Kiwan Maeng

49 papers A* 9A 1B 1Journal 28Unranked 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
Composition for Pufferfish Privacy.
CoRR
Jiamu Bai, Guanlin He, Xin Gu, Daniel Kifer, Kiwan Maeng
2025 J jnl
Characterizing the System Overhead of Discrete Noise Generation for Differential Privacy.
IEEE Comput. Archit. Lett.
SeokHyeon Kong, Donghwan Kim, Euiseong Seo, Kiwan Maeng
2025 J jnl
Cocoon: A System Architecture for Differentially Private Training with Correlated Noises.
CoRR
Donghwan Kim, Xin Gu, Jinho Baek, Timothy Lo, Younghoon Min, Kwangsik Shin, Jongryool Kim, Jongse Park, Kiwan Maeng
2025 J jnl
Correlating Cross-Iteration Noise for DP-SGD using Model Curvature.
CoRR
Xin Gu, Yingtai Xiao, Guanlin He, Jiamu Bai, Daniel Kifer, Kiwan Maeng
2025 J jnl
CrypTorch: PyTorch-based Auto-tuning Compiler for Machine Learning with Multi-party Computation.
CoRR
Jinyu Liu, Gang Tan, Kiwan Maeng
2025 A* conf
Hermes: Algorithm-System Co-design for Efficient Retrieval-Augmented Generation At-Scale.
ISCA
Michael Shen, Muhammad Umar, Kiwan Maeng, G. Edward Suh, Udit Gupta
2025 J jnl
In-Depth Characterization of Machine Learning on an Optimized Multi-Party Computing Library.
IEEE Comput. Archit. Lett.
Jinyu Liu, Kiwan Maeng
2025 — conf
Pirate: No Compromise Low-Bandwidth VR Streaming for Edge Devices.
ASPLOS (2)
Yingtian Zhang, Yan Kang, Ziyu Ying, Wanhang Lu, Sijie Lan, Huijuan Xu, Kiwan Maeng, Anand Sivasubramaniam, Mahmut T. Kandemir, Chita R. Das
2025 — conf
Practical Federated Recommendation Model Learning Using ORAM with Controlled Privacy.
ASPLOS (2)
Jinyu Liu, Wenjie Xiong, G. Edward Suh, Kiwan Maeng
2025 J jnl
SVDE: Serverless Framework for Low-Latency Video Analytic Queries With Hardware Disaggregation.
IEEE Trans. Computers
Pingyi Huo, Theodore Michailidis, Yi Zheng, Prapti Panigrahi, Kiwan Maeng, Jishen Zhao, Vijaykrishnan Narayanan
2025 J jnl
Towards Better Optimization For Listwise Preference in Diffusion Models.
CoRR
Jiamu Bai, Xin Yu, Meilong Xu, Weitao Lu, Xin Pan, Kiwan Maeng, Daniel Kifer, Jian Wang, Yu Wang
2024 — conf
Accelerating ReLU for MPC-Based Private Inference with a Communication-Efficient Sign Estimation.
MLSys
Kiwan Maeng, G. Edward Suh
2024 B conf
Compiler-Based Memory Encryption for Machine Learning on Commodity Low-Power Devices.
CC
Kiwan Maeng, Brandon Lucia
2024 — conf
GPU-based Private Information Retrieval for On-Device Machine Learning Inference.
ASPLOS (1)
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
2024 A* conf
Information Flow Control in Machine Learning through Modular Model Architecture.
USENIX Security Symposium
Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh
2024 — conf
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models.
ASPLOS (2)
Juntaek Lim, Youngeun Kwon, Ranggi Hwang, Kiwan Maeng, G. Edward Suh, Minsoo Rhu
2024 J jnl
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models.
CoRR
Juntaek Lim, Youngeun Kwon, Ranggi Hwang, Kiwan Maeng, G. Edward Suh, Minsoo Rhu
2024 — conf
QoS-Diff: Adaptive Auto-tuning Framework for Low-latency Diffusion Model Inference.
MMAsia
Pingyi Huo, Ajay Narayanan Sridhar, Md Fahim Faysal Khan, Kiwan Maeng, Vijaykrishnan Narayanan
2024 J jnl
Towards Understanding Systems Trade-offs in Retrieval-Augmented Generation Model Inference.
