Arun Sai Suggala

CoRR, 2024

Time-Reversal Provides Unsupervised Feedback to LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

Arpan Dasgupta

Gagan Jain

Milind Tambe

Aparna Taneja

CoRR, 2024

Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD.

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

Pranav Ajit Nair

CoRR, 2024

End-to-End Neural Network Compression via l1/l2 Regularized Latency Surrogates.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Second Order Methods for Bandit Optimization and Control.

[BibT_eX]

[DOI]

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Efficient Public Health Intervention Planning Using Decomposition-Based Decision-focused Learning.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Soumyabrata Pal

Milind Tambe

Aparna Taneja

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

Shubhada Agrawal

Sandeep Juneja

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Near Optimal Private and Robust Linear Regression.

[BibT_eX]

[DOI]

CoRR, 2023

Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints.

[BibT_eX]

[DOI]

Soumyabrata Pal

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Soumyabrata Pal

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Flexible Budgets in Restless Bandits: A Primal-Dual Algorithm for Efficient Budget Allocation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Statistical Game Theory.

[BibT_eX]

[DOI]

PhD thesis, 2022

Building Robust Ensembles via Margin Boosting.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Boosted CVaR Classification.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Praneeth Netrapalli

Proceedings of the Conference on Learning Theory, 2021

2020

Learning Minimax Estimators via Online Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games.

[BibT_eX]

[DOI]

Praneeth Netrapalli

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

Generalized Boosting.

[BibT_eX]

[DOI]

Bingbin Liu

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.

[BibT_eX]

[DOI]

Praneeth Netrapalli

Proceedings of the Algorithmic Learning Theory, 2020

2019

How Sensitive are Sensitivity-Based Explanations?

[BibT_eX]

[DOI]

CoRR, 2019

On the (In)fidelity and Sensitivity of Explanations.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2019

Revisiting Adversarial Risk.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

On Adversarial Risk and Training.

[BibT_eX]

[DOI]

CoRR, 2018

Robust Estimation via Robust Gradient Estimation.

[BibT_eX]

[DOI]

Adarsh Prasad

Sivaraman Balakrishnan

CoRR, 2018

Connecting Optimization and Regularization Paths.

[BibT_eX]

[DOI]

Adarsh Prasad

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.

[BibT_eX]

[DOI]

Mladen Kolar

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Latent Feature Lasso.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Ordinal Graphical Models: A Tale of Two Approaches.

[BibT_eX]

[DOI]

Eunho Yang

Proceedings of the 34th International Conference on Machine Learning, 2017

ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices.

[BibT_eX]

[DOI]

Chirag Gupta

Oscar Hernan Madrid Padilla

Ankit Goyal

Harsha Vardhan Simhadri

Proceedings of the 34th International Conference on Machine Learning, 2017

2015

Vector-Space Markov Random Fields via Exponential Families.

[BibT_eX]

[DOI]

Wesley Tansey