Aaron Sidford

1.3k citations
20 papers · 245 indexed · h-index 8
Topics
Stochastic Gradient Optimization Techniques (14 papers)Sparse and Compressive Sensing Techniques (7 papers)Machine Learning and Algorithms (5 papers)
Journals
Naval Research Logistics (NRL)arXiv (Cornell University)neural information processing systems

In The Last Decade

Aaron Sidford

19 papers receiving 229 citations

Peers

Aaron Sidford
Comparison fields: 5 of 49
  • Artificial Intelligence 146
  • Computational Theory and Mathematics 90
  • Computer Networks and Communications 56
  • Computational Mechanics 52
  • Statistics and Probability 30
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Citations per field
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Citations per year

Countries citing papers authored by Aaron Sidford

Since Specialization
Citations

This map shows the geographic impact of Aaron Sidford's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aaron Sidford with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron Sidford more than expected).

Fields of papers citing papers by Aaron Sidford

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aaron Sidford. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aaron Sidford. The network helps show where Aaron Sidford may publish in the future.

Co-authorship network of co-authors of Aaron Sidford

This figure shows the co-authorship network connecting the top 25 collaborators of Aaron Sidford. A scholar is included among the top collaborators of Aaron Sidford based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aaron Sidford. Aaron Sidford is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 8
4 5
5
A Rank-1 Sketch for Matrix Multiplicative Weights
2
6
Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity
2
7
Near-optimal method for highly smooth convex optimization
6
8
Complexity of Highly Parallel Non-Smooth Convex Optimization
1
9
Variance Reduction for Matrix Games
5
10
Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model
26
11
Accelerating Stochastic Gradient Descent for Least Squares Regression
5
12 9
13
Accelerating Stochastic Gradient Descent
10
14
Matching Matrix Bernstein with Little Memory: Near-Optimal Finite Sample Guarantees for Oja's Algorithm.
2
15
Parallelizing Stochastic Approximation Through Mini-Batching and Tail-Averaging.
4
16
Faster eigenvector computation via shift-and-invert preconditioning
2
17 53
18
Competing with the Empirical Risk Minimizer in a Single Pass
24
19 25
20 55

About Aaron Sidford

Aaron Sidford is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computational Mechanics, having authored 20 papers that have together received 245 indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (14 papers), Sparse and Compressive Sensing Techniques (7 papers) and Machine Learning and Algorithms (5 papers). The work is most often cited by research in Computational Mathematics (5 citations), Computational Theory and Mathematics (90 citations) and Artificial Intelligence (146 citations). Aaron Sidford has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Yin Tat Lee, Jonathan A. Kelner, Lorenzo Orecchia, Gary L. Miller, Jakub Pachocki, Michael B. Cohen, Sham M. Kakade, Mengdi Wang, Yinyu Ye and Xian Wu. Their work appears in journals such as Naval Research Logistics (NRL), arXiv (Cornell University) and neural information processing systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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