Sejin Kim

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 27

Top Topics

Pareto Dominance

Reinforcement Learning

Application Profiles

Top Venues

IEEE Comput. Archit. Lett.

Publications

Innyoung Kim, Sejin Kim, Donghyun You
Non-iterative generation of an optimal mesh for a blade passage using deep reinforcement learning. Comput. Phys. Commun. 294 (2024)
Hosung Lee, Sejin Kim, Seungpil Lee, Sanha Hwang, Jihwan Lee, Byung-Jun Lee, Sundong Kim
ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning. CoRR (2024)
Seungpil Lee, Woochang Sim, Donghyeon Shin, Sanha Hwang, Wongyu Seo, Jiwon Park, Seokki Lee, Sejin Kim, Sundong Kim
Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus. CoRR (2024)
Rayoung Park, Heonzoo Lee, Tan Loc Nguyen, Sejin Kim, Yonggwan Won
A Fast and Simple Method for Sleep Breathing Cycle Segmentation in Time Domain. IMCOM (2024)
Sejin Kim, Yoonhee Kim
Interference-aware execution framework with Co-scheML on GPU clusters. Clust. Comput. 26 (5) (2023)
Jaehyun Park, Jaegyun Im, Sanha Hwang, Mintaek Lim, Sabina Ualibekova, Sejin Kim, Sundong Kim
Unraveling the ARC Puzzle: Mimicking Human Solutions with Object-Centric Decision Transformer. CoRR (2023)
Varsha Gouthamchand, Ananya Choudhury, Frank Hoebers, Frederik Wesseling, Mattea Welch, Sejin Kim, Benjamin Haibe-Kains, Joanna Kazmierska, Andre Dekker, Johan van Soest, Leonard Wee
Privacy-Preserving Dashboard for F.A.I.R Head and Neck Cancer data supporting multi-centered collaborations. SWAT4HCLS (2023)
Sejin Kim, Innyoung Kim, Donghyun You
Multi-condition multi-objective optimization using deep reinforcement learning. J. Comput. Phys. 462 (2022)
Sejin Kim, Yoonhee Kim
K-Scheduler: dynamic intra-SM multitasking management with execution profiles on GPUs. Clust. Comput. 25 (1) (2022)
Sejin Kim, Jungwoo Kim, Yongjoo Jang, Jaeha Kung, Sungjin Lee
SEMS: Scalable Embedding Memory System for Accelerating Embedding-Based DNNs. IEEE Comput. Archit. Lett. 21 (2) (2022)
Xuelin Yang, Louis Abraham, Sejin Kim, Petr Smirnov, Feng Ruan, Benjamin Haibe-Kains, Robert Tibshirani
FastCPH: Efficient Survival Analysis for Neural Networks. CoRR (2022)
Innyoung Kim, Sejin Kim, Donghyun You
Optimal mesh generation for a blade passage using deep reinforcement learning. CoRR (2022)
Sejin Kim, Innyoung Kim, Donghyun You
Multi-condition multi-objective optimization using deep reinforcement learning. CoRR (2021)
Sejin Kim, Michal Kazmierski, Benjamin Haibe-Kains
Deep-CR MTLR: a Multi-Modal Approach for Cancer Survival Prediction with Competing Risks. SPACA (2021)
Sejin Kim, Hee Seung Lee
Appreciating interleaved benefits: The effect of metacognitive activities on the selection of learning strategy. CogSci (2021)
Michal Kazmierski, Mattea Welch, Sejin Kim, Chris McIntosh, Katrina Rey-McIntyre, Shao-Hui Huang, Tirth Patel, Tony Tadic, Michael F. Milosevic, Fei-Fei Liu, Andrew Hope, Scott V. Bratman, Benjamin Haibe-Kains
A Machine Learning Challenge for Prognostic Modelling in Head and Neck Cancer Using Multi-modal Data. CoRR (2021)
Seungpyo Hong, Sejin Kim, Donghyun You
Control of a fly-mimicking flyer in complex flow using deep reinforcement learning. CoRR (2021)
Yongjoo Jang, Sejin Kim, Daehoon Kim, Sungjin Lee, Jaeha Kung
Deep Partitioned Training From Near-Storage Computing to DNN Accelerators. IEEE Comput. Archit. Lett. 20 (1) (2021)
Sundong Kim, Hwanjun Song, Sejin Kim, Beomyoung Kim, Jae-Gil Lee
Revisit Prediction by Deep Survival Analysis. PAKDD (2) (2020)
Sejin Kim, Michal Kazmierski, Benjamin Haibe-Kains
Deep-CR MTLR: a Multi-Modal Approach for Cancer Survival Prediction with Competing Risks. CoRR (2020)
Sejin Kim, Taejin Lee
XGBoost based Packer Identification study using Entry point. ICEA (2020)
Sejin Kim, Yoonhee Kim
Co-scheML: Interference-aware Container Co-scheduling Scheme Using Machine Learning Application Profiles for GPU Clusters. CLUSTER (2020)
Sejin Kim, Yoonhee Kim
Exploiting Interference-aware GPU Container Concurrency Learning from Resource Usage of Application Execution. APNOMS (2020)
Sejin Kim, Yoonhee Kim
Toward Interference-aware GPU Container Co-scheduling Learning from Application Profiles. ACSOS Companion (2020)
Sejin Kim, Jisun Oh, Yoonhee Kim
Data Provenance for Experiment Management of Scientific Applications on GPU. APNOMS (2019)
Joonwoo Ahn, Minsung Kim, Sejin Kim, Sangyup Lee, Jaeheung Park
Formation-Based Tracking Method for Human Following Robot. UR (2018)
Sang-Jun Yea, Sejin Kim, John-Michaël To, Jae-Gil Lee
SentiWorld: Understanding Emotions between Countries Based on Tweets. ICWSM (2016)
Sejin Kim, Hyerim Kim, Sung Jo Kim
A trust value-based scheme for efficient contents sharing over mobile P2P networks. J. Supercomput. 71 (6) (2015)