Tianqi Chen

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 73

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Publications

Bo Zhou, Jun Hou, Tianqi Chen, Yinchi Zhou, Xiongchao Chen, Huidong Xie, Qiong Liu, Xueqi Guo, Yu-Jung Tsai, Vladimir Y. Panin, Takuya Toyonaga, James S. Duncan, Chi Liu
POUR-Net: A Population-Prior-Aided Over-Under-Representation Network for Low-Count PET Attenuation Map Generation. CoRR (2024)
Tianqi Chen, Jun Hou, Yinchi Zhou, Huidong Xie, Xiongchao Chen, Qiong Liu, Xueqi Guo, Menghua Xia, James S. Duncan, Chi Liu, Bo Zhou
2.5D Multi-view Averaging Diffusion Model for 3D Medical Image Translation: Application to Low-count PET Reconstruction with CT-less Attenuation Correction. CoRR (2024)
Tianqi Chen, Zhe Li, Weixiang Xu, Zeyu Zhu, Dong Li, Lu Tian, Emad Barsoum, Peisong Wang, Jian Cheng
TernaryLLM: Ternarized Large Language Model. CoRR (2024)
Yinchi Zhou, Tianqi Chen, Jun Hou, Huidong Xie, Nicha C. Dvornek, S. Kevin Zhou, David L. Wilson, James S. Duncan, Chi Liu, Bo Zhou
Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation. CoRR (2024)
Shentao Yang, Tianqi Chen, Mingyuan Zhou
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference. CoRR (2024)
Tianqi Chen, Mingyuan Zhou
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling. CoRR (2023)
Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry
ACRoBat: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time. CoRR (2023)
Zihao Ye, Ruihang Lai, Junru Shao, Tianqi Chen, Luis Ceze
SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning. ASPLOS (3) (2023)
Tianqi Chen, Yongfei Liu, Zhendong Wang, Jianbo Yuan, Quanzeng You, Hongxia Yang, Mingyuan Zhou
Improving In-Context Learning in Diffusion Models with Visual Context-Modulated Prompts. CoRR (2023)
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 (2023)
Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng
Beta Diffusion. NeurIPS (2023)
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)
Tianqi Chen, Mingyuan Zhou
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling. ICML (2023)
Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng
Beta Diffusion. CoRR (2023)
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 (2023)
Tianqi Chen, Weixiang Xu, Weihan Chen, Peisong Wang, Jian Cheng
Towards Efficient and Accurate Winograd Convolution via Full Quantization. NeurIPS (2023)
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 (2023)
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)
Ren Wang, Tianqi Chen, Stephen Lindsly, Cooper Stansbury, Alnawaz Rehemtulla, Indika Rajapakse, Alfred O. Hero III
RAILS: A Robust Adversarial Immune-Inspired Learning System. IEEE Access 10 (2022)
Byungsoo Jeon, Sunghyun Park, Peiyuan Liao, Sheng Xu, Tianqi Chen, Zhihao Jia
Collage: Seamless Integration of Deep Learning Backends with Automatic Placement. PACT (2022)
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)
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)
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 (2022)
Elias Jääsaari, Michelle Ma, Ameet Talwalkar, Tianqi Chen
SONAR: Joint Architecture and System Optimization Search. CoRR (2022)
Zihao Ye, Ruihang Lai, Junru Shao, Tianqi Chen, Luis Ceze
SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning. CoRR (2022)
Ren Wang, Tianqi Chen, Philip Yao, Sijia Liu, Indika Rajapakse, Alfred O. Hero III
ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense. IEEE Access 10 (2022)
Tianning Zhang, Lay Keewq Ang, Tianqi Chen, Bo Yang, Erping Li
Stack operation of tensor networks. CoRR (2022)
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 (2022)
Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry
The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding. MLSys (2022)
Ziheng Jiang, Animesh Jain, Andrew Liu, Josh Fromm, Chengqian Ma, Tianqi Chen, Luis Ceze
Automated Backend-Aware Post-Training Quantization. CoRR (2021)
Marisa Kirisame, Steven Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared Roesch, Tianqi Chen, Zachary Tatlock
