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2020 – today
- 2024
[j16]Hyeonah Kim
, Jinkyoo Park, Changhyun Kwon:
A Neural Separation Algorithm for the Rounded Capacity Inequalities. INFORMS J. Comput. 36(4): 987-1005 (2024)- [j15]Hadi Charkhgard, Jinkyoo Park, Changhyun Kwon:
Special issue on advances in computational optimization and their modern applications. Optim. Lett. 18(9): 1961-1962 (2024) - [j14]Alexandros E. Tzikas, Jinkyoo Park, Mykel J. Kochenderfer, Ross E. Allen:
Distributed Online Planning for Min-Max Problems in Networked Markov Games. IEEE Robotics Autom. Lett. 9(7): 6656-6663 (2024) - [j13]Jiachen Li, David Isele, Kanghoon Lee, Jinkyoo Park, Kikuo Fujimura, Mykel J. Kochenderfer:
Interactive Autonomous Navigation With Internal State Inference and Interactivity Estimation. IEEE Trans. Robotics 40: 2932-2949 (2024) - [c42]Jiwoo Son, Minsu Kim, Sanghyeok Choi, Hyeonah Kim, Jinkyoo Park:
Equity-Transformer: Solving NP-Hard Min-Max Routing Problems as Sequential Generation with Equity Context. AAAI 2024: 20265-20273 - [c41]Shiqi Lei, Kanghoon Lee, Linjing Li, Jinkyoo Park, Jiachen Li:
ELA: Exploited Level Augmentation for Offline Learning in Zero-Sum Games. AAMAS 2024: 2357-2359 - [c40]Huijie Tang, Federico Berto, Zihan Ma, Chuanbo Hua, Kyuree Ahn, Jinkyoo Park:
HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfinding. AAMAS 2024: 2498-2500 - [c39]Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park:
Local Search GFlowNets. ICLR 2024 - [c38]Hyeonah Kim, Minsu Kim, Sungsoo Ahn, Jinkyoo Park:
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization. ICML 2024 - [c37]Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woochang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio:
Learning to Scale Logits for Temperature-Conditional GFlowNets. ICML 2024 - [c36]Taeyoung Yun, Kanghoon Lee, Sujin Yun, Ilmyung Kim, Won-Woo Jung, Min-Cheol Kwon, Kyujin Choi, Yoohyeon Lee, Jinkyoo Park:
An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems. KDD 2024: 6202-6213 - [i63]Jiachen Li, Chuanbo Hua, Hengbo Ma, Jinkyoo Park, Victoria Magdalena Dax, Mykel J. Kochenderfer:
Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation. CoRR abs/2401.12275 (2024) - [i62]Hyeonah Kim, Minsu Kim, Sanghyeok Choi, Jinkyoo Park:
Genetic-guided GFlowNets: Advancing in Practical Molecular Optimization Benchmark. CoRR abs/2402.05961 (2024) - [i61]Nayoung Kim, Minsu Kim, Jinkyoo Park:
Anfinsen Goes Neural: a Graphical Model for Conditional Antibody Design. CoRR abs/2402.05982 (2024) - [i60]Huijie Tang, Federico Berto, Zihan Ma, Chuanbo Hua, Kyuree Ahn, Jinkyoo Park:
HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfinding. CoRR abs/2402.15546 (2024) - [i59]Shiqi Lei, Kanghoon Lee, Linjing Li, Jinkyoo Park, Jiachen Li:
ELA: Exploited Level Augmentation for Offline Learning in Zero-Sum Games. CoRR abs/2402.18617 (2024) - [i58]Minsu Kim, Sanghyeok Choi, Jiwoo Son, Hyeonah Kim, Jinkyoo Park, Yoshua Bengio:
Ant Colony Sampling with GFlowNets for Combinatorial Optimization. CoRR abs/2403.07041 (2024) - [i57]Huijie Tang, Federico Berto, Jinkyoo Park:
Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding. CoRR abs/2403.07559 (2024) - [i56]Hyosoon Jang, Yunhui Jang, Minsu Kim, Jinkyoo Park, Sungsoo Ahn:
Pessimistic Backward Policy for GFlowNets. CoRR abs/2405.16012 (2024) - [i55]Jaewoo Lee, Sujin Yun, Taeyoung Yun, Jinkyoo Park:
GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning. CoRR abs/2405.16907 (2024) - [i54]Alexandros E. Tzikas, Jinkyoo Park, Mykel J. Kochenderfer, Ross E. Allen:
Distributed Online Planning for Min-Max Problems in Networked Markov Games. CoRR abs/2405.19570 (2024) - [i53]Federico Berto, Chuanbo Hua, Nayeli Gast Zepeda, André Hottung, Niels A. Wouda, Leon Lan, Kevin Tierney, Jinkyoo Park:
RouteFinder: Towards Foundation Models for Vehicle Routing Problems. CoRR abs/2406.15007 (2024) - [i52]Taeyoung Yun, Sujin Yun, Jaewoo Lee, Jinkyoo Park:
Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization. CoRR abs/2407.01624 (2024) - [i51]Taeyoung Yun, Kanghoon Lee, Sujin Yun, Ilmyung Kim, Won-Woo Jung, Min-Cheol Kwon, Kyujin Choi, Yoohyeon Lee, Jinkyoo Park:
An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems. CoRR abs/2408.07327 (2024) - [i50]Federico Berto, Chuanbo Hua, Laurin Luttmann, Jiwoo Son, Junyoung Park, Kyuree Ahn, Changhyun Kwon, Lin Xie, Jinkyoo Park:
PARCO: Learning Parallel Autoregressive Policies for Efficient Multi-Agent Combinatorial Optimization. CoRR abs/2409.03811 (2024) - [i49]Shiqi Lei, Kanghon Lee, Linjing Li, Jinkyoo Park:
Learning Strategy Representation for Imitation Learning in Multi-Agent Games. CoRR abs/2409.19363 (2024) - [i48]Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio:
Adaptive teachers for amortized samplers. CoRR abs/2410.01432 (2024) - 2023
- [j12]Jiyoung Jung, Kundo Park, Byungjin Cho, Jinkyoo Park, Seunghwa Ryu:
Optimization of injection molding process using multi-objective bayesian optimization and constrained generative inverse design networks. J. Intell. Manuf. 34(8): 3623-3636 (2023) - [c35]Yohan Jung, Jinkyoo Park:
Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior. AISTATS 2023: 3795-3824 - [c34]Junyoung Park, Changhyun Kwon, Jinkyoo Park:
Learn to Solve the Min-max Multiple Traveling Salesmen Problem with Reinforcement Learning. AAMAS 2023: 878-886 - [c33]Minjun Kim, Junyoung Park, Jinkyoo Park:
Learning to CROSS exchange to solve min-max vehicle routing problems. ICLR 2023 - [c32]Haeyeon Kim, Minsu Kim, Federico Berto, Joungho Kim, Jinkyoo Park:
DevFormer: A Symmetric Transformer for Context-Aware Device Placement. ICML 2023: 16541-16566 - [c31]Jiwoo Son, Minsu Kim, Hyeonah Kim, Jinkyoo Park:
Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization. ICML 2023: 32194-32210 - [c30]Kyuree Ahn, Heemang Park, Jinkyoo Park:
Learning to Schedule in Multi-Agent Pathfinding. IROS 2023: 7326-7332 - [c29]Kanghoon Lee, Jiachen Li, David Isele, Jinkyoo Park, Kikuo Fujimura, Mykel J. Kochenderfer:
Robust Driving Policy Learning with Guided Meta Reinforcement Learning. ITSC 2023: 4114-4120 - [c28]Kanghoon Yoon, Youngjun Im, Jingyu Choi, Taehwan Jeong, Jinkyoo Park:
Learning Multivariate Hawkes Process via Graph Recurrent Neural Network. KDD 2023: 5451-5462 - [c27]Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park:
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks. NeurIPS 2023 - [c26]Minsu Kim, Federico Berto, Sungsoo Ahn, Jinkyoo Park:
Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences. NeurIPS 2023 - [i47]Vivian Wen Hui Wong, Sang Hun Kim, Junyoung Park, Jinkyoo Park, Kincho H. Law:
Generating Dispatching Rules for the Interrupting Swap-Allowed Blocking Job Shop Problem Using Graph Neural Network and Reinforcement Learning. CoRR abs/2302.02506 (2023) - [i46]Hyeonah Kim, Minsu Kim, Sungsoo Ahn, Jinkyoo Park:
