8 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.AR2026
EnergAIzer: Fast and Accurate GPU Power Estimation Framework for AI Workloads
Kyungmi Lee, Zhiye Song, Eun Kyung Lee +3
As AI workloads drive increases in datacenter power consumption, accurate GPU power estimation is critical for proactive power management. However, existing power models face a sca…
cs.LG2020★ 1 cited
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods
Kyungmi Lee, Anantha P. Chandrakasan
We identify three common cases that lead to overestimation of adversarial accuracy against bounded first-order attack methods, which is popularly used as a proxy for adversarial ro…
cs.LG2019★ 8 cited
Autoencoder-Based Incremental Class Learning without Retraining on Old Data
Euntae Choi, Kyungmi Lee, Kiyoung Choi
Incremental class learning, a scenario in continual learning context where classes and their training data are sequentially and disjointedly observed, challenges a problem widely k…