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2020 – today
- 2024
[c17]Maximilian Lam
, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh:
GPU-based Private Information Retrieval for On-Device Machine Learning Inference. ASPLOS (1) 2024: 197-214- [c16]Juntaek Lim, Youngeun Kwon, Ranggi Hwang, Kiwan Maeng, G. Edward Suh, Minsoo Rhu:
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models. ASPLOS (2) 2024: 616-630 - [c15]Kiwan Maeng, Brandon Lucia:
Compiler-Based Memory Encryption for Machine Learning on Commodity Low-Power Devices. CC 2024: 198-211 - [c14]Kiwan Maeng, G. Edward Suh:
Accelerating ReLU for MPC-Based Private Inference with a Communication-Efficient Sign Estimation. MLSys 2024 - [c13]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 - [i16]Juntaek Lim, Youngeun Kwon, Ranggi Hwang, Kiwan Maeng, G. Edward Suh, Minsoo Rhu:
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models. CoRR abs/2404.08847 (2024) - 2023
- [j3]Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu:
Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. IEEE Data Eng. Bull. 46(1): 145-157 (2023) - [c12]Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Udit Gupta, Manoj Chakkaravarthy, David Brooks, Carole-Jean Wu:
Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenters. ASPLOS (2) 2023: 118-132 - [c11]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 - [c10]Rishabh Jain, Scott Cheng, Vishwas Kalagi, Vrushabh Sanghavi, Samvit Kaul, Meena Arunachalam, Kiwan Maeng, Adwait Jog, Anand Sivasubramaniam, Mahmut Taylan Kandemir, Chita R. Das:
Optimizing CPU Performance for Recommendation Systems At-Scale. ISCA 2023: 77:1-77:15 - [c9]Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh:
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information. NeurIPS 2023 - [i15]Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh:
GPU-based Private Information Retrieval for On-Device Machine Learning Inference. CoRR abs/2301.10904 (2023) - [i14]Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael G. Rabbat, Carole-Jean Wu, Ilya Mironov:
Green Federated Learning. CoRR abs/2303.14604 (2023) - [i13]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) - [i12]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) - [i11]Kiwan Maeng, G. Edward Suh:
Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference. CoRR abs/2309.04875 (2023) - 2022
- [c8]Emily Ruppel, Milijana Surbatovich, Harsh Desai, Kiwan Maeng, Brandon Lucia:
An Architectural Charge Management Interface for Energy-Harvesting Systems. MICRO 2022: 318-335 - [c7]Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, Jinshi Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood:
Sustainable AI: Environmental Implications, Challenges and Opportunities. MLSys 2022 - [c6]Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu:
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity. RecSys 2022: 156-167 - [i10]Bilge Acun, Benjamin Lee, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu:
A Holistic Approach for Designing Carbon Aware Datacenters. CoRR abs/2201.10036 (2022) - [i9]Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu:
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity. CoRR abs/2206.02633 (2022) - [i8]Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu:
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning. CoRR abs/2206.03852 (2022) - [i7]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) - [i6]Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh:
Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information. CoRR abs/2209.10119 (2022) - [i5]Hanieh Hashemi, Wenjie Xiong, Liu Ke, Kiwan Maeng, Murali Annavaram, G. Edward Suh, Hsien-Hsin S. Lee:
Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems. CoRR abs/2212.06264 (2022) - 2021
- [c5]Kiwan Maeng, Shivam Bharuka, Isabel Gao, Mark C. Jeffrey, Vikram Saraph, Bor-Yiing Su, Caroline Trippel, Jiyan Yang, Mike Rabbat, Brandon Lucia, Carole-Jean Wu:
Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery. MLSys 2021 - [i4]Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood:
Sustainable AI: Environmental Implications, Challenges and Opportunities. CoRR abs/2111.00364 (2021) - 2020
- [j2]Amjad Yousef Majid, Carlo Delle Donne, Kiwan Maeng, Alexei Colin, Kasim Sinan Yildirim, Brandon Lucia, Przemyslaw Pawelczak:
Dynamic Task-based Intermittent Execution for Energy-harvesting Devices. ACM Trans. Sens. Networks 16(1): 5:1-5:24 (2020) - [c4]Kiwan Maeng, Brandon Lucia:
Adaptive low-overhead scheduling for periodic and reactive intermittent execution. PLDI 2020: 1005-1021 - [i3]Kiwan Maeng, Shivam Bharuka, Isabel Gao, Mark C. Jeffrey, Vikram Saraph, Bor-Yiing Su, Caroline Trippel, Jiyan Yang, Mike Rabbat, Brandon Lucia, Carole-Jean Wu:
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery. CoRR abs/2011.02999 (2020)
2010 – 2019
- 2019
- [c3]Kiwan Maeng, Brandon Lucia:
Supporting peripherals in intermittent systems with just-in-time checkpoints. PLDI 2019: 1101-1116 - [i2]Kiwan Maeng, Alexei Colin, Brandon Lucia:
Alpaca: Intermittent Execution without Checkpoints. CoRR abs/1909.06951 (2019) - [i1]Kiwan Maeng, Iskender Kushan, Brandon Lucia, Ashish Kapoor:
Enhancing Stratospheric Weather Analyses and Forecasts by Deploying Sensors from a Weather Balloon. CoRR abs/1912.02276 (2019) - 2018
- [c2]Kiwan Maeng, Brandon Lucia:
Adaptive Dynamic Checkpointing for Safe Efficient Intermittent Computing. OSDI 2018: 129-144 - 2017
- [j1]Kiwan Maeng, Alexei Colin, Brandon Lucia:
Alpaca: intermittent execution without checkpoints. Proc. ACM Program. Lang. 1(OOPSLA): 96:1-96:30 (2017) - [c1]Brandon Lucia, Vignesh Balaji, Alexei Colin, Kiwan Maeng, Emily Ruppel:
Intermittent Computing: Challenges and Opportunities. SNAPL 2017: 8:1-8:14
Coauthor Index
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