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A. Savchenko

17 papers hereh-index 242.1k citations154 works total

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

author position
  • sole author8
  • first author2
  • middle author1
  • last author6

Across the 17 of 17 papers where every author was matched, so the position is known.

fields
  • cs.CV12
  • cs.LG2
  • cs.CL1
  • eess.AS1
  • stat.ML1
same name
  • A. Savchenko — 29 papers, h 20
  • A. Savchenko — 7 papers, h 6
  • A. Savchenko — 4 papers, h 8
  • A. Savchenko — 3 papers, h 9
  • A. Savchenko — 2 papers, h 10
  • A. Savchenko — 2 papers, 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
20142023
most citedFacial expression and attributes recognition based on multi-task learning of lightweight neural networks

173 citations · 554 across the 16 of their papers we have counts for

collaborators
Showing 2019Show all

3 papers · 1 filter

cs.CV2019★ 1 cited

Event Recognition with Automatic Album Detection based on Sequential Processing, Neural Attention and Image Captioning

Andrey V. Savchenko

In this paper a new formulation of event recognition task is examined: it is required to predict event categories in a gallery of images, for which albums (groups of photos corresp…

cs.CV2019★ 26 cited

Preferences Prediction using a Gallery of Mobile Device based on Scene Recognition and Object Detection

A. V. Savchenko, K. V. Demochkin, I. S. Grechikhin

In this paper user modeling task is examined by processing a gallery of photos and videos on a mobile device. We propose novel engine for user preference prediction based on scene…

cs.CL2019★ 43 cited

Compression of Recurrent Neural Networks for Efficient Language Modeling

Artem M. Grachev, Dmitry I. Ignatov, Andrey V. Savchenko

Recurrent neural networks have proved to be an effective method for statistical language modeling. However, in practice their memory and run-time complexity are usually too large t…

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