Symmetric Exploration in Combinatorial Optimization is Free! CoRR abs/2306.01276 (2023) - [i45]Jiwoo Son, Minsu Kim, Hyeonah Kim, Jinkyoo Park:
Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization. CoRR abs/2306.02688 (2023) - [i44]Jiwoo Son, Minsu Kim, Sanghyeok Choi, Jinkyoo Park:
Solving NP-hard Min-max Routing Problems as Sequential Generation with Equity Context. CoRR abs/2306.02689 (2023) - [i43]Minsu Kim, Federico Berto, Sungsoo Ahn, Jinkyoo Park:
Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences. CoRR abs/2306.03111 (2023) - [i42]Jaeyeon Jo, Jihwan Yu, Jinkyoo Park:
Computing Algorithm for an Equilibrium of the Generalized Stackelberg Game. CoRR abs/2306.05732 (2023) - [i41]Federico Berto, Chuanbo Hua, Junyoung Park, Minsu Kim, Hyeonah Kim, Jiwoo Son, Haeyeon Kim, Joungho Kim, Jinkyoo Park:
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark. CoRR abs/2306.17100 (2023) - [i40]Hyeonah Kim, Jinkyoo Park, Changhyun Kwon:
A Neural Separation Algorithm for the Rounded Capacity Inequalities. CoRR abs/2306.17283 (2023) - [i39]Kanghoon Lee, Jiachen Li, David Isele, Jinkyoo Park, Kikuo Fujimura, Mykel J. Kochenderfer:
Robust Driving Policy Learning with Guided Meta Reinforcement Learning. CoRR abs/2307.10160 (2023) - [i38]Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park:
Local Search GFlowNets. CoRR abs/2310.02710 (2023) - [i37]Minsu Kim, Joohwan Ko, Dinghuai Zhang, Ling Pan, Taeyoung Yun, Woochang Kim, Jinkyoo Park, Yoshua Bengio:
Learning to Scale Logits for Temperature-Conditional GFlowNets. CoRR abs/2310.02823 (2023) - [i36]Abhay Sobhanan, Junyoung Park, Jinkyoo Park, Changhyun Kwon:
Genetic Algorithms with Neural Cost Predictor for Solving Hierarchical Vehicle Routing Problems. CoRR abs/2310.14157 (2023) - [i35]Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park:
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks. CoRR abs/2310.16397 (2023) - [i34]Jiachen Li, David Isele, Kanghoon Lee, Jinkyoo Park, Kikuo Fujimura, Mykel J. Kochenderfer:
Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimation. CoRR abs/2311.16091 (2023) - 2022
- [j11]Stefano Massaroli, Michael Poli, Stefano Peluchetti, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Learning Stochastic Optimal Policies via Gradient Descent. IEEE Control. Syst. Lett. 6: 1094-1099 (2022) - [j10]Yohan Jung, Jinkyoo Park:
Scalable Inference for Hybrid Bayesian Hidden Markov Model Using Gaussian Process Emission. J. Comput. Graph. Stat. 31(3): 666-683 (2022) - [j9]Stefano Massaroli, Michael Poli, Federico Califano, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Optimal Energy Shaping via Neural Approximators. SIAM J. Appl. Dyn. Syst. 21(3): 2126-2147 (2022) - [c25]Heechang Ryu, Hayong Shin, Jinkyoo Park:
REMAX: Relational Representation for Multi-Agent Exploration. AAMAS 2022: 1137-1145 - [c24]Federico Berto, Stefano Massaroli, Michael Poli, Jinkyoo Park:
Neural Solvers for Fast and Accurate Numerical Optimal Control. ICLR 2022 - [c23]Junyoung Park, Jinhyun Choo, Jinkyoo Park:
Convergent Graph Solvers. ICLR 2022 - [c22]Yohan Jung, Kyungwoo Song, Jinkyoo Park:
Efficient Approximate Inference for Stationary Kernel on Frequency Domain. ICML 2022: 10502-10538 - [c21]Hyunwook Kang, Taehwan Kwon, Jinkyoo Park, James R. Morrison:
Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning. NeurIPS 2022 - [c20]Minsu Kim, Junyoung Park, Jinkyoo Park:
Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization. NeurIPS 2022 - [c19]Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon:
