagarajan Natarajan
+	Leveraging Distributional Semantics for Multi-Label Learning	2017	Rahul Wadbude Vivek Gupta Piyush Rai Nagarajan Natarajan Harish Karnick Prateek Jain
+	Learning from Binary Labels with Instance-Dependent Corruption	2016	Aditya Krishna Menon Brendan van Rooyen Nagarajan Natarajan
+	Learning from Binary Labels with Instance-Dependent Corruption	2016	Aditya Krishna Menon Brendan van Rooyen Nagarajan Natarajan
+	Regret Bounds for Non-decomposable Metrics with Missing Labels	2016	Prateek Jain Nagarajan Natarajan
+	Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics	2015	Nagarajan Natarajan Oluwasanmi Koyejo Pradeep Ravikumar Inderjit S. Dhillon
+	PU Learning for Matrix Completion	2014	Cho‐Jui Hsieh Nagarajan Natarajan Inderjit S. Dhillon
+	PU Learning for Matrix Completion	2014	Cho‐Jui Hsieh Nagarajan Natarajan Inderjit S. Dhillon
+	Prediction and Clustering in Signed Networks: A Local to Global Perspective	2013	Kai-Yang Chiang Cho‐Jui Hsieh Nagarajan Natarajan Ambuj Tewari Inderjit S. Dhillon

Common Coauthors

Coauthor	Papers Together
Prateek Jain	10
Sriram K. Rajamani	6
Naman Jain	5
Rahul Sharma	4
Ajaykrishna Karthikeyan	4
Inderjit S. Dhillon	4
Suresh Parthasarathy	4
Cho‐Jui Hsieh	3
Saswat Padhi	3
Sayak Ray Chowdhury	3
Atharv Sonwane	3
Aditya Krishna Menon	2
Sriram Balasubramanian	2
Brendan van Rooyen	2
Aadirupa Saha	2
Divyam Anshumaan	2
Daman Arora	2
Aditya Kanade	2
Manik Varma	2
Oluwasanmi Koyejo	2
Sundararajan Sellamanickam	2
Anush Kini	2
Shubham Tiwari	2
Amit Sharma	2
N. K. Wadhwa	2
Sumit Gulwani	2
Sahil Bhatia	2
Arun Iyer	2
Skanda Vaidyanath	2
Praneeth Netrapalli	2
Johannes Gehrke	2
Ivan Radiček	2
Rahul Sharma	2
Pankaj Malhotra	1
Gaurav Sinha	1
Gaurav Sinha	1
Amit Sharma	1
Prakhar Verma	1
Aditya Kanade	1
Vivek Gupta	1
Jui Pradhan	1
Venkat N. Padmanabhan	1
Abhav Mehrotra	1
Wojciech Kotłowski	1
Sukruta Prakash Midigeshi	1
Sonu Mehta	1
Jayashree Mohan	1
Arno Solin	1
Ramachandran Ramjee	1
Hua Li	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Online convex programming and generalized infinitesimal gradient ascent	2003	Martin Zinkevich	3
+	Provable Inductive Matrix Completion	2013	Prateek Jain Inderjit S. Dhillon	2
+ PDF Chat	The octagon abstract domain	2006	Antoine Miné	2
+	Surrogate regret bounds for bipartite ranking via strongly proper losses	2014	Shivani Agarwal	2
+	Efficient non-greedy optimization of decision trees	2015	Mohammad Norouzi Maxwell D. Collins Matthew Johnson David J. Fleet Pushmeet Kohli	2
+	A Contextual Bandit Bake-off	2018	Alberto Bietti Alekh Agarwal John Langford	2
+ PDF Chat	Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming	2013	Saeed Ghadimi Guanghui Lan	2
+	Making Contextual Decisions with Low Technical Debt	2016	Alekh Agarwal Sarah Bird Markus Cozowicz Luong Hoang John Langford Stephen Lee Jiaji Li Dan Melamed Gal Oshri Oswaldo Ribas	2
+	Surrogate regret bounds for proper losses	2009	Mark D. Reid Robert C. Williamson	2
+ PDF Chat	Counterexample-guided approach to finding numerical invariants	2017	ThanhVu Nguyen Timos Antonopoulos Andrew Ruef Michael Hicks	2
+ PDF Chat	An Empirical Distribution Function for Sampling with Incomplete Information	1955	Miriam Ayer H. D. Brunk George M. Ewing Willam T. Reid Edward Silverman	1
+	Some estimates of norms of random matrices	2004	Rafał Latała	1
+	How to Compare Different Loss Functions and Their Risks	2007	Ingo Steinwart	1
+	A sequential algorithm for training text classifiers	1994	David Lewis William A. Gale	1
+	Composite Binary Losses	2010	Mark D. Reid Robert C. Williamson	1
+ PDF Chat	Noise Tolerance Under Risk Minimization	2012	Naresh Manwani P. S. Sastry	1
+ PDF Chat	A Singular Value Thresholding Algorithm for Matrix Completion	2010	Jian‐Feng Cai Emmanuel J. Candès Zuowei Shen	1
+ PDF Chat	The slashdot zoo: mining a social network with negative edges	2009	Jérôme Kunegis Andreas Lommatzsch Christian Bauckhage	1
