Linnan Wang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 31

Top Topics

Neural Architecture

Monte Carlo Tree Search

Top Venues

Publications

Yiyang Zhao, Linnan Wang, Tian Guo
Multi-objective Neural Architecture Search by Learning Search Space Partitions. CoRR (2024)
Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian
Multi-objective Optimization by Learning Space Partition. ICLR (2022)
Linnan Wang, Chenhan Yu, Satish Salian, Slawomir Kierat, Szymon Migacz, Alex Fit-Florea
Searching the Deployable Convolution Neural Networks for GPUs. CVPR (2022)
Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian
Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search. IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2022)
Linnan Wang, Chenhan Yu, Satish Salian, Slawomir Kierat, Szymon Migacz, Alex Fit-Florea
GPUNet: Searching the Deployable Convolution Neural Networks for GPUs. CoRR (2022)
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 (2021)
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)
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo
Few-Shot Neural Architecture Search. ICML (2021)
Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian
Multi-objective Optimization by Learning Space Partitions. CoRR (2021)
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo
Few-shot Neural Architecture Search. CoRR (2020)
Linnan Wang, Rodrigo Fonseca, Yuandong Tian
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. CoRR (2020)
Linnan Wang, Rodrigo Fonseca, Yuandong Tian
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. NeurIPS (2020)
Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca
Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search. AAAI (2020)
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)
Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. CoRR (2019)
Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian
Sample-Efficient Neural Architecture Search by Learning Action Space. CoRR (2019)
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)
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 (2018)
Xi Luo, Wei Wu, George Bosilca, Thananon Patinyasakdikul, Linnan Wang, Jack J. Dongarra
ADAPT: an event-based adaptive collective communication framework. HPDC (2018)
Linnan Wang, Yiyang Zhao, Yuu Jinnai
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. CoRR (2018)
Ang Li, Weifeng Liu, Linnan Wang, Kevin J. Barker, Shuaiwen Leon Song
Warp-Consolidation: A Novel Execution Model for GPUs. ICS (2018)
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 (2018)
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. PPOPP (2018)
Guangxi Li, Zenglin Xu, Linnan Wang, Jinmian Ye, Irwin King, Michael R. Lyu
Simple and efficient parallelization for probabilistic temporal tensor factorization. IJCNN (2017)
Linnan Wang, Yi Yang, Renqiang Min, Srimat T. Chakradhar
Accelerating deep neural network training with inconsistent stochastic gradient descent. Neural Networks 93 (2017)
Yiyang Zhao, Linnan Wang, Wei Wu, George Bosilca, Richard W. Vuduc, Jinmian Ye, Wenqi Tang, Zenglin Xu
Efficient Communications in Training Large Scale Neural Networks. ACM Multimedia (Thematic Workshops) (2017)
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 (2017)
Carsten Binnig, Fuat Basik, Benedetto Buratti, Ugur Çetintemel, Yeounoh Chung, Andrew Crotty, Cyrus Cousins, Dylan Ebert, Philipp Eichmann, Alex Galakatos, Benjamin Hättasch, Amir Ilkhechi, Tim Kraska, Zeyuan Shang, Isabella Tromba, Arif Usta, Prasetya Utama, Eli Upfal, Linnan Wang, Nathaniel Weir, Robert C. Zeleznik, Emanuel Zgraggen
Towards Interactive Data Exploration. BIRTE (Revised Selected Papers) (2017)
Linnan Wang, Wei Wu, Zenglin Xu, Jianxiong Xiao, Yi Yang
BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing. ICS (2016)
Guangxi Li, Zenglin Xu, Linnan Wang, Jinmian Ye, Irwin King, Michael R. Lyu
Simple and Efficient Parallelization for Probabilistic Temporal Tensor Factorization. CoRR (2016)
Linnan Wang, Yi Yang, Martin Renqiang Min, Srimat T. Chakradhar
Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent. CoRR (2016)
Linnan Wang, Wei Wu, Jianxiong Xiao, Yi Yang
BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing. CoRR (2015)
Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi
Large Scale Artificial Neural Network Training Using Multi-GPUs. CoRR (2015)