Transform Once: Efficient Operator Learning in Frequency Domain. NeurIPS 2022 - [i33]Federico Berto, Stefano Massaroli, Michael Poli, Jinkyoo Park:
Neural Solvers for Fast and Accurate Numerical Optimal Control. CoRR abs/2203.08072 (2022) - [i32]Minsu Kim, Junyoung Park, Jinkyoo Park:
Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization. CoRR abs/2205.13209 (2022) - [i31]Haeyeon Kim, Minsu Kim, Joungho Kim, Jinkyoo Park:
Collaborative Distillation Meta Learning for Simulation Intensive Hardware Design. CoRR abs/2205.13225 (2022) - [i30]Junyoung Park, Federico Berto, Arec L. Jamgochian, Mykel J. Kochenderfer, Jinkyoo Park:
Meta-SysId: A Meta-Learning Approach for Simultaneous Identification and Prediction. CoRR abs/2206.00694 (2022) - [i29]Minjun Kim, Junyoung Park, Jinkyoo Park:
Neuro CROSS exchange: Learning to CROSS exchange to solve realistic vehicle routing problems. CoRR abs/2206.02771 (2022) - [i28]Jiachen Li, Chuanbo Hua, Jinkyoo Park, Hengbo Ma, Victoria Magdalena Dax, Mykel J. Kochenderfer:
EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction. CoRR abs/2208.05470 (2022) - [i27]Yohan Jung, Jinkyoo Park:
Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior. CoRR abs/2210.12363 (2022) - [i26]Haewon Jung, Junyoung Park, Jinkyoo Park:
Learning context-aware adaptive solvers to accelerate quadratic programming. CoRR abs/2211.12443 (2022) - [i25]Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon:
Transform Once: Efficient Operator Learning in Frequency Domain. CoRR abs/2211.14453 (2022) - 2021
- [j8]Kyuree Ahn, Jinkyoo Park:
Cooperative zone-based rebalancing of idle overhead hoist transportations using multi-agent reinforcement learning with graph representation learning. IISE Trans. 53(10): 1140-1156 (2021) - [j7]Junyoung Park, Jaehyeong Chun, Sang Hun Kim, Youngkook Kim, Jinkyoo Park:
Learning to schedule job-shop problems: representation and policy learning using graph neural network and reinforcement learning. Int. J. Prod. Res. 59(11): 3360-3377 (2021) - [c18]Heechang Ryu, Hayong Shin, Jinkyoo Park:
Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning. AAMAS 2021: 1091-1099 - [c17]Jaehyuk Yi, Jinkyoo Park:
Semi-supervised Bearing Fault Diagnosis with Adversarially-Trained Phase-Consistent Network. KDD 2021: 3875-3885 - [c16]Michael Poli, Stefano Massaroli, Luca Scimeca, Sanghyuk Chun, Seong Joon Oh, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg:
Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions. NeurIPS 2021: 9977-9989 - [c15]Minsu Kim, Jinkyoo Park, Joungho Kim:
Learning Collaborative Policies to Solve NP-hard Routing Problems. NeurIPS 2021: 10418-10430 - [c14]Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Differentiable Multiple Shooting Layers. NeurIPS 2021: 16532-16544 - [i24]Stefano Massaroli, Michael Poli, Federico Califano, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Optimal Energy Shaping via Neural Approximators. CoRR abs/2101.05537 (2021) - [i23]Heechang Ryu, Hayong Shin, Jinkyoo Park:
Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning. CoRR abs/2101.06890 (2021) - [i22]Fangying Chen, Junyoung Park, Jinkyoo Park:
A Hypergraph Convolutional Neural Network for Molecular Properties Prediction using Functional Group. CoRR abs/2106.01028 (2021) - [i21]Junyoung Park, Jaehyeong Chun, Sang-Hun Kim, Youngkook Kim, Jinkyoo Park:
