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A. Dubrawski

43 papers hereh-index 313.3k citations195 works total

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

author position
  • middle author5
  • last author36

Across the 41 of 43 papers where every author was matched, so the position is known.

fields
  • cs.LG25
  • stat.ML12
  • stat.AP2
  • cs.AI1
  • cs.SI1
  • eess.SP1
same name
  • A. Dubrawski — 7 papers, h 11
  • A. Dubrawski — 3 papers, h 1

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
20152023
most citedNeural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx

259 citations · 463 across the 39 of their papers we have counts for

collaborators
Showing 2015Show all

4 papers · 1 filter

stat.ML2015

Canonical Autocorrelation Analysis

Maria De-Arteaga, Artur Dubrawski, Peter Huggins

We present an extension of sparse Canonical Correlation Analysis (CCA) designed for finding multiple-to-multiple linear correlations within a single set of variables. Unlike CCA, w…

stat.ML2015★ 1 cited

Lass-0: sparse non-convex regression by local search

William Herlands, Maria De-Arteaga, Daniel Neill +1

We compute approximate solutions to L0 regularized linear regression using L1 regularization, also known as the Lasso, as an initialization step. Our algorithm, the Lass-0 ("Lass-z…

stat.ML2015

Performance Bounds for Pairwise Entity Resolution

Matt Barnes, Kyle Miller, Artur Dubrawski

One significant challenge to scaling entity resolution algorithms to massive datasets is understanding how performance changes after moving beyond the realm of small, manually labe…

cs.SI2015

An Entity Resolution approach to isolate instances of Human Trafficking online

Chirag Nagpal, Kyle Miller, Benedikt Boecking +1

Human trafficking is a challenging law enforcement problem, and a large amount of such activity manifests itself on various online forums. Given the large, heterogeneous and noisy…

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