![](https://dblp.uni-trier.de/img/logo.ua.320x120.png)
![](https://dblp.uni-trier.de/img/dropdown.dark.16x16.png)
![](https://dblp.uni-trier.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
![search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
default search action
Tianqi Chen 0001
Person information
- affiliation: Carnegie Mellon University, USA
- affiliation (PhD 2019): University of Washington, USA
Other persons with the same name
- Tianqi Chen (aka: Tian-Qi Chen) — disambiguation page
Refine list
![note](https://dblp.uni-trier.de/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c34]Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry:
ACROBAT: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time. MLSys 2024 - [c33]Yilong Zhao, Chien-Yu Lin, Kan Zhu, Zihao Ye, Lequn Chen, Size Zheng, Luis Ceze, Arvind Krishnamurthy, Tianqi Chen, Baris Kasikci:
Atom: Low-Bit Quantization for Efficient and Accurate LLM Serving. MLSys 2024 - [i27]Siyuan Feng, Jiawei Liu, Ruihang Lai, Charlie F. Ruan, Yong Yu, Lingming Zhang, Tianqi Chen:
Emerging Platforms Meet Emerging LLMs: A Year-Long Journey of Top-Down Development. CoRR abs/2404.09151 (2024) - [i26]Byungsoo Jeon, Mengdi Wu, Shiyi Cao, Sunghyun Kim, Sunghyun Park, Neeraj Aggarwal, Colin Unger, Daiyaan Arfeen, Peiyuan Liao, Xupeng Miao, Mohammad Alizadeh, Gregory R. Ganger, Tianqi Chen, Zhihao Jia:
GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism. CoRR abs/2406.17145 (2024) - 2023
- [c32]Zihao Ye
, Ruihang Lai, Junru Shao, Tianqi Chen, Luis Ceze:
SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning. ASPLOS (3) 2023: 660-678 - [c31]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 - [c30]Siyuan Chen, Pratik Pramod Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry:
ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines. ICML 2023: 4514-4528 - [e1]Dawn Song, Michael Carbin, Tianqi Chen:
Proceedings of the Sixth Conference on Machine Learning and Systems, MLSys 2023, Miami, FL, USA, June 4-8, 2023. mlsys.org 2023 [contents] - [i25]Siyuan Chen, Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry:
ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines. CoRR abs/2302.03851 (2023) - [i24]Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry:
ACRoBat: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time. CoRR abs/2305.10611 (2023) - [i23]Yilong Zhao, Chien-Yu Lin, Kan Zhu, Zihao Ye, Lequn Chen, Size Zheng, Luis Ceze, Arvind Krishnamurthy, Tianqi Chen, Baris Kasikci:
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving. CoRR abs/2310.19102 (2023) - [i22]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) - [i21]Xupeng Miao, Gabriele Oliaro
, Zhihao Zhang, Xinhao Cheng, Hongyi Jin, Tianqi Chen, Zhihao Jia:
Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems. CoRR abs/2312.15234 (2023) - 2022
- [c29]Byungsoo Jeon, Sunghyun Park, Peiyuan Liao, Sheng Xu, Tianqi Chen, Zhihao Jia:
Collage: Seamless Integration of Deep Learning Backends with Automatic Placement. PACT 2022: 517-529 - [c28]Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry:
The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding. MLSys 2022 - [c27]Bojian Zheng, Ziheng Jiang, Cody Hao Yu, Haichen Shen, Joshua Fromm, Yizhi Liu, Yida Wang, Luis Ceze, Tianqi Chen, Gennady Pekhimenko:
DietCode: Automatic Optimization for Dynamic Tensor Programs. MLSys 2022 - [c26]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 - [i20]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) - [i19]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) - [i18]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
- [c25]Marisa Kirisame, Steven Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared Roesch, Tianqi Chen, Zachary Tatlock:
Dynamic Tensor Rematerialization. ICLR 2021 - [c24]Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry:
Cortex: A Compiler for Recursive Deep Learning Models. MLSys 2021 - [c23]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 - [i17]Ziheng Jiang, Animesh Jain, Andrew Liu, Josh Fromm, Chengqian Ma, Tianqi Chen, Luis Ceze:
Automated Backend-Aware Post-Training Quantization. CoRR abs/2103.14949 (2021) - [i16]Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry:
The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding. CoRR abs/2110.10221 (2021) - [i15]Byungsoo Jeon, Sunghyun Park, Peiyuan Liao, Sheng Xu, Tianqi Chen, Zhihao Jia:
Collage: Automated Integration of Deep Learning Backends. CoRR abs/2111.00655 (2021) - 2020
- [c22]Meghan Cowan, Thierry Moreau, Tianqi Chen, James Bornholt, Luis Ceze:
Automatic generation of high-performance quantized machine learning kernels. CGO 2020: 305-316 - [i14]Marisa Kirisame, Steven Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared Roesch, Tianqi Chen, Zachary Tatlock:
Dynamic Tensor Rematerialization. CoRR abs/2006.09616 (2020) - [i13]Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry:
Cortex: A Compiler for Recursive Deep Learning Models. CoRR abs/2011.01383 (2020)
2010 – 2019
- 2019
- [b1]Tianqi Chen:
Scalable and Intelligent Learning Systems. University of Washington, USA, 2019 - [j3]Thierry Moreau, Tianqi Chen, Luis Vega, Jared Roesch, Eddie Q. Yan, Lianmin Zheng, Josh Fromm, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
A Hardware-Software Blueprint for Flexible Deep Learning Specialization. IEEE Micro 39(5): 8-16 (2019) - [j2]Yi-An Ma
, Emily B. Fox
, Tianqi Chen, Lei Wu:
Irreversible samplers from jump and continuous Markov processes. Stat. Comput. 29(1): 177-202 (2019) - [i12]Jared Roesch, Steven Lyubomirsky, Marisa Kirisame, Josh Pollock, Logan Weber, Ziheng Jiang, Tianqi Chen, Thierry Moreau, Zachary Tatlock:
Relay: A High-Level IR for Deep Learning. CoRR abs/1904.08368 (2019) - 2018
- [c21]Lanmin Zheng, Tianqi Chen:
Optimizing Deep Learning Workloads on ARM GPU with TVM. ReQuEST@ASPLOS 2018: 3 - [c20]Thierry Moreau, Tianqi Chen, Luis Ceze:
Leveraging the VTA-TVM Hardware-Software Stack for FPGA Acceleration of 8-bit ResNet-18 Inference. ReQuEST@ASPLOS 2018: 5 - [c19]Grigori Fursin, Thierry Moreau, Hillery C. Hunter, Yiran Chen, Charles Qi, Tianqi Chen:
PANEL: Open panel and discussion on tackling complexity, reproducibility and tech transfer challenges in a rapidly evolving AI/ML/systems research. ReQuEST@ASPLOS 2018: 7 - [c18]Tianqi Chen, Lianmin Zheng, Eddie Q. Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
Learning to Optimize Tensor Programs. NeurIPS 2018: 3393-3404 - [c17]Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Q. Yan, Haichen Shen, Meghan Cowan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy
:
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning. OSDI 2018: 578-594 - [c16]Jared Roesch, Steven Lyubomirsky
, Logan Weber, Josh Pollock, Marisa Kirisame, Tianqi Chen, Zachary Tatlock
:
Relay: a new IR for machine learning frameworks. MAPL@PLDI 2018: 58-68 - [i11]Tianqi Chen, Thierry Moreau, Ziheng Jiang, Haichen Shen, Eddie Q. Yan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
TVM: End-to-End Optimization Stack for Deep Learning. CoRR abs/1802.04799 (2018) - [i10]Tianqi Chen, Lianmin Zheng, Eddie Q. Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
Learning to Optimize Tensor Programs. CoRR abs/1805.08166 (2018) - [i9]Thierry Moreau, Tianqi Chen, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
