Naman Agarwal - RankMe

83 papers A* 20B 4C 2Misc 1Journal 50Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Artificial intelligence in healthcare IT: Enhancing work productivity through techno-eustress. Int. J. Inf. Manag. Shameem Shagirbasha, Naman Agarwal, Angelin Vilma G.
2025	J	`jnl`	Can Multimodal LLMs Solve the Basic Perception Problems of Percept-V? CoRR Samrajnee Ghosh, Naman Agarwal, Hemanshu Garg, Chinmay Mittal, Mausam, Parag Singla
2025	—	`conf`	Cycle Slip repair for single-frequency smartphone GNSS using the Best Integer Equivariant estimator. PLANS Naman Agarwal, Kyle O'Keefe
2025	J	`jnl`	How far away are truly hyperparameter-free learning algorithms? CoRR Priya Kasimbeg, Vincent Roulet, Naman Agarwal, Sourabh Medapati, Fabian Pedregosa, Atish Agarwala, George E. Dahl
2025	J	`jnl`	How far away are truly hyperparameter-free learning algorithms? Trans. Mach. Learn. Res. Priya Kasimbeg, Vincent Roulet, Naman Agarwal, Sourabh Medapati, Fabian Pedregosa, Atish Agarwala, George E. Dahl
2025	Misc	`conf`	Multivariate Time Series Data Mining for Failure Prediction & Root Cause Analysis. ICASSP Naman Agarwal, Gagan Raj Gupta, Vishwesh Jatala, Aniket Saha
2025	A*	`conf`	Provable Length Generalization in Sequence Prediction via Spectral Filtering. ICML Annie Marsden, Evan Dogariu, Naman Agarwal, Xinyi Chen, Daniel Suo, Elad Hazan
2025	J	`jnl`	Training neural networks faster with minimal tuning using pre-computed lists of hyperparameters for NAdamW. CoRR Sourabh Medapati, Priya Kasimbeg, Shankar Krishnan, Naman Agarwal, George E. Dahl
2024	J	`jnl`	FutureFill: Fast Generation from Convolutional Sequence Models. CoRR Naman Agarwal, Xinyi Chen, Evan Dogariu, Vladimir Feinberg, Daniel Suo, Peter L. Bartlett, Elad Hazan
2024	—	`conf`	GenGradAttack: Efficient and Robust Targeted Adversarial Attacks Using Genetic Algorithms and Gradient-Based Fine-Tuning. ICAART (3) Naman Agarwal, James Pope
2024	A*	`conf`	Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements. ICML Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Guha Thakurta
2024	J	`jnl`	Provable Length Generalization in Sequence Prediction via Spectral Filtering. CoRR Annie Marsden, Evan Dogariu, Naman Agarwal, Xinyi Chen, Daniel Suo, Elad Hazan
2024	J	`jnl`	Stacking as Accelerated Gradient Descent. CoRR Naman Agarwal, Pranjal Awasthi, Satyen Kale, Eric Zhao
2024	J	`jnl`	Towards Quantifying the Preconditioning Effect of Adam. CoRR Rudrajit Das, Naman Agarwal, Sujay Sanghavi, Inderjit S. Dhillon
2023	C	`conf`	Alternative Approach to Integrate GNSS Doppler in Kalman Filter for Smartphone Positioning. IPIN Naman Agarwal, Kyle O'Keefe, Richard Klukas
2023	J	`jnl`	Benchmarking Neural Network Training Algorithms. CoRR 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
2023	—	`conf`	Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret. L4DC Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan
2023	A*	`conf`	Differentially Private and Lazy Online Convex Optimization. COLT Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Thakurta
2023	—	`conf`	HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues. PKDD/ECML Workshops (4) Ankit Jha, Debabrata Pal, Mainak Singha, Naman Agarwal, Biplab Banerjee
2023	J	`jnl`	HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues. CoRR Ankit Jha, Debabrata Pal, Mainak Singha, Naman Agarwal, Biplab Banerjee
2023	J	`jnl`	Improved Differentially Private and Lazy Online Convex Optimization. CoRR Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Guha Thakurta
2023	A*	`conf`	Multi-User Reinforcement Learning with Low Rank Rewards. ICML Dheeraj Mysore Nagaraj, Suhas S. Kowshik, Naman Agarwal, Praneeth Netrapalli, Prateek Jain
2023	J	`jnl`	Spectral State Space Models. CoRR Naman Agarwal, Daniel Suo, Xinyi Chen, Elad Hazan
2023	B	`conf`	Variance-Reduced Conservative Policy Iteration. ALT Naman Agarwal, Brian Bullins, Karan Singh
