Publications

• [Conference] Kyungmin Bin, Jongseok Park, Chanjeong Park, Seyeon Kim, and Kyunghan Lee, “CoActo: CoActive Neural Network Inference Offloading with Fine-grained and Concurrent Execution,” ACM MobiSys (Acceptance Rate: 16.3%=43/263), Tokyo, Japan, 2024.

• [Conference] Jongseok Park, Kyunbmin Bin, Gibum Park, Sangtae Ha, and Kyunghan Lee, “ASPEN: Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks,” NeurIPS (Acceptance Rate: 26.1%=3222/12343), New Orleans, LA, 2023.

• [Conference] Seyeon Kim, Kyungmin Bin, Donggyu Yang, Sangtae Ha, Song Chong, and Kyunghan Lee, “ENTRO: Tackling the Encoding and Networking Trade-off in Offloaded Video Analytics.” in ACM Multimedia (Acceptance Rate: 29.3%=902/3072), Ottawa, Canad, 2023.

• [Conference] Insoo Lee, Seyeon Kim, Sandesh Dhawaskar Sathyanarayana, Kyungmin Bin, Song Chong, Kyunghan Lee, Dirk Grunwald, Sangtae Ha, “R-FEC: RL-based FEC Adjustment for better QoE in WebRTC,” in ACM Multimedia (Acceptance Rate: 27.5%=690/2473), Lisbon, Portugal, 2022.

• [Conference] Jongseok Park, Kyungmin Bin, and Kyunghan Lee, “mGEMM: Low Latency Convolution with Minimal Memory Overhead Optimized for Mobile Devices” in ACM MobiSys (Acceptance Rate: 21.6%=38/176), Oregon, PO, 2022. paper

• [Journal, Invited] Seyeon Kim, Kyungmin Bin, Sangtae Ha, Kyunghan Lee, and Song Chong, “zTT: Learning-based DVFS with Zero Thermal Throttling for Mobile Devices,” in ACM GetMobile, vol. 25, no.4, pp.30-34, Mar. 2022. paper

• [Conference] [BEST PAPER AWARD] Seyeon Kim, Kyungmin Bin, Sangtae Ha, Kyunghan Lee, and Song Chong, “zTT: Learning-based DVFS with Zero Thermal Throttling for Mobile Devices,” in ACM MobiSys (Acceptance Rate: 21.7%=36/166), Milky way, Mars, 2021. paper