+	Loss Functions for Binary Class Probability Estimation and Classification: Structure and Applications	2005	Andreas Buja Werner Stuetzle Yi Shen	1
+	Sequence to Sequence Learning with Neural Networks	2014	Ilya Sutskever Oriol Vinyals Quoc V. Le	1
+ PDF Chat	The Power of Convex Relaxation: Near-Optimal Matrix Completion	2010	Emmanuel J. Candès Terence Tao	1
+	Parallel matrix factorization for recommender systems	2013	Hsiang‐Fu Yu Cho‐Jui Hsieh Si Si Inderjit S. Dhillon	1
+	Modularity and community structure in networks	2006	M. E. J. Newman	1
+	Sequence Level Training with Recurrent Neural Networks	2015	Marc’Aurelio Ranzato Sumit Chopra Michael Auli Wojciech Zaremba	1
+	Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation	2013	Yoshua Bengio Nicholas Léonard Aaron Courville	1
+	Loss factorization, weakly supervised learning and label noise robustness	2016	Giorgio Patrini Frank Nielsen Richard Nock Marcello Carioni	1
+ PDF Chat	XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks	2016	Mohammad Rastegari Vicente Ordóñez Joseph Redmon Ali Farhadi	1
+	An optimal algorithm for bandit convex optimization	2016	Elad Hazan Yuanzhi Li	1
+	Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1	2016	Matthieu Courbariaux Itay Hubara Daniel Soudry Ran El‐Yaniv Yoshua Bengio	1
+	A Multiworld Testing Decision Service.	2016	Alekh Agarwal Sarah Bird Markus Cozowicz Luong Hoang John Langford Stephen Lee Jiaji Li Dan Melamed Gal Oshri Oswaldo Ribas	1
+	Online Controlled Experiments and A/B Testing	2016	Ron Kohavi Roger Longbotham	1
+	Neural Decision Trees.	2017	Randall Balestriero	1
+ PDF Chat	MoleculeNet: a benchmark for molecular machine learning	2017	Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes Caleb Geniesse Aneesh Pappu Karl Leswing Vijay S. Pande	1
+	Conditional Time Series Forecasting with Convolutional Neural Networks	2017	Anastasia Borovykh Sander M. Bohté Cornelis W. Oosterlee	1
+	A Practical Method for Solving Contextual Bandit Problems Using Decision Trees	2017	Adam N. Elmachtoub Ryan McNellis Sechan Oh Marek Petrik	1
+	Peeking at A/B Tests	2017	Ramesh Johari Pete Koomen Leonid Pekelis David Walsh	1
+	FlashProfile: Interactive Synthesis of Syntactic Profiles.	2017	Saswat Padhi Prateek Jain Daniel Perelman Oleksandr Polozov Sumit Gulwani Todd Millstein	1
+	Distilling a Neural Network Into a Soft Decision Tree	2017	Nicholas Frosst Geoffrey E. Hinton	1
+	Projection-Free Bandit Convex Optimization	2018	Lin Chen Mingrui Zhang Amin Karbasi	1
+	Deep Neural Decision Trees	2018	Yongxin Yang Irene Garcia Morillo Timothy M. Hospedales	1
+	SmartChoices: Hybridizing Programming and Machine Learning	2019	Victor Cărbune Thierry Coppey Alexander N. Daryin Thomas Deselaers Nikhil Sarda Jay Yagnik	1
+ PDF Chat	Optimal Prescriptive Trees	2019	Dimitris Bertsimas Jack Dunn Nishanth Mundru	1
+	SyGuS-Comp 2018: Results and Analysis.	2019	Rajeev Alur Dana Fisman Saswat Padhi Rishabh Singh Abhishek Udupa	1
+	Time Series Simulation by Conditional Generative Adversarial Net	2020	Rao Fu Jie Chen Shutian Zeng Yiping Zhuang Agus Sudjianto	1
+	Overfitting in Synthesis: Theory and Practice (Extended Version)	2019	Saswat Padhi Todd Millstein Aditya V. Nori Rahul Sharma	1
+	Towards Gradient Free and Projection Free Stochastic Optimization	2018	Anit Kumar Sahu Manzil Zaheer Soummya Kar	1
+	Deep Extreme Multi-label Learning	2017	Wenjie Zhang Junchi Yan Xiangfeng Wang Hongyuan Zha	1
+	Consistent Multilabel Ranking through Univariate Losses	2012	Krzysztof Dembczyński Wojciech Kotłowski Eyke Huellermeier	1
+	Surrogate regret bounds for generalized classification performance metrics	2015	Wojciech Kotłowski Krzysztof Dembczyński	1
+	Predicting Positive and Negative Links in Online Social Networks	2010	Jure Leskovec Daniel P. Huttenlocher Jon Kleinberg	1