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Linnan Wang
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2020 – today
- 2024
- [j3]Yiyang Zhao, Linnan Wang, Tian Guo:
Multi-Objective Neural Architecture Search by Learning Search Space Partitions. J. Mach. Learn. Res. 25: 177:1-177:41 (2024) - [i16]Yiyang Zhao, Linnan Wang, Tian Guo:
Multi-objective Neural Architecture Search by Learning Search Space Partitions. CoRR abs/2406.00291 (2024) - 2022
- [b1]Linnan Wang:
Building an Intelligent Agent to Design Neural Networks. Brown University, USA, 2022 - [j2]Linnan Wang
, Saining Xie, Teng Li
Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5503-5515 (2022) - [c15]Linnan Wang, Chenhan Yu, Satish Salian, Slawomir Kierat, Szymon Migacz, Alex Fit-Florea:
Searching the Deployable Convolution Neural Networks for GPUs. CVPR 2022: 12217-12226 - [c14]Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo
Multi-objective Optimization by Learning Space Partition. ICLR 2022 - [i15]Linnan Wang, Chenhan Yu, Satish Salian, Slawomir Kierat, Szymon Migacz, Alex Fit-Florea:
GPUNet: Searching the Deployable Convolution Neural Networks for GPUs. CoRR abs/2205.00841 (2022) - 2021
- [c13]Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo:
Few-Shot Neural Architecture Search. ICML 2021: 12707-12718 - [c12]Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian:
Learning Space Partitions for Path Planning. NeurIPS 2021: 378-391 - [i14]Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian:
Learning Space Partitions for Path Planning. CoRR abs/2106.10544 (2021) - [i13]Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian:
Multi-objective Optimization by Learning Space Partitions. CoRR abs/2110.03173 (2021) - 2020
- [c11]Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca:
Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search. AAAI 2020: 9983-9991 - [c10]Linnan Wang, Wei Wu, Junyu Zhang, Hang Liu, George Bosilca, Maurice Herlihy, Rodrigo Fonseca:
FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Networks. HPDC 2020: 113-124 - [c9]Linnan Wang, Rodrigo Fonseca, Yuandong Tian:
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. NeurIPS 2020 - [i12]Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo:
Few-shot Neural Architecture Search. CoRR abs/2006.06863 (2020) - [i11]Linnan Wang, Rodrigo Fonseca, Yuandong Tian:
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. CoRR abs/2007.00708 (2020)
2010 – 2019
- 2019
- [i10]Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca:
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. CoRR abs/1903.11059 (2019) - [i9]Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian:
Sample-Efficient Neural Architecture Search by Learning Action Space. CoRR abs/1906.06832 (2019) - 2018
- [c8]Jinmian Ye, Linnan Wang, Guangxi Li, Di Chen, Shandian Zhe, Xinqi Chu, Zenglin Xu:
Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition. CVPR 2018: 9378-9387 - [c7]Xi Luo, Wei Wu
ADAPT: an event-based adaptive collective communication framework. HPDC 2018: 118-130 - [c6]Ang Li, Weifeng Liu
Warp-Consolidation: A Novel Execution Model for GPUs. ICS 2018: 53-64 - [c5]Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu
Superneurons: dynamic GPU memory management for training deep neural networks. PPoPP 2018: 41-53 - [i8]Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu, Ang Li, Shuaiwen Leon Song, Zenglin Xu, Tim Kraska:
SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks. CoRR abs/1801.04380 (2018) - [i7]Linnan Wang, Yiyang Zhao, Yuu Jinnai:
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. CoRR abs/1805.07440 (2018) - [i6]Linnan Wang, Wei Wu, Yiyang Zhao, Junyu Zhang, Hang Liu, George Bosilca, Jack J. Dongarra, Maurice Herlihy, Rodrigo Fonseca:
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks. CoRR abs/1811.08596 (2018) - 2017
- [j1]Linnan Wang
Accelerating deep neural network training with inconsistent stochastic gradient descent. Neural Networks 93: 219-229 (2017) - [c4]Carsten Binnig
Towards Interactive Data Exploration. BIRTE (Revised Selected Papers) 2017: 177-190 - [c3]Guangxi Li, Zenglin Xu, Linnan Wang, Jinmian Ye, Irwin King
Simple and efficient parallelization for probabilistic temporal tensor factorization. IJCNN 2017: 1-8 - [c2]Yiyang Zhao, Linnan Wang, Wei Wu
Efficient Communications in Training Large Scale Neural Networks. ACM Multimedia (Thematic Workshops) 2017: 110-116 - [i5]Jinmian Ye, Linnan Wang, Guangxi Li, Di Chen, Shandian Zhe, Xinqi Chu, Zenglin Xu:
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition. CoRR abs/1712.05134 (2017) - 2016
- [c1]Linnan Wang, Wei Wu
BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing. ICS 2016: 20:1-20:11 - [i4]Linnan Wang, Yi Yang, Martin Renqiang Min, Srimat T. Chakradhar:
Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent. CoRR abs/1603.05544 (2016) - [i3]Guangxi Li, Zenglin Xu, Linnan Wang, Jinmian Ye, Irwin King, Michael R. Lyu:
Simple and Efficient Parallelization for Probabilistic Temporal Tensor Factorization. CoRR abs/1611.03578 (2016) - 2015
- [i2]Linnan Wang, Wei Wu, Jianxiong Xiao, Yi Yang:
BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing. CoRR abs/1510.05041 (2015) - [i1]Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi:
Large Scale Artificial Neural Network Training Using Multi-GPUs. CoRR abs/1511.04348 (2015)
Coauthor Index
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