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researcher

Le Song

101 papers hereh-index 6623.5k citations190 works total

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

author position
  • first author2
  • middle author36
  • last author60

Across the 98 of 101 papers where every author was matched, so the position is known.

fields
  • cs.LG70
  • cs.SI12
  • cs.AI8
  • cs.CV4
  • stat.ML3
  • cs.CL2
same name
  • Le Song — 11 papers, h 33
  • Le Song — 10 papers, h 5
  • Le Song — 6 papers, h 6
  • Le Song — 4 papers, h 7
  • Le Song — 3 papers
  • Le Song — 3 papers, h 6

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
20122022
most citedLearning Combinatorial Optimization Algorithms over Graphs

1.1k citations · 5.5k across the 100 of their papers we have counts for

collaborators
Showing 2013Show all

4 papers · 1 filter

cs.LG2013★ 11 cited

Nonparametric Estimation of Multi-View Latent Variable Models

Le Song, Animashree Anandkumar, Bo Dai +1

Spectral methods have greatly advanced the estimation of latent variable models, generating a sequence of novel and efficient algorithms with strong theoretical guarantees. However…

cs.LG2013★ 12 cited

Budgeted Influence Maximization for Multiple Products

Nan Du, Yingyu Liang, Maria Florina Balcan +1

The typical algorithmic problem in viral marketing aims to identify a set of influential users in a social network, who, when convinced to adopt a product, shall influence other us…

cs.SI2013★ 129 cited

Scalable Influence Estimation in Continuous-Time Diffusion Networks

Nan Du, Le Song, Manuel Gomez Rodriguez +1

If a piece of information is released from a media site, can it spread, in 1 month, to a million web pages? This influence estimation problem is very challenging since both the tim…

cs.LG2013★ 20 cited

Least Squares Revisited: Scalable Approaches for Multi-class Prediction

Alekh Agarwal, Sham M. Kakade, Nikos Karampatziakis +2

This work provides simple algorithms for multi-class (and multi-label) prediction in settings where both the number of examples n and the data dimension d are relatively large. The…

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