Tianqi Chen

19 papers · 2012–2025 · 7 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🏃 Academic Marathon (13) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (7) 🐣 Hot Topic Early Bird

🏃 Academic Marathon (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🧬 Topic Evolution 🏆 Keyword Champion 🗃️ Keyword Collector (69) 💎 Century Club (19) 🔥 Unstoppable (5) 📈 Trend Setter 🚀 Conference Pioneer

Conferences

NIPS (6) ICML (5) ICLR (4) AISTATS (1) EMNLP (1) JMLR (1) OSDI (1)

Top co-authors

Carlos Guestrin (4) Mingyuan Zhou (4) Luis Ceze (2) Lianmin Zheng (2) Eddie Yan (2) Thierry Moreau (2) Ruihang Lai (2) Arvind Krishnamurthy (2) Ziheng Jiang (2) Beidi Chen (2)

Keywords

neural network (3) markov chain monte carlo (2) gradient boosting (2) stochastic gradient (2) generative modeling (2) collaborative filtering (2) tensor program (2) diffusion model (2) second-order optimization (2) bayesian inference (2) hamiltonian monte carlo (2) bayesian matrix factorization (1) reinforcement learning (1) matrix factorization (1) structured prediction (1) langevin dynamics (1) model quantization (1) neural network optimization (1) variational inference (1) deep learning (1)

Papers

ARXSA: A General Negative Feedback Control Theory in Vision-Language Models EMNLP 2025 Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models ICLR 2025 APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding ICLR 2025 MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding ICLR 2025 A Dense Reward View on Aligning Text-to-Image Diffusion with Preference ICML 2024 Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression NIPS 2024 Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling ICML 2023 Beta Diffusion NIPS 2023 Towards Efficient and Accurate Winograd Convolution via Full Quantization NIPS 2023 ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines ICML 2023 Tensor Program Optimization with Probabilistic Programs NIPS 2022 Dynamic Tensor Rematerialization ICLR 2021 TVM: An Automated End-to-End Optimizing Compiler for Deep Learning OSDI 2018 Learning to Optimize Tensor Programs NIPS 2018 Efficient Second-Order Gradient Boosting for Conditional Random Fields AISTATS 2015 A Complete Recipe for Stochastic Gradient MCMC NIPS 2015 Stochastic Gradient Hamiltonian Monte Carlo ICML 2014 General Functional Matrix Factorization Using Gradient Boosting ICML 2013 SVDFeature: A Toolkit for Feature-based Collaborative Filtering JMLR 2012