Dynamic Tensor Rematerialization. ICLR (2021)
Ren Wang, Tianqi Chen
Deep Adversarially-Enhanced k-Nearest Neighbors. CoRR (2021)
Ren Wang, Tianqi Chen, Stephen Lindsly, Cooper Stansbury, Indika Rajapakse, Alfred Olivier Hero
Immuno-mimetic Deep Neural Networks (Immuno-Net). CoRR (2021)
Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry
The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding. CoRR (2021)
Ren Wang, Tianqi Chen, Philip Yao, Sijia Liu, Indika Rajapakse, Alfred O. Hero III
ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense. CoRR (2021)
Byungsoo Jeon, Sunghyun Park, Peiyuan Liao, Sheng Xu, Tianqi Chen, Zhihao Jia
Collage: Automated Integration of Deep Learning Backends. CoRR (2021)
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)
Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry
Cortex: A Compiler for Recursive Deep Learning Models. MLSys (2021)
Ren Wang, Tianqi Chen, Stephen Lindsly, Cooper Stansbury, Alnawaz Rehemtulla, Indika Rajapakse, Alfred O. Hero III
RAILS: A Robust Adversarial Immune-inspired Learning System. CoRR (2021)
Ren Wang, Tianqi Chen, Zhe Xu, Pengzhi Gao
Robust Low-Rank Tensor Recovery From Quantized and Corrupted Measurements. ACSCC (2021)
Ren Wang, Tianqi Chen, Stephen Lindsly, Alnawaz Rehemtulla, Alfred O. Hero III, Indika Rajapakse
RAILS: A Robust Adversarial Immune-inspired Learning System. CoRR (2020)
Tianqi Chen, Jian He, Huiling Zhu, Lin Cai, Peng Yue, Jiangzhou Wang
Resource Allocation in Drone-Assisted Emergency Communication Systems. INFOCOM Workshops (2020)
Xin Wang, Liang Zhang, Tuoyang Zhou, Zhen Liao, Zhanshuo Zhang, Ning Li, Qiang Yao, Jin Liang, Yang Yu, Zhiqiang Tian, Tianqi Chen
Risk-Taking Propensity During a Prolonged Voyage at Sea: A Simulator Experiment Study. HCI (12) (2020)
Meghan Cowan, Thierry Moreau, Tianqi Chen, James Bornholt, Luis Ceze
Automatic generation of high-performance quantized machine learning kernels. CGO (2020)
Fatemeh Homayounieh, Ramandeep Singh, Tianqi Chen, Ellen J. Sugarman, Thomas J. Schultz, Subba R. Digumarthy, Keith J. Dreyer, Mannudeep K. Kalra
Viewing Imaging Studies: How Patient Location and Imaging Site Affect Referring Physicians. J. Digit. Imaging 33 (2) (2020)
Marisa Kirisame, Steven Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared Roesch, Tianqi Chen, Zachary Tatlock
Dynamic Tensor Rematerialization. CoRR (2020)
Pratik Fegade, Tianqi Chen, Phil Gibbons, Todd C. Mowry
Cortex: A Compiler for Recursive Deep Learning Models. CoRR (2020)
Yining Mu, Fanqi Tang, Makram Ibrahim, Yan Zhu, Wenxin Liu, Zhe Cao, Tianqi Chen
Optimization Design of Self-Triggered Complex Detector for Space Range-Gated Imaging System. IEEE Access 8 (2020)
Mohamed Sharafeldin, Karteek Kadimisetty, Ketki S. Bhalerao, Tianqi Chen, James F. Rusling
3D-Printed Immunosensor Arrays for Cancer Diagnostics. Sensors 20 (16) (2020)
Yi-An Ma, Emily B. Fox, Tianqi Chen, Lei Wu
Irreversible samplers from jump and continuous Markov processes. Stat. Comput. 29 (1) (2019)
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) (2019)
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 (2019)
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 (2018)
Meghan Cowan, Thierry Moreau, Tianqi Chen, Luis Ceze
Automating Generation of Low Precision Deep Learning Operators. CoRR (2018)
Thierry Moreau, Tianqi Chen, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy
VTA: An Open Hardware-Software Stack for Deep Learning. CoRR (2018)
Tianqi Chen, Lianmin Zheng, Eddie Q. Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy
Learning to Optimize Tensor Programs. CoRR (2018)
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)
Ignacio Cano, Lequn Chen, Pedro Fonseca, Tianqi Chen, Chern Cheah, Karan Gupta, Ramesh Chandra, Arvind Krishnamurthy
ADARES: Adaptive Resource Management for Virtual Machines. CoRR (2018)
Jared Roesch, Steven Lyubomirsky, Logan Weber, Josh Pollock, Marisa Kirisame, Tianqi Chen, Zachary Tatlock
