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researcher

R. Willett

79 papers hereh-index 429k citations228 works total

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

author position
  • first author1
  • middle author24
  • last author54

Across the 79 of 79 papers where every author was matched, so the position is known.

fields
  • stat.ML28
  • cs.LG11
  • math.ST11
  • cs.CV6
  • cs.IT6
  • math.OC6
same name
  • R. Willett — 42 papers, h 23
  • R. Willett — 14 papers, h 25
  • R. Willett — 6 papers, h 4

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
20092026
most citedThis is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms - Theory and Practice

289 citations · 1.2k across the 72 of their papers we have counts for

collaborators
Showing 2016 · stat.MLShow all

4 papers · 2 filters

stat.ML2016★ 6 cited

Improved Strongly Adaptive Online Learning using Coin Betting

Kwang-Sung Jun, Francesco Orabona, Rebecca Willett +1

This paper describes a new parameter-free online learning algorithm for changing environments. In comparing against algorithms with the same time complexity as ours, we obtain a st…

stat.ML2016

Online Data Thinning via Multi-Subspace Tracking

Xin Jiang, Rebecca Willett

In an era of ubiquitous large-scale streaming data, the availability of data far exceeds the capacity of expert human analysts. In many settings, such data is either discarded or s…

stat.ML2016★ 28 cited

Inference of High-dimensional Autoregressive Generalized Linear Models

Eric C. Hall, Garvesh Raskutti, Rebecca Willett

Vector autoregressive models characterize a variety of time series in which linear combinations of current and past observations can be used to accurately predict future observatio…

stat.ML2016★ 3 cited

On Learning High Dimensional Structured Single Index Models

Nikhil Rao, Ravi Ganti, Laura Balzano +2

Single Index Models (SIMs) are simple yet flexible semi-parametric models for machine learning, where the response variable is modeled as a monotonic function of a linear combinati…

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