Feature-Based Matrix Factorization - Tianqi Chen 001; Zhao Zheng; Qiuxia Lu; Weinan Zhang 001; Yong Yu 001 (CoRR, 2011)

Feature Based Informative Model for Discriminating Favorite Items from Unrated Ones. - Bing Cheng; Tianqi Chen 001; Diyi Yang; Weinan Zhang 001; Yongqiang Wang; Yong Yu 001 (APWeb, 2012)

Discriminative Factor Alignment across Heterogeneous Feature Space. - Fangwei Hu; Tianqi Chen 001; Nathan Nan Liu; Qiang Yang 001; Yong Yu 001 (ECML/PKDD (2), 2012)

Local implicit feedback mining for music recommendation. - Diyi Yang; Tianqi Chen 001; Weinan Zhang 001; Qiuxia Lu; Yong Yu 001 (RecSys, 2012)

Collaborative personalized tweet recommendation. - Kailong Chen; Tianqi Chen 001; Guoqing Zheng; Ou Jin; Enpeng Yao; Yong Yu 001 (SIGIR, 2012)

Collaborative filtering with short term preferences mining. - Diyi Yang; Tianqi Chen 001; Weinan Zhang 001; Yong Yu 001 (SIGIR, 2012)

Serendipitous Personalized Ranking for Top-N Recommendation. - Qiuxia Lu; Tianqi Chen 001; Weinan Zhang 001; Diyi Yang; Yong Yu 001 (Web Intelligence, 2012)

SVDFeature: a toolkit for feature-based collaborative filtering. - Tianqi Chen 001; Weinan Zhang 001; Qiuxia Lu; Kailong Chen; Zhao Zheng; Yong Yu 001 (J. Mach. Learn. Res., 2012)

Rating Prediction with Informative Ensemble of Multi-Resolution Dynamic Models. - Zhao Zheng; Tianqi Chen 001; Nathan Nan Liu; Qiang Yang 001; Yong Yu 001 (KDD Cup, 2012)

General Functional Matrix Factorization Using Gradient Boosting. - Tianqi Chen 001; Hang Li 001; Qiang Yang 001; Yong Yu 001 (ICML (1), 2013)

Optimizing top-n collaborative filtering via dynamic negative item sampling. - Weinan Zhang 001; Tianqi Chen 001; Jun Wang 012; Yong Yu 001 (SIGIR, 2013)

A Parallel and Efficient Algorithm for Learning to Match. - Jingbo Shang; Tianqi Chen 001; Hang Li 001; Zhengdong Lu; Yong Yu 001 (ICDM, 2014)

Stochastic Gradient Hamiltonian Monte Carlo. - Tianqi Chen 001; Emily B. Fox; Carlos Guestrin (ICML, 2014)

Efficient Second-Order Gradient Boosting for Conditional Random Fields. - Tianqi Chen 001; Sameer Singh 001; Ben Taskar; Carlos Guestrin (AISTATS, 2015)

A Complete Recipe for Stochastic Gradient MCMC. - Yi-An Ma; Tianqi Chen 001; Emily B. Fox (NIPS, 2015)

XGBoost: A Scalable Tree Boosting System. - Tianqi Chen 001; Carlos Guestrin (KDD, 2016)

Training Deep Nets with Sublinear Memory Cost. - Tianqi Chen 001; Bing Xu; Chiyuan Zhang; Carlos Guestrin (CoRR, 2016)

An end to end IR stack for deep learning systems. - Tianqi Chen 001 (TIML@ISCA, 2017)

PANEL: Open panel and discussion on tackling complexity, reproducibility and tech transfer challenges in a rapidly evolving AI/ML/systems research. - Grigori Fursin; Thierry Moreau; Hillery C. Hunter; Yiran Chen 001; Charles Qi; Tianqi Chen 001 (ReQuEST@ASPLOS, 2018)

Leveraging the VTA-TVM Hardware-Software Stack for FPGA Acceleration of 8-bit ResNet-18 Inference. - Thierry Moreau; Tianqi Chen 001; Luis Ceze (ReQuEST@ASPLOS, 2018)

Optimizing Deep Learning Workloads on ARM GPU with TVM. - Lanmin Zheng; Tianqi Chen 001 (ReQuEST@ASPLOS, 2018)

Learning to Optimize Tensor Programs. - Tianqi Chen 001; Lianmin Zheng; Eddie Q. Yan; Ziheng Jiang; Thierry Moreau; Luis Ceze; Carlos Guestrin; Arvind Krishnamurthy (NeurIPS, 2018)

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning. - Tianqi Chen 001; Thierry Moreau; Ziheng Jiang; Lianmin Zheng; Eddie Q. Yan; Haichen Shen; Meghan Cowan; Leyuan Wang; Yuwei Hu; Luis Ceze; Carlos Guestrin; Arvind Krishnamurthy (OSDI, 2018)

Relay: a new IR for machine learning frameworks. - Jared Roesch; Steven Lyubomirsky; Logan Weber; Josh Pollock; Marisa Kirisame; Tianqi Chen 001; Zachary Tatlock (MAPL@PLDI, 2018)

TVM: End-to-End Optimization Stack for Deep Learning. - Tianqi Chen 001; Thierry Moreau; Ziheng Jiang; Haichen Shen; Eddie Q. Yan; Leyuan Wang; Yuwei Hu; Luis Ceze; Carlos Guestrin; Arvind Krishnamurthy (CoRR, 2018)

VTA: An Open Hardware-Software Stack for Deep Learning. - Thierry Moreau; Tianqi Chen 001; Ziheng Jiang; Luis Ceze; Carlos Guestrin; Arvind Krishnamurthy (CoRR, 2018)

Automating Generation of Low Precision Deep Learning Operators. - Meghan Cowan; Thierry Moreau; Tianqi Chen 001; Luis Ceze (CoRR, 2018)

ADARES: Adaptive Resource Management for Virtual Machines. - Ignacio Cano 001; Lequn Chen 001; Pedro Fonseca 001; Tianqi Chen 001; Chern Cheah; Karan Gupta; Ramesh Chandra; Arvind Krishnamurthy (CoRR, 2018)

Relay: A High-Level IR for Deep Learning. - Jared Roesch; Steven Lyubomirsky; Marisa Kirisame; Josh Pollock; Logan Weber; Ziheng Jiang; Tianqi Chen 001; Thierry Moreau; Zachary Tatlock (CoRR, 2019)

A Hardware-Software Blueprint for Flexible Deep Learning Specialization. - Thierry Moreau; Tianqi Chen 001; Luis Vega; Jared Roesch; Eddie Q. Yan; Lianmin Zheng; Josh Fromm; Ziheng Jiang; Luis Ceze; Carlos Guestrin; Arvind Krishnamurthy (IEEE Micro, 2019)

Irreversible samplers from jump and continuous Markov processes. - Yi-An Ma; Emily B. Fox; Tianqi Chen 001; Lei Wu (Stat. Comput., 2019)

Scalable and Intelligent Learning Systems. - Tianqi Chen 001 (2019)

Automatic generation of high-performance quantized machine learning kernels. - Meghan Cowan; Thierry Moreau; Tianqi Chen 001; James Bornholt; Luis Ceze (CGO, 2020)

Dynamic Tensor Rematerialization. - Marisa Kirisame; Steven Lyubomirsky; Altan Haan; Jennifer Brennan; Mike He; Jared Roesch; Tianqi Chen 001; Zachary Tatlock (ICLR, 2021)

Cortex: A Compiler for Recursive Deep Learning Models. - Pratik Fegade; Tianqi Chen 001; Phillip B. Gibbons; Todd C. Mowry (MLSys, 2021)

TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers. - Lianmin Zheng; Ruochen Liu; Junru Shao; Tianqi Chen 001; Joseph Gonzalez 001; Ion Stoica; Ameer Haj-Ali (NeurIPS Datasets and Benchmarks, 2021)

Automated Backend-Aware Post-Training Quantization. - Ziheng Jiang; Animesh Jain; Andrew Liu; Josh Fromm; Chengqian Ma; Tianqi Chen 001; Luis Ceze (CoRR, 2021)

Collage: Automated Integration of Deep Learning Backends. - Byungsoo Jeon; Sunghyun Park 004; Peiyuan Liao; Sheng Xu; Tianqi Chen 001; Zhihao Jia (CoRR, 2021)

Collage: Seamless Integration of Deep Learning Backends with Automatic Placement. - Byungsoo Jeon; Sunghyun Park 004; Peiyuan Liao; Sheng Xu; Tianqi Chen 001; Zhihao Jia (PACT, 2022)

The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding. - Pratik Fegade; Tianqi Chen 001; Phillip B. Gibbons; Todd C. Mowry (MLSys, 2022)

DietCode: Automatic Optimization for Dynamic Tensor Programs. - Bojian Zheng; Ziheng Jiang; Cody Hao Yu; Haichen Shen; Joshua Fromm; Yizhi Liu; Yida Wang 003; Luis Ceze; Tianqi Chen 001; Gennady Pekhimenko (MLSys, 2022)

Tensor Program Optimization with Probabilistic Programs. - Junru Shao; Xiyou Zhou; Siyuan Feng; Bohan Hou; Ruihang Lai; Hongyi Jin; Wuwei Lin; Masahiro Masuda; Cody Hao Yu; Tianqi Chen 001 (NeurIPS, 2022)