Relay: A New IR for Machine Learning Frameworks. CoRR (2018)
Tianqi Chen, Lianmin Zheng, Eddie Q. Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy
Learning to Optimize Tensor Programs. NeurIPS (2018)
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)
Lanmin Zheng, Tianqi Chen
Optimizing Deep Learning Workloads on ARM GPU with TVM. ReQuEST@ASPLOS (2018)
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)
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)
Tianqi Chen
An end to end IR stack for deep learning systems. TIML@ISCA (2017)
Tianqi Chen, Bing Xu, Chiyuan Zhang, Carlos Guestrin
Training Deep Nets with Sublinear Memory Cost. CoRR (2016)
Tianqi Chen, Ian J. Goodfellow, Jonathon Shlens
Net2Net: Accelerating Learning via Knowledge Transfer. ICLR (2016)
Tianqi Chen, Carlos Guestrin
XGBoost: A Scalable Tree Boosting System. KDD (2016)
Tianqi Chen, Carlos Guestrin
XGBoost: A Scalable Tree Boosting System. CoRR (2016)
Yi-An Ma, Tianqi Chen, Emily B. Fox
A Complete Recipe for Stochastic Gradient MCMC. NIPS (2015)
Bing Xu, Naiyan Wang, Tianqi Chen, Mu Li
Empirical Evaluation of Rectified Activations in Convolutional Network. CoRR (2015)
Tianqi Chen, Sameer Singh, Ben Taskar, Carlos Guestrin
Efficient Second-Order Gradient Boosting for Conditional Random Fields. AISTATS (2015)
Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems. CoRR (2015)
Tianqi Chen, Tong He
Higgs Boson Discovery with Boosted Trees. HEPML@NIPS (2014)
Tianqi Chen, Emily B. Fox, Carlos Guestrin
Stochastic Gradient Hamiltonian Monte Carlo. ICML (2014)
Jingbo Shang, Tianqi Chen, Hang Li, Zhengdong Lu, Yong Yu
A Parallel and Efficient Algorithm for Learning to Match. ICDM (2014)
Jingbo Shang, Tianqi Chen, Hang Li, Zhengdong Lu, Yong Yu
A Parallel and Efficient Algorithm for Learning to Match. CoRR (2014)
Tianqi Chen, Emily B. Fox, Carlos Guestrin
Stochastic Gradient Hamiltonian Monte Carlo. CoRR (2014)
Weinan Zhang, Tianqi Chen, Jun Wang, Yong Yu
Optimizing top-n collaborative filtering via dynamic negative item sampling. SIGIR (2013)
Tianqi Chen, Hang Li, Qiang Yang, Yong Yu
General Functional Matrix Factorization Using Gradient Boosting. ICML (1) (2013)
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 (2012)
Fangwei Hu, Tianqi Chen, Nathan Nan Liu, Qiang Yang, Yong Yu
Discriminative Factor Alignment across Heterogeneous Feature Space. ECML/PKDD (2) (2012)
Behrang QasemiZadeh, Paul Buitelaar, Tianqi Chen, Georgeta Bordea
Semi-Supervised Technical Term Tagging With Minimal User Feedback. LREC (2012)
Qiuxia Lu, Tianqi Chen, Weinan Zhang, Diyi Yang, Yong Yu
Serendipitous Personalized Ranking for Top-N Recommendation. Web Intelligence (2012)
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)
Diyi Yang, Tianqi Chen, Weinan Zhang, Yong Yu
Collaborative filtering with short term preferences mining. SIGIR (2012)
Kailong Chen, Tianqi Chen, Guoqing Zheng, Ou Jin, Enpeng Yao, Yong Yu
Collaborative personalized tweet recommendation. SIGIR (2012)
Zhao Zheng, Tianqi Chen, Nathan Nan Liu, Qiang Yang, Yong Yu
Rating Prediction with Informative Ensemble of Multi-Resolution Dynamic Models. KDD Cup (2012)
Diyi Yang, Tianqi Chen, Weinan Zhang, Qiuxia Lu, Yong Yu
Local implicit feedback mining for music recommendation. RecSys (2012)
Tianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, Yong Yu
Feature-Based Matrix Factorization CoRR (2011)
Jihao Yin, Tianqi Chen
Direction-of-Arrival Estimation Using a Sparse Representation of Array Covariance Vectors. IEEE Trans. Signal Process. 59 (9) (2011)
Tianqi Chen, Jun Yan, Gui-Rong Xue, Zheng Chen
Transfer learning for behavioral targeting. WWW (2010)
Zhong Wen, Liping Li, Tianqi Chen, Xixiang Zhang
Joint multiple parameters estimation for coherent chirp signals using vector sensor array. Sci. China Ser. F Inf. Sci. 51 (1) (2008)
Xin Su, Tianqi Chen
Simultaneously estimating frequency and direction of coherent signal via an array triplet in motion. EUSIPCO (1998)