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researcher

Gen Li

9 papers hereh-index 141k citations48 works total

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

author position
  • first author6
  • middle author3

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.IT4
  • cs.LG4
  • cs.CV1
same name
  • Gen Li — 11 papers, h 5
  • Gen Li — 7 papers, h 6
  • Gen Li — 7 papers, h 6
  • Gen Li — 6 papers, h 4
  • Gen Li — 6 papers, h 4
  • Gen Li — 5 papers, h 4

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
20172025
most citedRigorous Restricted Isometry Property of Low-Dimensional Subspaces

5 citations · 13 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2021

Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting

Gen Li, Yuxin Chen, Yuejie Chi +2

Low-complexity models such as linear function representation play a pivotal role in enabling sample-efficient reinforcement learning (RL). The current paper pertains to a scenario…

cs.LG2020★ 4 cited

The Efficacy of L1​ Regularization in Two-Layer Neural Networks

Gen Li, Yuantao Gu, Jie Ding

A crucial problem in neural networks is to select the most appropriate number of hidden neurons and obtain tight statistical risk bounds. In this work, we present a new perspective…

cs.LG2019

Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph

Gen Li, Yuantao Gu

Spectral Method is a commonly used scheme to cluster data points lying close to Union of Subspaces by first constructing a Random Geometry Graph, called Subspace Clustering. This p…

cs.LG2019★ 3 cited

Compressed Subspace Learning Based on Canonical Angle Preserving Property

Yuchen Jiao, Gen Li, Yuantao Gu

Union of Subspaces (UoS) is a popular model to describe the underlying low-dimensional structure of data. The fine details of UoS structure can be described in terms of canonical a…

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