Naman Agarwal

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 65

Top Topics

Iterative Learning

Online Convex Optimization

Top Venues

Publications

Naman Agarwal, Pranjal Awasthi, Satyen Kale, Eric Zhao
Stacking as Accelerated Gradient Descent. CoRR (2024)
Naman Agarwal, James Pope
GenGradAttack: Efficient and Robust Targeted Adversarial Attacks Using Genetic Algorithms and Gradient-Based Fine-Tuning. ICAART (3) (2024)
Rudrajit Das, Naman Agarwal, Sujay Sanghavi, Inderjit S. Dhillon
Towards Quantifying the Preconditioning Effect of Adam. CoRR (2024)
Naman Agarwal, Brian Bullins, Karan Singh
Variance-Reduced Conservative Policy Iteration. ALT (2023)
Dheeraj Mysore Nagaraj, Suhas S. Kowshik, Naman Agarwal, Praneeth Netrapalli, Prateek Jain
Multi-User Reinforcement Learning with Low Rank Rewards. ICML (2023)
Ankit Jha, Debabrata Pal, Mainak Singha, Naman Agarwal, Biplab Banerjee
HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues. CoRR (2023)
Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Guha Thakurta
Improved Differentially Private and Lazy Online Convex Optimization. CoRR (2023)
Naman Agarwal, Kyle O'Keefe, Richard Klukas
Alternative Approach to Integrate GNSS Doppler in Kalman Filter for Smartphone Positioning. IPIN (2023)
George E. Dahl, Frank Schneider, Zachary Nado, Naman Agarwal, Chandramouli Shama Sastry, Philipp Hennig, Sourabh Medapati, Runa Eschenhagen, Priya Kasimbeg, Daniel Suo, Juhan Bae, Justin Gilmer, Abel L. Peirson, Bilal Khan, Rohan Anil, Mike Rabbat, Shankar Krishnan, Daniel Snider, Ehsan Amid, Kongtao Chen, Chris J. Maddison, Rakshith Vasudev, Michal Badura, Ankush Garg, Peter Mattson
Benchmarking Neural Network Training Algorithms. CoRR (2023)
Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan
Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret. L4DC (2023)
Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Thakurta
Differentially Private and Lazy Online Convex Optimization. COLT (2023)
Naman Agarwal, Daniel Suo, Xinyi Chen, Elad Hazan
Spectral State Space Models. CoRR (2023)
Naman Agarwal, Satyen Kale, Julian Zimmert
Efficient Methods for Online Multiclass Logistic Regression. ALT (2022)
Julian Zimmert, Naman Agarwal, Satyen Kale
Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States. CoRR (2022)
Julian Zimmert, Naman Agarwal, Satyen Kale
Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States. COLT (2022)
Jeremy M. Cohen, Behrooz Ghorbani, Shankar Krishnan, Naman Agarwal, Sourabh Medapati, Michal Badura, Daniel Suo, David Cardoze, Zachary Nado, George E. Dahl, Justin Gilmer
Adaptive Gradient Methods at the Edge of Stability. CoRR (2022)
Naman Agarwal, Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
Multi-User Reinforcement Learning with Low Rank Rewards. CoRR (2022)
Naman Agarwal, Brian Bullins, Karan Singh
Variance-Reduced Conservative Policy Iteration. CoRR (2022)
Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan
Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret. CoRR (2022)
Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Mysore Nagaraj, Praneeth Netrapalli
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. ICLR (2022)
Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh
A Regret Minimization Approach to Iterative Learning Control. CoRR (2021)
Naman Agarwal, Pranjal Awasthi, Satyen Kale
A Deep Conditioning Treatment of Neural Networks. ALT (2021)
Naman Agarwal, Peter Kairouz, Ziyu Liu
The Skellam Mechanism for Differentially Private Federated Learning. NeurIPS (2021)
Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh
A Regret Minimization Approach to Iterative Learning Control. ICML (2021)
Naman Agarwal, Surbhi Goel, Cyril Zhang
Acceleration via Fractal Learning Rate Schedules. CoRR (2021)
Naman Agarwal, Peter Kairouz, Ziyu Liu
The Skellam Mechanism for Differentially Private Federated Learning. CoRR (2021)
Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel Cohen, Elad Hazan
Machine Learning for Mechanical Ventilation Control. CoRR (2021)
Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Udaya Ghai, Karan Singh, Cyril Zhang, Anirudha Majumdar, Elad Hazan
Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking. CoRR (2021)
Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. CoRR (2021)
Naman Agarwal, Satyen Kale, Julian Zimmert
Efficient Methods for Online Multiclass Logistic Regression. CoRR (2021)
Naman Agarwal, Surbhi Goel, Cyril Zhang
Acceleration via Fractal Learning Rate Schedules. ICML (2021)
Naman Agarwal, Nicolas Boumal, Brian Bullins, Coralia Cartis
Adaptive regularization with cubics on manifolds. Math. Program. 188 (1) (2021)
Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel Cohen, Elad Hazan
Machine Learning for Mechanical Ventilation Control (Extended Abstract). CoRR (2021)