CoRR
Michael Shen, Muhammad Umar, Kiwan Maeng, G. Edward Suh, Udit Gupta
2023 J jnl
Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference.
CoRR
Kiwan Maeng, G. Edward Suh
2023 A* conf
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information.
NeurIPS
Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
2023 J jnl
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information.
CoRR
Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
2023 — conf
Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenters.
ASPLOS (2)
Bilge Acun, Benjamin C. Lee, Fiodar Kazhamiaka, Kiwan Maeng, Udit Gupta, Manoj Chakkaravarthy, David Brooks, Carole-Jean Wu
2023 A* conf
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis.
ICML
Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong, G. Edward Suh, Moinuddin K. Qureshi, Hsien-Hsin S. Lee
2023 J jnl
Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems.
IEEE Data Eng. Bull.
Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu
2023 J jnl
GPU-based Private Information Retrieval for On-Device Machine Learning Inference.
CoRR
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
2023 J jnl
Green Federated Learning.
CoRR
Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael G. Rabbat, Carole-Jean Wu, Ilya Mironov
2023 J jnl
Information Flow Control in Machine Learning through Modular Model Architecture.
CoRR
Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh
2023 A* conf
Optimizing CPU Performance for Recommendation Systems At-Scale.
ISCA
Rishabh Jain, Scott Cheng, Vishwas Kalagi, Vrushabh Sanghavi, Samvit Kaul, Meena Arunachalam, Kiwan Maeng, Adwait Jog, Anand Sivasubramaniam, Mahmut Taylan Kandemir, Chita R. Das
2022 J jnl
A Holistic Approach for Designing Carbon Aware Datacenters.
CoRR
Bilge Acun, Benjamin C. Lee, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
2022 A* conf
An Architectural Charge Management Interface for Energy-Harvesting Systems.
MICRO
Emily Ruppel, Milijana Surbatovich, Harsh Desai, Kiwan Maeng, Brandon Lucia
2022 J jnl
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis.
CoRR
Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong, G. Edward Suh, Moinuddin K. Qureshi, Hsien-Hsin S. Lee
2022 J jnl
Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems.
CoRR
Hanieh Hashemi, Wenjie Xiong, Liu Ke, Kiwan Maeng, Murali Annavaram, G. Edward Suh, Hsien-Hsin S. Lee
2022 J jnl
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning.
CoRR
Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu
2022 J jnl
Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information.
CoRR
Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
2022 — conf
Sustainable AI: Environmental Implications, Challenges and Opportunities.
MLSys
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 C. Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood
2022 A conf
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity.
RecSys
Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu
2022 J jnl
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity.
CoRR
Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu
2021 J jnl
Sustainable AI: Environmental Implications, Challenges and Opportunities.
CoRR
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 C. Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood
2021 — conf
Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery.
MLSys
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
2020 A* conf
Adaptive low-overhead scheduling for periodic and reactive intermittent execution.
PLDI
Kiwan Maeng, Brandon Lucia
2020 J jnl
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery.
CoRR
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
2020 J jnl
Dynamic Task-based Intermittent Execution for Energy-harvesting Devices.
ACM Trans. Sens. Networks
Amjad Yousef Majid, Carlo Delle Donne, Kiwan Maeng, Alexei Colin, Kasim Sinan Yildirim, Brandon Lucia, Przemyslaw Pawelczak
2019 J jnl
Alpaca: Intermittent Execution without Checkpoints.
CoRR
Kiwan Maeng, Alexei Colin, Brandon Lucia
2019 J jnl
Enhancing Stratospheric Weather Analyses and Forecasts by Deploying Sensors from a Weather Balloon.
CoRR
Kiwan Maeng, Iskender Kushan, Brandon Lucia, Ashish Kapoor
2019 A* conf
Supporting peripherals in intermittent systems with just-in-time checkpoints.
PLDI
Kiwan Maeng, Brandon Lucia
2018 A* conf
Adaptive Dynamic Checkpointing for Safe Efficient Intermittent Computing.
OSDI
Kiwan Maeng, Brandon Lucia
2017 J jnl
Alpaca: intermittent execution without checkpoints.
Proc. ACM Program. Lang.
Kiwan Maeng, Alexei Colin, Brandon Lucia
2017 — conf
Intermittent Computing: Challenges and Opportunities.
SNAPL
Brandon Lucia, Vignesh Balaji, Alexei Colin, Kiwan Maeng, Emily Ruppel