default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLinnan Wang
Person information
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
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, 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): 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, Yuandong Tian:
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, George Bosilca, Thananon Patinyasakdikul, Linnan Wang, Jack J. Dongarra:
ADAPT: an event-based adaptive collective communication framework. HPDC 2018: 118-130 - [c6]Ang Li, Weifeng Liu, Linnan Wang, Kevin J. Barker, Shuaiwen Leon Song:
Warp-Consolidation: A Novel Execution Model for GPUs. ICS 2018: 53-64 - [c5]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: 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, Yi Yang, Renqiang Min, Srimat T. Chakradhar:
Accelerating deep neural network training with inconsistent stochastic gradient descent. Neural Networks 93: 219-229 (2017) - [c4]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 Ajie Utama, Eli Upfal, Linnan Wang, Nathaniel Weir, Robert C. Zeleznik, Emanuel Zgraggen:
Towards Interactive Data Exploration. BIRTE (Revised Selected Papers) 2017: 177-190 - [c3]Guangxi Li, Zenglin Xu, Linnan Wang, Jinmian Ye, Irwin King, Michael R. Lyu:
Simple and efficient parallelization for probabilistic temporal tensor factorization. IJCNN 2017: 1-8 - [c2]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: 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, Zenglin Xu, Jianxiong Xiao, Yi Yang:
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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:06 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
