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Seyoung Kim
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2020 – today
- 2023
- [j14]Seyoung Kim, Seungho Yang, Hyein Lim, Hyein Lee, Jongwook Jeon, Jung Yun Choi, Jaeha Kim:
Accurate Layout-Dependent Effect Model in 10 nm-Class DRAM Process Using Area-Efficient Array Test Circuits. IEEE Access 11: 70691-70697 (2023) - [j13]Seyoung Kim, Jaeha Kim:
Reachability Analysis for Nonlinear Analog/Mixed-Signal Circuits With Trajectory-Based Reachable Sets. IEEE Access 11: 74602-74613 (2023) - [c30]Daniel P. Jeong, Seyoung Kim:
Factorial SDE for Multi-Output Gaussian Process Regression. AISTATS 2023: 9755-9772 - [c29]Minseong Um, Minil Kang, Hyunjeong Kwak, Kyungmi Noh, Seyoung Kim, Hyung-Min Lee:
An ECRAM-Based Analog Compute-in-Memory Neuromorphic System with High-Precision Current Readout. BioCAS 2023: 1-5 - [c28]Seyoung Kim, Joohwan Hong, Yongjae Lee:
A GANs-Based Approach for Stock Price Anomaly Detection and Investment Risk Management. ICAIF 2023: 1-9 - [c27]Seonmi Kim, Seyoung Kim, Yejin Kim, Junpyo Park, Seongjin Kim, Moolkyeol Kim, Chang Hwan Sung, Joohwan Hong, Yongjae Lee:
LLMs Analyzing the Analysts: Do BERT and GPT Extract More Value from Financial Analyst Reports? ICAIF 2023: 383-391 - [c26]Hyuncheol Kim, Yun Hyeok Kim, Sanghyuck Moon, Hwanwoong Kim, Byeongjun Yoo, Jueun Park, Seyoung Kim, June-Mo Koo, Sewon Seo, Hye Ji Shin, Younghwan Choi, Jinwoo Kim, Kyungil Kim, Jae-Hoon Seo, Seunghyun Lim, Taesub Jung, Howoo Park, Sangil Jung, Juhyun Ko, Kyungho Lee, JungChak Ahn, Joonseo Yim:
A 0.64μm 4-Photodiode 1.28μm 50Mpixel CMOS Image Sensor with 0.98e- Temporal Noise and 20Ke- Full-Well Capacity Employing Quarter-Ring Source-Follower. ISSCC 2023: 96-97 - 2022
- [j12]O. Murat Onen, Tayfun Gokmen, Teodor K. Todorov, Tomasz Nowicki, Jesús A. del Alamo, John Rozen, Wilfried Haensch, Seyoung Kim:
Neural Network Training With Asymmetric Crosspoint Elements. Frontiers Artif. Intell. 5: 891624 (2022) - [j11]Jun Ho Yoon, Seyoung Kim:
EiGLasso for Scalable Sparse Kronecker-Sum Inverse Covariance Estimation. J. Mach. Learn. Res. 23: 110:1-110:39 (2022) - [c25]Jun Ho Yoon, Daniel P. Jeong, Seyoung Kim:
Doubly Mixed-Effects Gaussian Process Regression. AISTATS 2022: 6893-6908 - [i10]O. Murat Onen, Tayfun Gokmen, Teodor K. Todorov, Tomasz Nowicki, Jesús A. del Alamo, John Rozen, Wilfried Haensch, Seyoung Kim:
Neural Network Training with Asymmetric Crosspoint Elements. CoRR abs/2201.13377 (2022) - 2021
- [c24]Seyoung Kim, Heechun Park, Jaeha Kim:
Safety Verification of AMS Circuits with Piecewise-Linear System Reachability Analysis. ISOCC 2021: 203-206 - [c23]Eun Sub Shim, Kyungho Lee, Junghyung Pyo, Wooseok Choi, Jungbin Yun, Taesub Jung, Kyungduck Lee, Seyoung Kim, Chanhee Lee, Seungki Baek, Hyuncheol Kim, Sungsoo Choi, Junseok Yang, Kyoungmok Son, Jongwon Choi, Howoo Park, Bumsuk Kim, JungChak Ahn, Duckhyun Chang:
All-Directional Dual Pixel Auto Focus Technology in CMOS Image Sensors. VLSI Circuits 2021: 1-2 - [i9]Chaeun Lee, Seyoung Kim:
SEMULATOR: Emulating the Dynamics of Crossbar Array-based Analog Neural System with Regression Neural Networks. CoRR abs/2101.07864 (2021) - [i8]Jun Ho Yoon, Seyoung Kim:
EiGLasso for Scalable Sparse Kronecker-Sum Inverse Covariance Estimation. CoRR abs/2105.09872 (2021) - 2020
- [j10]Youngseok Kim, Seyoung Kim, Chun-Chen Yeh, Vijay Narayanan, Jungwook Choi:
Hardware and Software Co-optimization for the Initialization Failure of the ReRAM-based Cross-bar Array. ACM J. Emerg. Technol. Comput. Syst. 16(4): 36:1-36:19 (2020) - [j9]Calvin McCarter, Judie A. Howrylak, Seyoung Kim:
Learning gene networks underlying clinical phenotypes using SNP perturbation. PLoS Comput. Biol. 16(10) (2020) - [c22]Gi-Bum Kim, Seyoung Kim:
Multi-level Gaussian Graphical Models Conditional on Covariates. AISTATS 2020: 4216-4225 - [c21]Jun Ho Yoon, Seyoung Kim:
EiGLasso: Scalable Estimation of Cartesian Product of Sparse Inverse Covariance Matrices. UAI 2020: 1248-1257 - [i7]Youngseok Kim, Seyoung Kim, Chun-Chen Yeh, Vijay Narayanan, Jungwook Choi:
Hardware and software co-optimization for the initialization failure of the ReRAM based cross-bar array. CoRR abs/2002.04605 (2020)
2010 – 2019
- 2019
- [c20]Eduard A. Cartier, Wanki Kim, Nanbo Gong, Tayfun Gokmen, Martin M. Frank, Douglas M. Bishop, Youngseok Kim, Seyoung Kim, Takashi Ando, Ernest Y. Wu, Praneet Adusumilli, John Rozen, Paul M. Solomon, Wilfried Haensch, Matthew J. BrightSky, Abu Sebastian, Geoffrey W. Burr, Vijay Narayanan:
Reliability Challenges with Materials for Analog Computing. IRPS 2019: 1-10 - [i6]Hyungjun Kim, Malte J. Rasch, Tayfun Gokmen, Takashi Ando, Hiroyuki Miyazoe, Jae-Joon Kim, John Rozen, Seyoung Kim:
Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays. CoRR abs/1907.10228 (2019) - 2018
- [c19]Seongwoo Kim, Seyoung Kim, Kwang Ryel Ryu:
Deep Learning Experiments with Skewed Data for Defect Prediction in Plastic Injection Molding. AICCSA 2018: 1-2 - [c18]Seyoung Kim, Kwang Ryel Ryu:
Scheduling and Situation-Adaptive Operation for Energy Efficiency of Hot Press Forging Factory. ETFA 2018: 1157-1160 - 2017
- [c17]Haein Shin, Jaehyung Yu, Ji Hye Shin, Yongsik Jeong, Seyoung Kim, Gilljae Lee:
Spectral response of romaine lettuce by uptake of ZN. IGARSS 2017: 6162-6165 - [c16]Ji Hye Shin, Jaehyung Yu, Seyoung Kim, Haein Shin, Sang-Mo Koh:
Relationship between spectral reflectance and metal content of Korean pine needles as a metal contamination indicator. IGARSS 2017: 6166-6169 - [c15]Seyoung Kim, Tayfun Gokmen, Hyung-Min Lee, Wilfried E. Haensch:
Analog CMOS-based resistive processing unit for deep neural network training. MWSCAS 2017: 422-425 - [i5]Seyoung Kim, Tayfun Gokmen, Hyung-Min Lee, Wilfried E. Haensch:
Analog CMOS-based Resistive Processing Unit for Deep Neural Network Training. CoRR abs/1706.06620 (2017) - 2016
- [c14]Calvin McCarter, Seyoung Kim:
Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models. AISTATS 2016: 528-537 - 2014
- [j8]Seyoung Kim, Eric P. Xing:
Exploiting Genome Structure in Association Analysis. J. Comput. Biol. 21(4): 345-360 (2014) - [j7]Lingxue Zhang, Seyoung Kim:
Learning Gene Networks under SNP Perturbations Using eQTL Datasets. PLoS Comput. Biol. 10(2) (2014) - [c13]Calvin McCarter, Seyoung Kim:
On Sparse Gaussian Chain Graph Models. NIPS 2014: 3212-3220 - [c12]Sangheun Shim, Seyoung Kim, Yong Man Ro:
High resolution image formation method based on the realistic spaceborne SAR modeling and simulation. SAR 2014: 924316 - 2013
- [c11]Jing Xiang, Seyoung Kim:
A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables. NIPS 2013: 2418-2426 - 2012
- [c10]Seyoung Kim, Sheldon S. Williamson:
Negative impedance instability compensation in buck converter using state space pole placement control. CCECE 2012: 1-5 - [c9]Kyung-Ah Sohn, Seyoung Kim:
Joint Estimation of Structured Sparsity and Output Structure in Multiple-Output Regression via Inverse-Covariance Regularization. AISTATS 2012: 1081-1089 - [i4]Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing:
Smoothing Proximal Gradient Method for General Structured Sparse Learning. CoRR abs/1202.3708 (2012) - [i3]Seyoung Kim, Padhraic Smyth, Stefan Luther:
Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models. CoRR abs/1207.4143 (2012) - 2011
- [c8]Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing:
Smoothing Proximal Gradient Method for General Structured Sparse Learning. UAI 2011: 105-114 - 2010
- [j6]Kriti Puniyani, Seyoung Kim, Eric P. Xing:
Multi-population GWA mapping via multi-task regularized regression. Bioinform. 26(12): 208-216 (2010) - [j5]Sanjay Kumar Banerjee, Leonard Franklin Register, Emanuel Tutuc, Dipanjan Basu, Seyoung Kim, Dharmendar Reddy, Allan H. MacDonald:
Graphene for CMOS and Beyond CMOS Applications. Proc. IEEE 98(12): 2032-2046 (2010) - [j4]Seyoung Kim, Padhraic Smyth, Hal S. Stern:
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data. IEEE Trans. Medical Imaging 29(6): 1260-1274 (2010) - [c7]Seyoung Kim, Eric P. Xing:
Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity. ICML 2010: 543-550 - [i2]Xi Chen, Seyoung Kim, Qihang Lin, Jaime G. Carbonell, Eric P. Xing:
Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso. CoRR abs/1005.3579 (2010) - [i1]Xi Chen, Qihang Lin, Seyoung Kim, Javier Peña, Jaime G. Carbonell, Eric P. Xing:
An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity. CoRR abs/1005.4717 (2010)
2000 – 2009
- 2009
- [j3]Seyoung Kim, Kyung-Ah Sohn, Eric P. Xing:
A multivariate regression approach to association analysis of a quantitative trait network. Bioinform. 25(12) (2009) - [c6]Xiaolin Yang, Seyoung Kim, Eric P. Xing:
Heterogeneous multitask learning with joint sparsity constraints. NIPS 2009: 2151-2159 - 2008
- [c5]Seyoung Kim, Eric P. Xing:
Feature Selection via Block-Regularized Regression. UAI 2008: 325-332 - 2006
- [j2]Seyoung Kim, Padhraic Smyth:
Segmental Hidden Markov Models with Random Effects for Waveform Modeling. J. Mach. Learn. Res. 7: 945-969 (2006) - [c4]Seyoung Kim, Padhraic Smyth, Hal S. Stern:
A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data. MICCAI (2) 2006: 217-224 - [c3]Seyoung Kim, Padhraic Smyth:
Hierarchical Dirichlet Processes with Random Effects. NIPS 2006: 697-704 - 2005
- [c2]Seyoung Kim, Padhraic Smyth, Hal S. Stern, Jessica A. Turner:
Parametric Response Surface Models for Analysis of Multi-site fMRI Data. MICCAI 2005: 352-359 - 2004
- [c1]Seyoung Kim, Padhraic Smyth, Stefan Luther:
Modeling Waveform Shapes with Random E ects Segmental Hidden Markov Models. UAI 2004: 309-316
1990 – 1999
- 1991
- [j1]Seyoung Kim, John J. Metzner:
Performance improvement of a frequency hopping-CDMA system utilizing memorized prior data. IEEE Trans. Commun. 39(4): 496-502 (1991)
Coauthor Index
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