VTA: An Open Hardware-Software Stack for Deep Learning. CoRR abs/1807.04188 (2018) - [i8]Jared Roesch, Steven Lyubomirsky, Logan Weber, Josh Pollock, Marisa Kirisame, Tianqi Chen, Zachary Tatlock:
Relay: A New IR for Machine Learning Frameworks. CoRR abs/1810.00952 (2018) - [i7]Meghan Cowan, Thierry Moreau, Tianqi Chen, Luis Ceze:
Automating Generation of Low Precision Deep Learning Operators. CoRR abs/1810.11066 (2018) - [i6]Ignacio Cano, Lequn Chen, Pedro Fonseca, Tianqi Chen, Chern Cheah, Karan Gupta, Ramesh Chandra, Arvind Krishnamurthy:
ADARES: Adaptive Resource Management for Virtual Machines. CoRR abs/1812.01837 (2018) - 2017
- [c15]Tianqi Chen:
An end to end IR stack for deep learning systems. TIML@ISCA 2017: 8 - 2016
- [c14]Tianqi Chen, Carlos Guestrin:
XGBoost: A Scalable Tree Boosting System. KDD 2016: 785-794 - [i5]Tianqi Chen, Carlos Guestrin:
XGBoost: A Scalable Tree Boosting System. CoRR abs/1603.02754 (2016) - [i4]Tianqi Chen, Bing Xu, Chiyuan Zhang, Carlos Guestrin:
Training Deep Nets with Sublinear Memory Cost. CoRR abs/1604.06174 (2016) - 2015
- [c13]Tianqi Chen, Sameer Singh, Ben Taskar, Carlos Guestrin:
Efficient Second-Order Gradient Boosting for Conditional Random Fields. AISTATS 2015 - [c12]Yi-An Ma, Tianqi Chen, Emily B. Fox:
A Complete Recipe for Stochastic Gradient MCMC. NIPS 2015: 2917-2925 - 2014
- [c11]Jingbo Shang, Tianqi Chen, Hang Li, Zhengdong Lu, Yong Yu:
A Parallel and Efficient Algorithm for Learning to Match. ICDM 2014: 971-976 - [c10]Tianqi Chen, Emily B. Fox, Carlos Guestrin:
Stochastic Gradient Hamiltonian Monte Carlo. ICML 2014: 1683-1691 - [i3]Tianqi Chen, Emily B. Fox, Carlos Guestrin:
Stochastic Gradient Hamiltonian Monte Carlo. CoRR abs/1402.4102 (2014) - [i2]Jingbo Shang, Tianqi Chen, Hang Li, Zhengdong Lu, Yong Yu:
A Parallel and Efficient Algorithm for Learning to Match. CoRR abs/1410.6414 (2014) - 2013
- [c9]Tianqi Chen, Hang Li, Qiang Yang, Yong Yu:
General Functional Matrix Factorization Using Gradient Boosting. ICML (1) 2013: 436-444 - [c8]Weinan Zhang, Tianqi Chen, Jun Wang, Yong Yu:
Optimizing top-n collaborative filtering via dynamic negative item sampling. SIGIR 2013: 785-788 - 2012
- [j1]Tianqi Chen, Weinan Zhang, Qiuxia Lu, Kailong Chen, Zhao Zheng, Yong Yu:
SVDFeature: a toolkit for feature-based collaborative filtering. J. Mach. Learn. Res. 13: 3619-3622 (2012) - [c7]Bing Cheng, Tianqi Chen, Diyi Yang, Weinan Zhang, Yongqiang Wang, Yong Yu:
Feature Based Informative Model for Discriminating Favorite Items from Unrated Ones. APWeb 2012: 146-157 - [c6]Fangwei Hu, Tianqi Chen, Nathan Nan Liu, Qiang Yang, Yong Yu:
Discriminative Factor Alignment across Heterogeneous Feature Space. ECML/PKDD (2) 2012: 757-772 - [c5]Diyi Yang, Tianqi Chen, Weinan Zhang, Qiuxia Lu, Yong Yu:
Local implicit feedback mining for music recommendation. RecSys 2012: 91-98 - [c4]Kailong Chen, Tianqi Chen, Guoqing Zheng, Ou Jin, Enpeng Yao, Yong Yu:
Collaborative personalized tweet recommendation. SIGIR 2012: 661-670 - [c3]Diyi Yang, Tianqi Chen, Weinan Zhang, Yong Yu:
Collaborative filtering with short term preferences mining. SIGIR 2012: 1043-1044 - [c2]Qiuxia Lu, Tianqi Chen, Weinan Zhang, Diyi Yang, Yong Yu:
Serendipitous Personalized Ranking for Top-N Recommendation. Web Intelligence 2012: 258-265 - [c1]Zhao Zheng, Tianqi Chen, Nathan Nan Liu, Qiang Yang, Yong Yu:
Rating Prediction with Informative Ensemble of Multi-Resolution Dynamic Models. KDD Cup 2012: 75-97 - 2011
- [i1]Tianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, Yong Yu:
Feature-Based Matrix Factorization. CoRR abs/1109.2271 (2011)
Coauthor Index
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
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 2024-08-16 00:43 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint