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Tianqi Chen

6 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3
  • last author2

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • math-ph1
  • stat.AP1
ORCID 0000-0002-2336-1875
same name
  • Tianqi Chen — 13 papers, h 31
  • Tianqi Chen — 12 papers, h 4
  • Tianqi Chen — 7 papers, h 3
  • Tianqi Chen — 6 papers, h 6
  • Tianqi Chen — 6 papers, h 3
  • Tianqi Chen — 5 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122024
most citedTensorIR: An Abstraction for Automatic Tensorized Program Optimization

3 citations · 5 across the 6 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2024

WebLLM: A High-Performance In-Browser LLM Inference Engine

Charlie F. Ruan, Yucheng Qin, Akaash R. Parthasarathy +11

Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-grade GPUs and cloud-based inference, the…

cs.LG2023

ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines

Siyuan Chen, Pratik Fegade, Tianqi Chen +2

Batching has a fundamental influence on the efficiency of deep neural network (DNN) execution. However, for dynamic DNNs, efficient batching is particularly challenging as the data…

cs.LG2022★ 3 cited

TensorIR: An Abstraction for Automatic Tensorized Program Optimization

Siyuan Feng, Bohan Hou, Hongyi Jin +8

Deploying deep learning models on various devices has become an important topic. The wave of hardware specialization brings a diverse set of acceleration primitives for multi-dimen…

cs.LG2014

A Parallel and Efficient Algorithm for Learning to Match

Jingbo Shang, Tianqi Chen, Hang Li +2

Many tasks in data mining and related fields can be formalized as matching between objects in two heterogeneous domains, including collaborative filtering, link prediction, image t…

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