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ORCIDSanjay Kariyappa
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2020 – today
- 2024
[c11]Sanjay Kariyappa, Leonidas Tsepenekas, Freddy Lécué, Daniele Magazzeni:
SHAP@k: Efficient and Probably Approximately Correct (PAC) Identification of Top-K Features. AAAI 2024: 13068-13075- [c10]Sanjay Kariyappa, Freddy Lécué, Saumitra Mishra, Christopher Pond, Daniele Magazzeni, Manuela Veloso:
Progressive Inference: Explaining Decoder-Only Sequence Classification Models Using Intermediate Predictions. ICML 2024 - [c9]Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh:
Information Flow Control in Machine Learning through Modular Model Architecture. USENIX Security Symposium 2024 - [i14]Sanjay Kariyappa, Freddy Lécué, Saumitra Mishra, Christopher Pond, Daniele Magazzeni, Manuela Veloso:
Progressive Inference: Explaining Decoder-Only Sequence Classification Models Using Intermediate Predictions. CoRR abs/2406.02625 (2024) - [i13]Giang Nguyen, Ivan Brugere, Shubham Sharma, Sanjay Kariyappa, Anh Totti Nguyen, Freddy Lécué:
Interpretable LLM-based Table Question Answering. CoRR abs/2412.12386 (2024) - 2023
- [b1]Sanjay Kariyappa:
Understanding and Mitigating Privacy Vulnerabilities in Deep Learning. Georgia Institute of Technology, Atlanta, GA, USA, 2023 - [c8]Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong
, G. Edward Suh, Moinuddin K. Qureshi, Hsien-Hsin S. Lee:
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis. ICML 2023: 15884-15899 - [c7]Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh:
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information. NeurIPS 2023 - [c6]Sanjay Kariyappa, Moinuddin K. Qureshi:
ExPLoit: Extracting Private Labels in Split Learning. SaTML 2023: 165-175 - [i12]Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh:
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information. CoRR abs/2305.04146 (2023) - [i11]Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh:
Information Flow Control in Machine Learning through Modular Model Architecture. CoRR abs/2306.03235 (2023) - [i10]Sanjay Kariyappa, Leonidas Tsepenekas, Freddy Lécué, Daniele Magazzeni:
SHAP@k: Efficient and Probably Approximately Correct (PAC) Identification of Top-k Features. CoRR abs/2307.04850 (2023) - [i9]Sikha Pentyala, Shubham Sharma, Sanjay Kariyappa, Freddy Lécué, Daniele Magazzeni:
Privacy-Preserving Algorithmic Recourse. CoRR abs/2311.14137 (2023) - 2022
- [i8]Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong, G. Edward Suh, Moinuddin K. Qureshi, Hsien-Hsin S. Lee:
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis. CoRR abs/2209.05578 (2022) - [i7]Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh:
Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information. CoRR abs/2209.10119 (2022) - 2021
- [c5]Sanjay Kariyappa, Atul Prakash, Moinuddin K. Qureshi:
MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation. CVPR 2021: 13814-13823 - [c4]Sanjay Kariyappa, Atul Prakash, Moinuddin K. Qureshi:
Protecting DNNs from Theft using an Ensemble of Diverse Models. ICLR 2021 - [c3]Gururaj Saileshwar, Sanjay Kariyappa, Moinuddin K. Qureshi:
Bespoke Cache Enclaves: Fine-Grained and Scalable Isolation from Cache Side-Channels via Flexible Set-Partitioning. SEED 2021: 37-49 - [i6]Sanjay Kariyappa, Ousmane Dia, Moinuddin K. Qureshi:
Enabling Inference Privacy with Adaptive Noise Injection. CoRR abs/2104.02261 (2021) - [i5]Sanjay Kariyappa, Moinuddin K. Qureshi:
Gradient Inversion Attack: Leaking Private Labels in Two-Party Split Learning. CoRR abs/2112.01299 (2021) - 2020
- [c2]Sanjay Kariyappa, Moinuddin K. Qureshi:
Defending Against Model Stealing Attacks With Adaptive Misinformation. CVPR 2020: 767-775 - [i4]Sanjay Kariyappa, Atul Prakash, Moinuddin K. Qureshi:
MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation. CoRR abs/2005.03161 (2020)
2010 – 2019
- 2019
- [c1]Vinson Young, Sanjay Kariyappa, Moinuddin K. Qureshi:
Enabling Transparent Memory-Compression for Commodity Memory Systems. HPCA 2019: 570-581 - [i3]Sanjay Kariyappa, Moinuddin K. Qureshi:
Improving Adversarial Robustness of Ensembles with Diversity Training. CoRR abs/1901.09981 (2019) - [i2]Sanjay Kariyappa, Moinuddin K. Qureshi:
Defending Against Model Stealing Attacks with Adaptive Misinformation. CoRR abs/1911.07100 (2019) - 2018
- [i1]Vinson Young, Sanjay Kariyappa, Moinuddin K. Qureshi:
CRAM: Efficient Hardware-Based Memory Compression for Bandwidth Enhancement. CoRR abs/1807.07685 (2018)
Coauthor Index
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