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researcher

M. Smelyanskiy

16 papers hereh-index 3711.1k citations98 works total

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

author position
  • middle author9
  • last author5

Across the 14 of 16 papers where every author was matched, so the position is known.

fields
  • cs.LG8
  • cs.DC4
  • cs.AR1
  • cs.IR1
  • cs.PL1
  • quant-ph1

identity via Semantic Scholar / OpenAlex

activity
20162021
most citedOn Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

571 citations · 1.2k across the 9 of their papers we have counts for

collaborators
Showing 2018Show all

3 papers · 1 filter

cs.LG2018

Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications

Jongsoo Park, Maxim Naumov, Protonu Basu +25

The application of deep learning techniques resulted in remarkable improvement of machine learning models. In this paper provides detailed characterizations of deep learning models…

cs.LG2018

Bandana: Using Non-volatile Memory for Storing Deep Learning Models

Assaf Eisenman, Maxim Naumov, Darryl Gardner +5

Typical large-scale recommender systems use deep learning models that are stored on a large amount of DRAM. These models often rely on embeddings, which consume most of the require…

cs.PL2018

Glow: Graph Lowering Compiler Techniques for Neural Networks

Nadav Rotem, Jordan Fix, Saleem Abdulrasool +15

This paper presents the design of Glow, a machine learning compiler for heterogeneous hardware. It is a pragmatic approach to compilation that enables the generation of highly opti…

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