Learning to schedule job-shop problems: Representation and policy learning using graph neural network and reinforcement learning. CoRR abs/2106.01086 (2021) - [i20]Junyoung Park, Jinhyun Choo, Jinkyoo Park:
Convergent Graph Solvers. CoRR abs/2106.01680 (2021) - [i19]Junyoung Park, Sanjar Bakhtiyar, Jinkyoo Park:
ScheduleNet: Learn to solve multi-agent scheduling problems with reinforcement learning. CoRR abs/2106.03051 (2021) - [i18]Stefano Massaroli, Michael Poli, Stefano Peluchetti, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Learning Stochastic Optimal Policies via Gradient Descent. CoRR abs/2106.03780 (2021) - [i17]Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Differentiable Multiple Shooting Layers. CoRR abs/2106.03885 (2021) - [i16]Michael Poli, Stefano Massaroli, Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg:
Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions. CoRR abs/2106.04165 (2021) - [i15]Michael Poli, Stefano Massaroli, Clayton M. Rabideau, Junyoung Park, Atsushi Yamashita, Hajime Asama, Jinkyoo Park:
Continuous-Depth Neural Models for Dynamic Graph Prediction. CoRR abs/2106.11581 (2021) - [i14]Minsu Kim, Jinkyoo Park, Joungho Kim:
Learning Collaborative Policies to Solve NP-hard Routing Problems. CoRR abs/2110.13987 (2021) - 2020
- [j6]Joonho Bae, Jinkyoo Park:
Count-based change point detection via multi-output log-Gaussian Cox processes. IISE Trans. 52(9): 998-1013 (2020) - [j5]Woojin Cho, Youngrae Kim, Jinkyoo Park:
Hierarchical Anomaly Detection Using a Multioutput Gaussian Process. IEEE Trans Autom. Sci. Eng. 17(1): 261-272 (2020) - [j4]Jaeyeon Jo, Jinkyoo Park:
Demand-Side Management With Shared Energy Storage System in Smart Grid. IEEE Trans. Smart Grid 11(5): 4466-4476 (2020) - [c13]Heechang Ryu, Hayong Shin, Jinkyoo Park:
Multi-Agent Actor-Critic with Hierarchical Graph Attention Network. AAAI 2020: 7236-7243 - [c12]Jaehyuk Yi, Jinkyoo Park:
Hypergraph Convolutional Recurrent Neural Network. KDD 2020: 3366-3376 - [c11]Stefano Massaroli, Michael Poli, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Dissecting Neural ODEs. NeurIPS 2020 - [c10]Michael Poli, Stefano Massaroli, Atsushi Yamashita, Hajime Asama, Jinkyoo Park:
Hypersolvers: Toward Fast Continuous-Depth Models. NeurIPS 2020 - [i13]Yohan Jung, Jinkyoo Park:
Scalable Hybrid HMM with Gaussian Process Emission for Sequential Time-series Data Clustering. CoRR abs/2001.01917 (2020) - [i12]Stefano Massaroli, Michael Poli, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Dissecting Neural ODEs. CoRR abs/2002.08071 (2020) - [i11]Stefano Massaroli, Michael Poli, Michelangelo Bin, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Stable Neural Flows. CoRR abs/2003.08063 (2020) - [i10]Yohan Jung, Kyungwoo Song, Jinkyoo Park:
Approximate Inference for Spectral Mixture Kernel. CoRR abs/2006.07036 (2020) - [i9]Michael Poli, Stefano Massaroli, Atsushi Yamashita, Hajime Asama, Jinkyoo Park:
Hypersolvers: Toward Fast Continuous-Depth Models. CoRR abs/2007.09601 (2020) - [i8]Heechang Ryu, Hayong Shin, Jinkyoo Park:
REMAX: Relational Representation for Multi-Agent Exploration. CoRR abs/2008.05214 (2020) - [i7]Michael Poli, Stefano Massaroli, Atsushi Yamashita, Hajime Asama, Jinkyoo Park:
TorchDyn: A Neural Differential Equations Library. CoRR abs/2009.09346 (2020)
2010 – 2019
- 2019
- [c9]Kyuree Ahn, Jinkyoo Park:
Idle Vehicle Rebalancing in Semiconductor Fabrication Using Factorized Graph Neural Network Reinforcement Learning. CDC 2019: 132-138 - [c8]Stefano Massaroli, Michael Poli, Federico Califano, Angela Faragasso, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Port-Hamiltonian Approach to Neural Network Training. CDC 2019: 6799-6806 - [i6]Hyunwook Kang, Aydar Mynbay, James R. Morrison, Jinkyoo Park:
Scalable and transferable learning of algorithms via graph embedding for multi-robot reward collection. CoRR abs/1905.12204 (2019) - [i5]Stefano Massaroli, Michael Poli, Federico Califano, Angela Faragasso, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Port-Hamiltonian Approach to Neural Network Training. CoRR abs/1909.02702 (2019) - [i4]Michael Poli, Jinkyoo Park, Ilija Ilievski:
WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series. CoRR abs/1909.10801 (2019) - [i3]Heechang Ryu, Hayong Shin, Jinkyoo Park:
Multi-Agent Actor-Critic with Hierarchical Graph Attention Network. CoRR abs/1909.12557 (2019) - [i2]Michael Poli, Stefano Massaroli, Junyoung Park, Atsushi Yamashita, Hajime Asama, Jinkyoo Park:
Graph Neural Ordinary Differential Equations. CoRR abs/1911.07532 (2019) - 2018
- [c7]Jinkyoo Park, Max Ferguson, Kincho H. Law:
Data Driven Analytics (Machine Learning) for System Characterization, Diagnostics and Control Optimization. EG-ICE 2018: 16-36 - [c6]Seongcheol Woo, Juneyeong Yeon, Mingi Ji, Il-Chul Moon, Jinkyoo Park:
Deep Reinforcement Learning with Fully Convolutional Neural Network to Solve an Earthwork Scheduling Problem. SMC 2018: 4236-4242 - [i1]Heechang Ryu, Hayong Shin, Jinkyoo Park:
Multi-Agent Actor-Critic with Generative Cooperative Policy Network. CoRR abs/1810.09206 (2018) - 2016
- [j3]Jinkyoo Park, Kincho H. Law:
Bayesian Ascent: A Data-Driven Optimization Scheme for Real-Time Control With Application to Wind Farm Power Maximization. IEEE Trans. Control. Syst. Technol. 24(5): 1655-1668 (2016) - [c5]Jinkyoo Park, Soon-Duck Kwon, Kincho H. Law:
A data-driven approach for cooperative wind farm control. ACC 2016: 525-530 - [c4]Max Ferguson, Kincho H. Law, Raunak Bhinge, David Dornfeld, Jinkyoo Park, Yung-Tsun Tina Lee:
Evaluation of a PMML-based GPR scoring engine on a cloud platform and microcomputer board for smart manufacturing. IEEE BigData 2016: 2014-2023 - [c3]Heechang Ryu, Jinkyoo Park, Hayong Shin:
Classification of Heart Sound Recordings Using Convolution Neural Network. CinC 2016 - 2015
- [j2]Jinkyoo Park, Kay Smarsly, Kincho H. Law, Dietrich Hartmann:
Erratum for "Analyzing the Temporal Variation of Wind Turbine Responses Using Gaussian Mixture Model and Gaussian Discriminant Analysis" by J. Park, K. Smarsly, K. H. Law, and D. Hartmann. J. Comput. Civ. Eng. 29(2) (2015) - [j1]Jinkyoo Park, Kay Smarsly, Kincho H. Law, Dietrich Hartmann:
Analyzing the Temporal Variation of Wind Turbine Responses Using Gaussian Mixture Model and Gaussian Discriminant Analysis. J. Comput. Civ. Eng. 29(4) (2015) - [c2]Jinkyoo Park, Kincho H. Law, Raunak Bhinge, Mason Chen, David Dornfeld, Sudarsan Rachuri:
Real-time energy prediction for a milling machine tool using sparse Gaussian process regression. IEEE BigData 2015: 1451-1460 - 2014
- [c1]Raunak Bhinge, Nishant Biswas, David Dornfeld, Jinkyoo Park, Kincho H. Law, Moneer Helu, Sudarsan Rachuri:
An intelligent machine monitoring system for energy prediction using a Gaussian Process regression. IEEE BigData 2014: 978-986
Coauthor Index
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last updated on 2024-11-11 22:27 CET by the dblp team
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