Linnan Wang

According to our database1, Linnan Wang authored at least 26 papers between 2015 and 2022.

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Bibliography

2022
Building an Intelligent Agent to Design Neural Networks.
PhD thesis, 2022

Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

GPUNet: Searching the Deployable Convolution Neural Networks for GPUs.
CoRR, 2022

Multi-objective Optimization by Learning Space Partition.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Searching the Deployable Convolution Neural Networks for GPUs.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Multi-objective Optimization by Learning Space Partitions.
CoRR, 2021

Learning Space Partitions for Path Planning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Few-Shot Neural Architecture Search.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Networks.
Proceedings of the HPDC '20: The 29th International Symposium on High-Performance Parallel and Distributed Computing, 2020

Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Sample-Efficient Neural Architecture Search by Learning Action Space.
CoRR, 2019

AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search.
CoRR, 2019

2018
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks.
CoRR, 2018

AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search.
CoRR, 2018

Superneurons: dynamic GPU memory management for training deep neural networks.
Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2018

Warp-Consolidation: A Novel Execution Model for GPUs.
Proceedings of the 32nd International Conference on Supercomputing, 2018

ADAPT: an event-based adaptive collective communication framework.
Proceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing, 2018

Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017
Accelerating deep neural network training with inconsistent stochastic gradient descent.
Neural Networks, 2017

Efficient Communications in Training Large Scale Neural Networks.
Proceedings of the on Thematic Workshops of ACM Multimedia 2017, Mountain View, CA, USA, October 23, 2017

Simple and efficient parallelization for probabilistic temporal tensor factorization.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017


2016
BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing.
Proceedings of the 2016 International Conference on Supercomputing, 2016

2015
Large Scale Artificial Neural Network Training Using Multi-GPUs.
CoRR, 2015

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing.
CoRR, 2015


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