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Model Sparsification Can Simplify Machine Unlearning


Apr 14, 2023
Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

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What Is Missing in IRM Training and Evaluation? Challenges and Solutions


Mar 04, 2023
Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush Varshney, Sijia Liu

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* Accepted to Eleventh International Conference on Learning Representations (ICLR 2023) 

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Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection


Jan 12, 2023
Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble

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* Extended version of the paper appearing at the SIAM International Conference on Data Mining 2023 (SDM23) 

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Advancing Model Pruning via Bi-level Optimization


Oct 12, 2022
Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu

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* Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022) 

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Navigating Ensemble Configurations for Algorithmic Fairness


Oct 11, 2022
Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

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* arXiv admin note: text overlap with arXiv:2202.00751 

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Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning


Mar 03, 2022
Alex Gu, Songtao Lu, Parikshit Ram, Lily Weng

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Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis


Feb 16, 2022
Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

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* arXiv admin note: substantial text overlap with arXiv:2112.08524 

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An Empirical Study of Modular Bias Mitigators and Ensembles


Feb 01, 2022
Michael Feffer, Martin Hirzel, Samuel C. Hoffman, Kiran Kate, Parikshit Ram, Avraham Shinnar

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FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning


Dec 15, 2021
Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

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