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Qi Qi

8 papers hereh-index 11379 citations18 works total

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

author position
  • first author2
  • middle author4
  • last author1

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.GT2
  • cs.NI1
  • math.OC1
same name
  • Qi Qi — 16 papers, h 13
  • Qi Qi — 8 papers, h 3
  • Qi Qi — 5 papers, h 3
  • Qi Qi — 4 papers, h 10
  • Qi Qi — 4 papers, h 3
  • Qi Qi — 3 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
20092021
most citedOn the Complexity of Envy-Free Cake Cutting

9 citations · 29 across the 5 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2021★ 6 cited

A Variational U-Net for Weather Forecasting

Pak Hay Kwok, Qi Qi

Not only can discovering patterns and insights from atmospheric data enable more accurate weather predictions, but it may also provide valuable information to help tackle climate c…

cs.LG2020★ 5 cited

Traffic4cast 2020 -- Graph Ensemble Net and the Importance of Feature And Loss Function Design for Traffic Prediction

Qi Qi, Pak Hay Kwok

This paper details our solution to Traffic4cast 2020. Similar to Traffic4cast 2019, Traffic4cast 2020 challenged its contestants to develop algorithms that can predict the future t…

cs.LG2020★ 4 cited

Variance-Reduced Off-Policy Memory-Efficient Policy Search

Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh +3

Off-policy policy optimization is a challenging problem in reinforcement learning (RL). The algorithms designed for this problem often suffer from high variance in their estimators…

cs.LG2019

A Simple and Effective Framework for Pairwise Deep Metric Learning

Qi Qi, Yan Yan, Xiaoyu Wang +1

Deep metric learning (DML) has received much attention in deep learning due to its wide applications in computer vision. Previous studies have focused on designing complicated loss…

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