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Jialin Song
Jialin Song
Research Scientist, NVIDIA
nvidia.com의 이메일 확인됨 - 홈페이지
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Onsets and frames: Dual-objective piano transcription
C Hawthorne, E Elsen, J Song, A Roberts, I Simon, C Raffel, J Engel, ...
ISMIR 2018, 2017
3302017
A general framework for multi-fidelity bayesian optimization with gaussian processes
J Song, Y Chen, Y Yue
AISTATS 2019, 2018
1242018
A general large neighborhood search framework for solving integer linear programs
J Song, Y Yue, B Dilkina
Advances in Neural Information Processing Systems 33, 20012-20023, 2020
572020
Learning to search via retrospective imitation
J Song, R Lanka, A Zhao, A Bhatnagar, Y Yue, M Ono
arXiv preprint arXiv:1804.00846, 2018
352018
Machine learning based path planning for improved rover navigation
N Abcouwer, S Daftry, T Del Sesto, O Toupet, M Ono, S Venkatraman, ...
2021 IEEE Aerospace Conference (50100), 1-9, 2021
292021
Co-training for Policy Learning
J Song, R Lanka, Y Yue, M Ono
Conference on Uncertainty in Artificial Intelligence, 2019
192019
Mlnav: Learning to safely navigate on martian terrains
S Daftry, N Abcouwer, T Del Sesto, S Venkatraman, J Song, L Igel, A Byon, ...
IEEE Robotics and Automation Letters 7 (2), 5461-5468, 2022
162022
Learning to Make Decisions via Submodular Regularization
A Alieva, A Aceves, J Song, S Mayo, Y Yue, Y Chen
International Conference on Learning Representations (ICLR), 2021
122021
Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes
J Song, YS Tokpanov, Y Chen, D Fleischman, KT Fountaine, HA Atwater, ...
Workshop on Machine Learning for Molecules and Materials, NeurIPS 2018, 2018
102018
A general large neighborhood search framework for solving integer programs
J Song, R Lanka, Y Yue, B Dilkina
Annual Conference on Neural Information Processing Systems (NeurIPS), 2020
92020
Multi-task Bayesian Optimization via Gaussian Process Upper Confidence Bound
S Dai, J Song, Y Yue
ICML 2020 Workshop on Real World Experiment Design and Active Learning, 2020
62020
Learning to search via self-imitation with application to risk-aware planning
J Song, R Lanka, A Zhao, Y Yue, M Ono
Workshop on Learning with Limited Labeled Data, NeurIPS 2017, 2017
52017
Deep kernel Bayesian optimization
J Bowden, J Song, Y Chen, Y Yue, TA Desautels
Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2021
42021
Learning regions of interest for Bayesian optimization with adaptive level-set estimation
F Zhang, J Song, JC Bowden, A Ladd, Y Yue, T Desautels, Y Chen
International Conference on Machine Learning, 41579-41595, 2023
22023
Learning pseudo-backdoors for mixed integer programs
A Ferber, J Song, B Dilkina, Y Yue
International Conference on Integration of Constraint Programming …, 2022
22022
Multi-objective Reinforcement Learning with Adaptive Pareto Reset for Prefix Adder Design
J Song, R Roy, J Raiman, R Kirby, N Kant, S Godil, B Catanzaro
Workshop on ML for Systems at NeurIPS 2022, 2022
12022
Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models
J Song, YS Tokpanov, Y Chen, D Fleischman, KT Fountaine, Y Yue, ...
CLEO: Science and Innovations, JTu2D. 6, 2020
12020
Efficient Imitation Learning with Local Trajectory Optimization
J Song, JW Jiang, A Yazdanbakhsh, E Songhori, A Goldie, N Jaitly, ...
ICML 2020 Workshop on Inductive Biases, Invariances and Generalization in RL, 2020
12020
CircuitVAE: Efficient and Scalable Latent Circuit Optimization
J Song, A Swope, R Kirby, R Roy, S Godil, J Raiman, B Catanzaro
arXiv preprint arXiv:2406.09535, 2024
2024
Joint-Space Multi-Robot Motion Planning with Learned Decentralized Heuristics
F Xie, M Dominguez-Kuhne, B Riviere, J Song, W Hönig, SJ Chung, ...
arXiv preprint arXiv:2311.12385, 2023
2023
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