Arun Sai Suggala

According to our database1, Arun Sai Suggala authored at least 31 papers between 2015 and 2024.

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Bibliography

2024
Efficient Public Health Intervention Planning Using Decomposition-Based Decision-Focused Learning.
CoRR, 2024

Second Order Methods for Bandit Optimization and Control.
CoRR, 2024

2023
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization.
CoRR, 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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