2022	J	`jnl`	Adaptive Gradient Methods at the Edge of Stability. CoRR Jeremy Cohen, Behrooz Ghorbani, Shankar Krishnan, Naman Agarwal, Sourabh Medapati, Michal Badura, Daniel Suo, David Cardoze, Zachary Nado, George E. Dahl, Justin Gilmer
2022	J	`jnl`	Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret. CoRR Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan
2022	B	`conf`	Efficient Methods for Online Multiclass Logistic Regression. ALT Naman Agarwal, Satyen Kale, Julian Zimmert
2022	J	`jnl`	Multi-User Reinforcement Learning with Low Rank Rewards. CoRR Naman Agarwal, Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
2022	A*	`conf`	Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. ICLR Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Mysore Nagaraj, Praneeth Netrapalli
2022	A*	`conf`	Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States. COLT Julian Zimmert, Naman Agarwal, Satyen Kale
2022	J	`jnl`	Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States. CoRR Julian Zimmert, Naman Agarwal, Satyen Kale
2022	J	`jnl`	Variance-Reduced Conservative Policy Iteration. CoRR Naman Agarwal, Brian Bullins, Karan Singh
2021	B	`conf`	A Deep Conditioning Treatment of Neural Networks. ALT Naman Agarwal, Pranjal Awasthi, Satyen Kale
2021	A*	`conf`	A Regret Minimization Approach to Iterative Learning Control. ICML Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh
2021	J	`jnl`	A Regret Minimization Approach to Iterative Learning Control. CoRR Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh
2021	A*	`conf`	Acceleration via Fractal Learning Rate Schedules. ICML Naman Agarwal, Surbhi Goel, Cyril Zhang
2021	J	`jnl`	Acceleration via Fractal Learning Rate Schedules. CoRR Naman Agarwal, Surbhi Goel, Cyril Zhang
2021	J	`jnl`	Adaptive regularization with cubics on manifolds. Math. Program. Naman Agarwal, Nicolas Boumal, Brian Bullins, Coralia Cartis
2021	J	`jnl`	Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking. CoRR Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Udaya Ghai, Karan Singh, Cyril Zhang, Anirudha Majumdar, Elad Hazan
2021	J	`jnl`	Efficient Methods for Online Multiclass Logistic Regression. CoRR Naman Agarwal, Satyen Kale, Julian Zimmert
2021	J	`jnl`	Machine Learning for Mechanical Ventilation Control (Extended Abstract). CoRR Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel J. Cohen, Elad Hazan
2021	J	`jnl`	Machine Learning for Mechanical Ventilation Control. CoRR Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel J. Cohen, Elad Hazan
2021	J	`jnl`	Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. CoRR Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
2021	A*	`conf`	The Skellam Mechanism for Differentially Private Federated Learning. NeurIPS Naman Agarwal, Peter Kairouz, Ziyu Liu
2021	J	`jnl`	The Skellam Mechanism for Differentially Private Federated Learning. CoRR Naman Agarwal, Peter Kairouz, Ziyu Liu
2020	J	`jnl`	A Deep Conditioning Treatment of Neural Networks. CoRR Naman Agarwal, Pranjal Awasthi, Satyen Kale
2020	J	`jnl`	Automated detection of Glaucoma using deep learning convolution network (G-net). Multim. Tools Appl. Mamta Juneja, Shaswat Singh, Naman Agarwal, Shivank Bali, Shubham Gupta, Niharika Thakur, Prashant Jindal
2020	A*	`conf`	Boosting for Control of Dynamical Systems. ICML Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu
2020	J	`jnl`	Disentangling Adaptive Gradient Methods from Learning Rates. CoRR Naman Agarwal, Rohan Anil, Elad Hazan, Tomer Koren, Cyril Zhang
2020	A*	`conf`	Extreme Tensoring for Low-Memory Preconditioning. ICLR Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang
2020	B	`conf`	Leverage Score Sampling for Faster Accelerated Regression and ERM. ALT Naman Agarwal, Sham M. Kakade, Rahul Kidambi, Yin Tat Lee, Praneeth Netrapalli, Aaron Sidford
2020	A*	`conf`	Stochastic Optimization with Laggard Data Pipelines. NeurIPS Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang
