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E. Richard

8 papers hereh-index 11905 citations20 works total

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

author position
  • first author6
  • middle author1
  • last author1

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

fields
  • stat.ML3
  • cs.LG2
  • cs.DS1
  • cs.IT1
  • math.OC1
same name
  • E. Richard — 14 papers, h 14
  • E. Richard — 1 paper
  • E. Richard — 1 paper, h 0
  • E. Richard — 1 paper, h 3
  • E. Richard — 1 paper, h 2

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
20122016
most citedEstimation of Simultaneously Sparse and Low Rank Matrices

110 citations · 225 across the 7 of their papers we have counts for

collaborators
Showing 2012Show all

4 papers · 1 filter

stat.ML2012★ 5 cited

Link Prediction in Graphs with Autoregressive Features

Emile Richard, Stephane Gaiffas, Nicolas Vayatis

In the paper, we consider the problem of link prediction in time-evolving graphs. We assume that certain graph features, such as the node degree, follow a vector autoregressive (VA…

cs.DS2012★ 110 cited

Estimation of Simultaneously Sparse and Low Rank Matrices

Emile Richard, Pierre-Andre Savalle, Nicolas Vayatis

The paper introduces a penalized matrix estimation procedure aiming at solutions which are sparse and low-rank at the same time. Such structures arise in the context of social netw…

stat.ML2012

Graph Prediction in a Low-Rank and Autoregressive Setting

Emile Richard, Pierre-Andre Savalle, Nicolas Vayatis

We study the problem of prediction for evolving graph data. We formulate the problem as the minimization of a convex objective encouraging sparsity and low-rank of the solution, th…

cs.LG2012

A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs

Emile Richard, Andreas Argyriou, Theodoros Evgeniou +1

We consider the two problems of predicting links in a dynamic graph sequence and predicting functions defined at each node of the graph. In many applications, the solution of one p…

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