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Igor Melnyk

4 papers hereh-index 7273 citations7 works total

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

author position
  • first author2
  • middle author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • math.ST1
  • stat.ML1
same name
  • Igor Melnyk — 22 papers, h 17
  • Igor Melnyk — 2 papers, h 3

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
20142017
most citedR2N2: Residual Recurrent Neural Networks for Multivariate Time Series Forecasting

30 citations · 60 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2017★ 30 cited

R2N2: Residual Recurrent Neural Networks for Multivariate Time Series Forecasting

Hardik Goel, Igor Melnyk, Arindam Banerjee

Multivariate time-series modeling and forecasting is an important problem with numerous applications. Traditional approaches such as VAR (vector auto-regressive) models and more re…

math.ST2016★ 24 cited

Estimating Structured Vector Autoregressive Model

Igor Melnyk, Arindam Banerjee

While considerable advances have been made in estimating high-dimensional structured models from independent data using Lasso-type models, limited progress has been made for settin…

cs.LG2016

Semi-Markov Switching Vector Autoregressive Model-based Anomaly Detection in Aviation Systems

Igor Melnyk, Arindam Banerjee, Bryan Matthews +1

In this work we consider the problem of anomaly detection in heterogeneous, multivariate, variable-length time series datasets. Our focus is on the aviation safety domain, where da…

stat.ML2014★ 6 cited

A Spectral Algorithm for Inference in Hidden Semi-Markov Models

Igor Melnyk, Arindam Banerjee

Hidden semi-Markov models (HSMMs) are latent variable models which allow latent state persistence and can be viewed as a generalization of the popular hidden Markov models (HMMs).…

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