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2020 – today
- 2023
[c9]Zihao Ye
, Ruihang Lai, Junru Shao, Tianqi Chen, Luis Ceze:
SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning. ASPLOS (3) 2023: 660-678- [c8]Siyuan Feng, Bohan Hou, Hongyi Jin, Wuwei Lin, Junru Shao, Ruihang Lai, Zihao Ye, Lianmin Zheng, Cody Hao Yu, Yong Yu, Tianqi Chen:
TensorIR: An Abstraction for Automatic Tensorized Program Optimization. ASPLOS (2) 2023: 804-817 - [i11]Cody Hao Yu, Haozheng Fan, Guangtai Huang, Zhen Jia, Yizhi Liu, Jie Wang, Zach Zheng, Yuan Zhou, Haichen Shen, Junru Shao, Mu Li, Yida Wang:
RAF: Holistic Compilation for Deep Learning Model Training. CoRR abs/2303.04759 (2023) - [i10]Ruihang Lai, Junru Shao, Siyuan Feng, Steven S. Lyubomirsky, Bohan Hou, Wuwei Lin, Zihao Ye, Hongyi Jin, Yuchen Jin, Jiawei Liu, Lesheng Jin, Yaxing Cai, Ziheng Jiang, Yong Wu, Sunghyun Park, Prakalp Srivastava, Jared G. Roesch, Todd C. Mowry, Tianqi Chen:
Relax: Composable Abstractions for End-to-End Dynamic Machine Learning. CoRR abs/2311.02103 (2023) - 2022
- [c7]Junru Shao, Xiyou Zhou, Siyuan Feng, Bohan Hou, Ruihang Lai, Hongyi Jin, Wuwei Lin, Masahiro Masuda, Cody Hao Yu, Tianqi Chen:
Tensor Program Optimization with Probabilistic Programs. NeurIPS 2022 - [i9]Junru Shao, Xiyou Zhou, Siyuan Feng, Bohan Hou, Ruihang Lai, Hongyi Jin, Wuwei Lin, Masahiro Masuda, Cody Hao Yu, Tianqi Chen:
Tensor Program Optimization with Probabilistic Programs. CoRR abs/2205.13603 (2022) - [i8]Siyuan Feng, Bohan Hou, Hongyi Jin, Wuwei Lin, Junru Shao, Ruihang Lai, Zihao Ye, Lianmin Zheng, Cody Hao Yu, Yong Yu, Tianqi Chen:
TensorIR: An Abstraction for Automatic Tensorized Program Optimization. CoRR abs/2207.04296 (2022) - [i7]Zihao Ye, Ruihang Lai, Junru Shao, Tianqi Chen, Luis Ceze:
SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning. CoRR abs/2207.04606 (2022) - 2021
- [c6]Lianmin Zheng, Ruochen Liu, Junru Shao, Tianqi Chen, Joseph Gonzalez, Ion Stoica, Ameer Haj-Ali:
TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers. NeurIPS Datasets and Benchmarks 2021
2010 – 2019
- 2019
- [c5]Hongyang Zhang, Junru Shao, Ruslan Salakhutdinov:
Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex. AISTATS 2019: 1099-1109 - 2018
- [i6]Hongyang Zhang, Junru Shao, Ruslan Salakhutdinov:
Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex. CoRR abs/1806.01845 (2018) - 2017
- [j1]Shicong Liu, Junru Shao, Hongtao Lu:
Generalized Residual Vector Quantization and Aggregating Tree for Large Scale Search. IEEE Trans. Multim. 19(8): 1785-1797 (2017) - [c4]Xinya Du, Junru Shao, Claire Cardie:
Learning to Ask: Neural Question Generation for Reading Comprehension. ACL (1) 2017: 1342-1352 - [i5]Xinya Du, Junru Shao, Claire Cardie:
Learning to Ask: Neural Question Generation for Reading Comprehension. CoRR abs/1705.00106 (2017) - 2016
- [c3]Shicong Liu, Junru Shao, Hongtao Lu:
Aggregating Tree for Searching in Billion Scale High Dimensional Data. ICDM Workshops 2016: 748-755 - [c2]Shicong Liu, Junru Shao, Hongtao Lu:
Generalized residual vector quantization for large scale data. ICME 2016: 1-6 - [c1]Shicong Liu, Junru Shao, Hongtao Lu:
Accelerated distance computation with encoding tree/forest for high dimensional data. ICMLC 2016: 495-501 - [i4]Shicong Liu, Junru Shao, Hongtao Lu:
Generalized residual vector quantization for large scale data. CoRR abs/1609.05345 (2016) - 2015
- [i3]Shicong Liu, Junru Shao, Hongtao Lu:
Accelerated Distance Computation with Encoding Tree for High Dimensional Data. CoRR abs/1509.05186 (2015) - [i2]Shicong Liu, Junru Shao, Hongtao Lu:
HCLAE: High Capacity Locally Aggregating Encodings for Approximate Nearest Neighbor Search. CoRR abs/1509.05194 (2015) - [i1]Shicong Liu, Hongtao Lu, Junru Shao:
Improved Residual Vector Quantization for High-dimensional Approximate Nearest Neighbor Search. CoRR abs/1509.05195 (2015)
Coauthor Index
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