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researcher

Bo Ji

28 papers hereh-index 201.6k citations58 works total

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

author position
  • first author5
  • middle author8
  • last author15

Across the 28 of 28 papers where every author was matched, so the position is known.

fields
  • cs.NI12
  • cs.IT6
  • cs.DC4
  • cs.LG3
  • cs.DS1
  • cs.GT1
same name
  • Bo Ji — 10 papers, h 7
  • Bo Ji — 8 papers, h 3
  • Bo Ji — 6 papers, h 3
  • Bo Ji — 5 papers, h 3
  • Bo Ji — 4 papers, h 2
  • Bo Ji — 4 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
20102023
most citedDelay-Based Back-Pressure Scheduling in Multihop Wireless Networks

119 citations · 197 across the 27 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.DC2022

On Scheduling Ring-All-Reduce Learning Jobs in Multi-Tenant GPU Clusters with Communication Contention

Menglu Yu, Bo Ji, Hridesh Rajan +1

Powered by advances in deep learning (DL) techniques, machine learning and artificial intelligence have achieved astonishing successes. However, the rapidly growing needs for DL al…

cs.LG2022

Differentially Private Linear Bandits with Partial Distributed Feedback

Fengjiao Li, Xingyu Zhou, Bo Ji

In this paper, we study the problem of global reward maximization with only partial distributed feedback. This problem is motivated by several real-world applications (e.g., cellul…

cs.IT2022★ 7 cited

Towards Optimal Tradeoff Between Data Freshness and Update Cost in Information-update Systems

Zhongdong Liu, Bin Li, Zizhan Zheng +2

In this paper, we consider a discrete-time information-update system, where a service provider can proactively retrieve information from the information source to update its data a…

cs.DC2022

GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs

Menglu Yu, Ye Tian, Bo Ji +3

Fueled by advances in distributed deep learning (DDL), recent years have witnessed a rapidly growing demand for resource-intensive distributed/parallel computing to process DDL com…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.