TensorIR: An Abstraction for Automatic Tensorized Program Optimization. - Siyuan Feng; Bohan Hou; Hongyi Jin; Wuwei Lin; Junru Shao; Ruihang Lai; Zihao Ye 001; Lianmin Zheng; Cody Hao Yu; Yong Yu 001; Tianqi Chen 001 (ASPLOS (2), 2023)

SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning. - Zihao Ye 001; Ruihang Lai; Junru Shao; Tianqi Chen 001; Luis Ceze (ASPLOS (3), 2023)

ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines. - Siyuan Chen 007; Pratik Pramod Fegade; Tianqi Chen 001; Phillip B. Gibbons; Todd C. Mowry (ICML, 2023)

Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems. - Xupeng Miao; Gabriele Oliaro; Zhihao Zhang 001; Xinhao Cheng; Hongyi Jin; Tianqi Chen 001; Zhihao Jia (CoRR, 2023)

ACROBAT: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time. - Pratik Fegade; Tianqi Chen 001; Phillip B. Gibbons; Todd C. Mowry (MLSys, 2024)

Atom: Low-Bit Quantization for Efficient and Accurate LLM Serving. - Yilong Zhao; Chien-Yu Lin; Kan Zhu; Zihao Ye 001; Lequn Chen 001; Size Zheng 001; Luis Ceze; Arvind Krishnamurthy; Tianqi Chen 001; Baris Kasikci (MLSys, 2024)

Emerging Platforms Meet Emerging LLMs: A Year-Long Journey of Top-Down Development. - Siyuan Feng; Jiawei Liu 004; Ruihang Lai; Charlie F. Ruan; Yong Yu 001; Lingming Zhang 001; Tianqi Chen 001 (CoRR, 2024)

Local deployment of large-scale music AI models on commodity hardware. - Xun Zhou; Charlie Ruan; Zihe Zhao; Tianqi Chen 001; Chris Donahue (CoRR, 2024)

XGrammar: Flexible and Efficient Structured Generation Engine for Large Language Models. - Yixin Dong; Charlie F. Ruan; Yaxing Cai; Ruihang Lai; Ziyi Xu; Yilong Zhao; Tianqi Chen 001 (CoRR, 2024)

A System for Microserving of LLMs. - Hongyi Jin; Ruihang Lai; Charlie F. Ruan; Yingcheng Wang; Todd C. Mowry; Xupeng Miao; Zhihao Jia; Tianqi Chen 001 (CoRR, 2024)

WebLLM: A High-Performance In-Browser LLM Inference Engine. - Charlie F. Ruan; Yucheng Qin; Xun Zhou; Ruihang Lai; Hongyi Jin; Yixin Dong; Bohan Hou; Meng-Shiun Yu; Yiyan Zhai; Sudeep Agarwal; Hangrui Cao; Siyuan Feng; et al. (CoRR, 2024)

GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism. - Byungsoo Jeon; Mengdi Wu; Shiyi Cao; Sunghyun Kim; Sunghyun Park 004; Neeraj Aggarwal; Colin Unger; Daiyaan Arfeen; Peiyuan Liao; Xupeng Miao; Mohammad Alizadeh; Gregory R. Ganger; et al. (ASPLOS (1), 2025)

Relax: Composable Abstractions for End-to-End Dynamic Machine Learning. - Ruihang Lai; Junru Shao; Siyuan Feng; Steven Lyubomirsky; Bohan Hou; Wuwei Lin; Zihao Ye 001; Hongyi Jin; Yuchen Jin; Jiawei Liu 004; Lesheng Jin; Yaxing Cai; et al. (ASPLOS (2), 2025)

Productively Deploying Emerging Models on Emerging Platforms: A Top-Down Approach for Testing and Debugging. - Siyuan Feng; Jiawei Liu 004; Ruihang Lai; Charlie Ruan; Yong Yu 001; Lingming Zhang 001; Tianqi Chen 001 (Proc. ACM Softw. Eng., 2025)

FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving. - Zihao Ye 001; Lequn Chen 001; Ruihang Lai; Wuwei Lin; Yineng Zhang; Stephanie Wang; Tianqi Chen 001; Baris Kasikci; Vinod Grover; Arvind Krishnamurthy; Luis Ceze (CoRR, 2025)

Tilus: A Virtual Machine for Arbitrary Low-Precision GPGPU Computation in LLM Serving. - Yaoyao Ding; Bohan Hou; Xiao Zhang; Allan Lin; Tianqi Chen 001; Cody Yu Hao; Yida Wang 003; Gennady Pekhimenko (CoRR, 2025)