Arun Sai Suggala

Orcid: 0000-0003-4113-5924

According to our database1, Arun Sai Suggala authored at least 45 papers between 2015 and 2025.

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Bibliography

2025
A Personalized Exercise Assistant using Reinforcement Learning (PEARL): Results from a four-arm Randomized-controlled Trial.
CoRR, August, 2025

Regret minimization in Linear Bandits with offline data via extended D-optimal exploration.
CoRR, August, 2025

Learning to Call: A Field Trial of a Collaborative Bandit Algorithm for Improved Message Delivery in Mobile Maternal Health.
CoRR, July, 2025

Robust Reward Modeling via Causal Rubrics.
CoRR, June, 2025

Online Bidding under RoS Constraints without Knowing the Value.
Proceedings of the ACM on Web Conference 2025, 2025

Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health.
Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Offline-to-Online Hyperparameter Transfer for Stochastic Bandits.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization.
Trans. Mach. Learn. Res., 2024

Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health Program.
CoRR, 2024

CDQuant: Accurate Post-training Weight Quantization of Large Pre-trained Models using Greedy Coordinate Descent.
CoRR, 2024

Time-Reversal Provides Unsupervised Feedback to LLMs.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

End-to-End Neural Network Compression via l1/l2 Regularized Latency Surrogates.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Second Order Methods for Bandit Optimization and Control.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Efficient Public Health Intervention Planning Using Decomposition-Based Decision-focused Learning.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Improving Mobile Maternal and Child Health Care Programs: Collaborative Bandits for Time Slot Selection.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023
Optimal Best-Arm Identification in Bandits with Access to Offline Data.
CoRR, 2023

End-to-End Neural Network Compression via 𝓁<sub>1</sub>/𝓁<sub>2</sub> Regularized Latency Surrogates.
CoRR, 2023

Near Optimal Private and Robust Linear Regression.
CoRR, 2023

Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Responsible AI (RAI) Games and Ensembles.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimal Algorithms for Latent Bandits with Cluster Structure.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Flexible Budgets in Restless Bandits: A Primal-Dual Algorithm for Efficient Budget Allocation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Statistical Game Theory.
PhD thesis, 2022

Building Robust Ensembles via Margin Boosting.
Proceedings of the International Conference on Machine Learning, 2022

2021
Boosted CVaR Classification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficient Bandit Convex Optimization: Beyond Linear Losses.
Proceedings of the Conference on Learning Theory, 2021

2020
Learning Minimax Estimators via Online Learning.
CoRR, 2020

Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalized Boosting.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Non-Convex Learning: Following the Perturbed Leader is Optimal.
Proceedings of the Algorithmic Learning Theory, 2020

2019
How Sensitive are Sensitivity-Based Explanations?
CoRR, 2019

On the (In)fidelity and Sensitivity of Explanations.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression.
Proceedings of the Conference on Learning Theory, 2019

Revisiting Adversarial Risk.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
On Adversarial Risk and Training.
CoRR, 2018

Robust Estimation via Robust Gradient Estimation.
CoRR, 2018

Connecting Optimization and Regularization Paths.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Latent Feature Lasso.
Proceedings of the 34th International Conference on Machine Learning, 2017

Ordinal Graphical Models: A Tale of Two Approaches.
Proceedings of the 34th International Conference on Machine Learning, 2017

ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices.
Proceedings of the 34th International Conference on Machine Learning, 2017

2015
Vector-Space Markov Random Fields via Exponential Families.
Proceedings of the 32nd International Conference on Machine Learning, 2015


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