2020	J	`jnl`	Stochastic Optimization with Laggard Data Pipelines. CoRR Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang
2019	J	`jnl`	Boosting for Dynamical Systems. CoRR Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu
2019	J	`jnl`	Design and Development of Underwater Vehicle: ANAHITA. CoRR 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
2019	A*	`conf`	Efficient Full-Matrix Adaptive Regularization. ICML Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang
2019	J	`jnl`	Extreme Tensoring for Low-Memory Preconditioning. CoRR Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang
2019	A*	`conf`	Learning in Non-convex Games with an Optimization Oracle. COLT Naman Agarwal, Alon Gonen, Elad Hazan
2019	A*	`conf`	Logarithmic Regret for Online Control. NeurIPS Naman Agarwal, Elad Hazan, Karan Singh
2019	J	`jnl`	Logarithmic Regret for Online Control. CoRR Naman Agarwal, Elad Hazan, Karan Singh
2019	J	`jnl`	On the Expansion of Group-Based Lifts. SIAM J. Discret. Math. Naman Agarwal, Karthekeyan Chandrasekaran, Alexandra Kolla, Vivek Madan
2019	A*	`conf`	Online Control with Adversarial Disturbances. ICML Naman Agarwal, Brian Bullins, Elad Hazan, Sham M. Kakade, Karan Singh
2019	J	`jnl`	Online Control with Adversarial Disturbances. CoRR Naman Agarwal, Brian Bullins, Elad Hazan, Sham M. Kakade, Karan Singh
2018	J	`jnl`	Effective Dimension of Exp-concave Optimization. CoRR Naman Agarwal, Alon Gonen
2018	A*	`conf`	Lower Bounds for Higher-Order Convex Optimization. COLT Naman Agarwal, Elad Hazan
2018	—	`—`	Second-Order Optimization Methods for Machine Learning Naman Agarwal
2018	J	`jnl`	The Case for Full-Matrix Adaptive Regularization. CoRR Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang
2018	A*	`conf`	cpSGD: Communication-efficient and differentially-private distributed SGD. NeurIPS Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Brendan McMahan
2018	J	`jnl`	cpSGD: Communication-efficient and differentially-private distributed SGD. CoRR Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan
2017	A*	`conf`	Finding approximate local minima faster than gradient descent. STOC Naman Agarwal, Zeyuan Allen Zhu, Brian Bullins, Elad Hazan, Tengyu Ma
2017	J	`jnl`	Leverage Score Sampling for Faster Accelerated Regression and ERM. CoRR Naman Agarwal, Sham M. Kakade, Rahul Kidambi, Yin Tat Lee, Praneeth Netrapalli, Aaron Sidford
2017	J	`jnl`	Lower Bounds for Higher-Order Convex Optimization. CoRR Naman Agarwal, Elad Hazan
2017	—	`conf`	On the Expansion of Group-Based Lifts. APPROX-RANDOM Naman Agarwal, Karthekeyan Chandrasekaran, Alexandra Kolla, Vivek Madan
2017	J	`jnl`	Second-Order Stochastic Optimization for Machine Learning in Linear Time. J. Mach. Learn. Res. Naman Agarwal, Brian Bullins, Elad Hazan
2017	J	`jnl`	The Price of Differential Privacy For Online Learning. CoRR Naman Agarwal, Karan Singh
2017	A*	`conf`	The Price of Differential Privacy for Online Learning. ICML Naman Agarwal, Karan Singh
2016	J	`jnl`	Finding Approximate Local Minima for Nonconvex Optimization in Linear Time. CoRR Naman Agarwal, Zeyuan Allen Zhu, Brian Bullins, Elad Hazan, Tengyu Ma
2016	J	`jnl`	Second Order Stochastic Optimization in Linear Time. CoRR Naman Agarwal, Brian Bullins, Elad Hazan
2015	J	`jnl`	Multisection in the Stochastic Block Model using Semidefinite Programming. CoRR Naman Agarwal, Afonso S. Bandeira, Konstantinos Koiliaris, Alexandra Kolla
2015	J	`jnl`	Unique Games on the Hypercube. Chic. J. Theor. Comput. Sci. Naman Agarwal, Guy Kindler, Alexandra Kolla, Luca Trevisan
2014	J	`jnl`	Unique Games on the Hypercube. CoRR Naman Agarwal, Guy Kindler, Alexandra Kolla, Luca Trevisan
2013	J	`jnl`	Small Lifts of Expander Graphs are Expanding. CoRR Naman Agarwal, Alexandra Kolla, Vivek Madan
2007	C	`conf`	Factors Affecting e-Tailing Website Effectiveness: An Indian Perspective. ICIW Ankit Sharma, Yatendra Kumar Singhal, Dhawal Makhija, Anuj Kumar Goyal, Naman Agarwal, Arti Bakhshi