Mamta Juneja, Shaswat Singh, Naman Agarwal, Shivank Bali, Shubham Gupta, Niharika Thakur, Prashant Jindal
Automated detection of Glaucoma using deep learning convolution network (G-net). Multim. Tools Appl. 79 (21-22) (2020)
Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu
Boosting for Control of Dynamical Systems. ICML (2020)
Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang
Extreme Tensoring for Low-Memory Preconditioning. ICLR (2020)
Naman Agarwal, Rohan Anil, Elad Hazan, Tomer Koren, Cyril Zhang
Disentangling Adaptive Gradient Methods from Learning Rates. CoRR (2020)
Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang
Stochastic Optimization with Laggard Data Pipelines. CoRR (2020)
Naman Agarwal, Sham M. Kakade, Rahul Kidambi, Yin Tat Lee, Praneeth Netrapalli, Aaron Sidford
Leverage Score Sampling for Faster Accelerated Regression and ERM. ALT (2020)
Naman Agarwal, Pranjal Awasthi, Satyen Kale
A Deep Conditioning Treatment of Neural Networks. CoRR (2020)
Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang
Stochastic Optimization with Laggard Data Pipelines. NeurIPS (2020)
Naman Agarwal, Karthekeyan Chandrasekaran, Alexandra Kolla, Vivek Madan
On the Expansion of Group-Based Lifts. SIAM J. Discret. Math. 33 (3) (2019)
Naman Agarwal, Elad Hazan, Karan Singh
Logarithmic Regret for Online Control. CoRR (2019)
Akash Jain, Manish Kumar, Rithvik Patibandla, Balamurugan R, Naveen Chandra R, Abhinav Arora, Akash K. Singh, Varun Pawar, Aditya Rai, Medha Agarwal, Priank Prasad, Vandit Sanadhya, Inshu Namdev, Nilay Shah, Saksham Mittal, Ayush Gupta, Naman Agarwal, Mangal Kothari
Design and Development of Underwater Vehicle: ANAHITA. CoRR (2019)
Naman Agarwal, Alon Gonen, Elad Hazan
Learning in Non-convex Games with an Optimization Oracle. COLT (2019)
Naman Agarwal, Elad Hazan, Karan Singh
Logarithmic Regret for Online Control. NeurIPS (2019)
Naman Agarwal, Brian Bullins, Elad Hazan, Sham M. Kakade, Karan Singh
Online Control with Adversarial Disturbances. CoRR (2019)
Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu
Boosting for Dynamical Systems. CoRR (2019)
Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang
Efficient Full-Matrix Adaptive Regularization. ICML (2019)
Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang
Extreme Tensoring for Low-Memory Preconditioning. CoRR (2019)
Naman Agarwal, Brian Bullins, Elad Hazan, Sham M. Kakade, Karan Singh
Online Control with Adversarial Disturbances. ICML (2019)
Naman Agarwal, Alon Gonen
Effective Dimension of Exp-concave Optimization. CoRR (2018)
Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Brendan McMahan
cpSGD: Communication-efficient and differentially-private distributed SGD. NeurIPS (2018)
Naman Agarwal, Elad Hazan
Lower Bounds for Higher-Order Convex Optimization. COLT (2018)
Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan
cpSGD: Communication-efficient and differentially-private distributed SGD. CoRR (2018)
Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang
The Case for Full-Matrix Adaptive Regularization. CoRR (2018)
Naman Agarwal, Karan Singh
The Price of Differential Privacy for Online Learning. ICML (2017)
Naman Agarwal, Karthekeyan Chandrasekaran, Alexandra Kolla, Vivek Madan
On the Expansion of Group-Based Lifts. APPROX-RANDOM (2017)
Naman Agarwal, Zeyuan Allen Zhu, Brian Bullins, Elad Hazan, Tengyu Ma
Finding approximate local minima faster than gradient descent. STOC (2017)
Naman Agarwal, Brian Bullins, Elad Hazan
Second-Order Stochastic Optimization for Machine Learning in Linear Time. J. Mach. Learn. Res. 18 (2017)
Naman Agarwal, Elad Hazan
Lower Bounds for Higher-Order Convex Optimization. CoRR (2017)
Naman Agarwal, Sham M. Kakade, Rahul Kidambi, Yin Tat Lee, Praneeth Netrapalli, Aaron Sidford
Leverage Score Sampling for Faster Accelerated Regression and ERM. CoRR (2017)
Naman Agarwal, Karan Singh
The Price of Differential Privacy For Online Learning. CoRR (2017)
Naman Agarwal, Brian Bullins, Elad Hazan
Second Order Stochastic Optimization in Linear Time. CoRR (2016)
Naman Agarwal, Zeyuan Allen Zhu, Brian Bullins, Elad Hazan, Tengyu Ma
Finding Approximate Local Minima for Nonconvex Optimization in Linear Time. CoRR (2016)
Naman Agarwal, Afonso S. Bandeira, Konstantinos Koiliaris, Alexandra Kolla
Multisection in the Stochastic Block Model using Semidefinite Programming. CoRR (2015)
Naman Agarwal, Guy Kindler, Alexandra Kolla, Luca Trevisan
Unique Games on the Hypercube. Chic. J. Theor. Comput. Sci. 2015 (2015)
Naman Agarwal, Guy Kindler, Alexandra Kolla, Luca Trevisan
Unique Games on the Hypercube. CoRR (2014)
Naman Agarwal, Alexandra Kolla, Vivek Madan
Small Lifts of Expander Graphs are Expanding. CoRR (2013)
Ankit Sharma, Yatendra Kumar Singhal, Dhawal Makhija, Anuj Kumar Goyal, Naman Agarwal, Arti Bakhshi
Factors Affecting e-Tailing Website Effectiveness: An Indian Perspective. ICIW (2007)