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2020 – today
- 2021
[c8]Wenxing Hong, Jinjie You, Hejia Zhang:
A Survey on Blockchain Application: a Data Collaboration Perspective. ICCSE 2021: 125-132- 2020
- [j3]Ryan Julian, Eric Heiden, Zhanpeng He, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman:
Scaling simulation-to-real transfer by learning a latent space of robot skills. Int. J. Robotics Res. 39(10-11) (2020) - [j2]Manoj Kumar
, Cameron T. Ellis, Qihong Lu, Hejia Zhang, Mihai Capota, Theodore L. Willke, Peter J. Ramadge, Nicholas B. Turk-Browne, Kenneth A. Norman:
BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis. PLoS Comput. Biol. 16(1) (2020) - [j1]Chaoyang Zhu, Kejie Huang, Shuyuan Yang, Ziqi Zhu, Hejia Zhang, Haibin Shen:
An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs. IEEE Trans. Very Large Scale Integr. Syst. 28(9): 1953-1965 (2020) - [c7]Hejia Zhang, Matthew C. Fontaine, Amy K. Hoover, Julian Togelius, Bistra Dilkina, Stefanos Nikolaidis:
Video Game Level Repair via Mixed Integer Linear Programming. AIIDE 2020: 151-158 - [i11]Chaoyang Zhu, Kejie Huang, Shuyuan Yang, Ziqi Zhu, Hejia Zhang, Haibin Shen:
An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs. CoRR abs/2001.01955 (2020) - [i10]Ming Bo Cai, Michael Shvartsman, Anqi Wu, Hejia Zhang, Xia Zhu:
Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis. CoRR abs/2005.04879 (2020) - [i9]Hejia Zhang, Matthew C. Fontaine, Amy K. Hoover, Julian Togelius, Bistra Dilkina, Stefanos Nikolaidis:
Video Game Level Repair via Mixed Integer Linear Programming. CoRR abs/2010.06627 (2020)
2010 – 2019
- 2019
- [c6]Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau:
Multitask Metric Learning: Theory and Algorithm. AISTATS 2019: 3362-3371 - [c5]Hejia Zhang, Po-Jen Lai, Sayan Paul, Suraj Kothawade, Stefanos Nikolaidis:
Learning Collaborative Action Plans from YouTube Videos. ISRR 2019: 208-223 - [c4]Xianjing Liu, Hejia Zhang, Mingkuan Liu, Alan Lu:
System Design of Extreme Multi-label Query Classification using a Hybrid Model. eCOM@SIGIR 2019 - [i8]Eric Heiden, David Millard, Hejia Zhang, Gaurav S. Sukhatme:
Interactive Differentiable Simulation. CoRR abs/1905.10706 (2019) - [i7]Hejia Zhang, Stefanos Nikolaidis:
Robot Learning and Execution of Collaborative Manipulation Plans from YouTube Videos. CoRR abs/1911.10686 (2019) - 2018
- [c3]Hejia Zhang, Po-Hsuan Chen, Peter J. Ramadge:
Transfer Learning on fMRI Datasets. AISTATS 2018: 595-603 - [c2]Ryan Julian, Eric Heiden, Zhanpeng He, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman:
Scaling Simulation-to-Real Transfer by Learning Composable Robot Skills. ISER 2018: 267-279 - [i6]Ryan Julian, Eric Heiden, Zhanpeng He, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman:
Scaling simulation-to-real transfer by learning composable robot skills. CoRR abs/1809.10253 (2018) - [i5]Hejia Zhang, Eric Heiden, Ryan Julian, Zhangpeng He, Joseph J. Lim, Gaurav S. Sukhatme:
Auto-conditioned Recurrent Mixture Density Networks for Complex Trajectory Generation. CoRR abs/1810.00146 (2018) - [i4]Zhanpeng He, Ryan Julian, Eric Heiden, Hejia Zhang, Stefan Schaal, Joseph J. Lim, Gaurav S. Sukhatme, Karol Hausman:
Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations. CoRR abs/1810.02422 (2018) - 2017
- [i3]Hejia Zhang, Xia Zhu, Theodore L. Willke:
Segmenting Brain Tumors with Symmetry. CoRR abs/1711.06636 (2017) - 2016
- [i2]Po-Hsuan Chen, Xia Zhu, Hejia Zhang, Javier S. Turek, Janice Chen, Theodore L. Willke, Uri Hasson, Peter J. Ramadge:
A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation. CoRR abs/1608.04846 (2016) - [i1]Hejia Zhang, Po-Hsuan Chen, Janice Chen, Xia Zhu, Javier S. Turek, Theodore L. Willke, Uri Hasson, Peter J. Ramadge:
A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis. CoRR abs/1609.09432 (2016) - 2015
- [c1]Blaine Rister, Daniel Reiter, Hejia Zhang, Daniel Volz, Mark Horowitz, Refaat E. Gabr, Joseph R. Cavallaro:
Scale- and orientation-invariant keypoints in higher-dimensional data. ICIP 2015: 3490-3494
Coauthor Index
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