Kiwan Maeng

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 36

Top Topics

Fisher Information

Projective Transformations

Weather Forecasts

Top Venues

Publications

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)
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)
Kiwan Maeng, Brandon Lucia
Compiler-Based Memory Encryption for Machine Learning on Commodity Low-Power Devices. CC (2024)
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)
Kiwan Maeng, G. Edward Suh
Accelerating ReLU for MPC-Based Private Inference with a Communication-Efficient Sign Estimation. MLSys (2024)
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 (2024)
Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael Rabbat, Carole-Jean Wu, Ilya Mironov
Green Federated Learning. CoRR (2023)
Kiwan Maeng, G. Edward Suh
Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference. CoRR (2023)
Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information. NeurIPS (2023)
Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, 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 (2023)
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)
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)
Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information. CoRR (2023)
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)
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 (2023)
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) (2023)
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 (2022)
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 (2022)
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 (2022)
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)
Emily Ruppel, Milijana Surbatovich, Harsh Desai, Kiwan Maeng, Brandon Lucia
An Architectural Charge Management Interface for Energy-Harvesting Systems. MICRO (2022)
Bilge Acun, Benjamin Lee, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
A Holistic Approach for Designing Carbon Aware Datacenters. CoRR (2022)
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)
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 (2022)
Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information. CoRR (2022)
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 Hazelwood
Sustainable AI: Environmental Implications, Challenges and Opportunities. CoRR (2021)
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)
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 (2020)
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) (2020)
Kiwan Maeng, Brandon Lucia
Adaptive low-overhead scheduling for periodic and reactive intermittent execution. PLDI (2020)
Kiwan Maeng, Brandon Lucia
Supporting peripherals in intermittent systems with just-in-time checkpoints. PLDI (2019)
Kiwan Maeng, Iskender Kushan, Brandon Lucia, Ashish Kapoor
Enhancing Stratospheric Weather Analyses and Forecasts by Deploying Sensors from a Weather Balloon. CoRR (2019)
Kiwan Maeng, Alexei Colin, Brandon Lucia
Alpaca: Intermittent Execution without Checkpoints. CoRR (2019)
Kiwan Maeng, Brandon Lucia
Adaptive Dynamic Checkpointing for Safe Efficient Intermittent Computing. OSDI (2018)
Kiwan Maeng, Alexei Colin, Brandon Lucia
Alpaca: intermittent execution without checkpoints. Proc. ACM Program. Lang. 1 (OOPSLA) (2017)
Brandon Lucia, Vignesh Balaji, Alexei Colin, Kiwan Maeng, Emily Ruppel
Intermittent Computing: Challenges and Opportunities. SNAPL (2017)