Murat A. Erdogdu

19 papers receiving 107 citations

Peers

Murat A. Erdogdu
Comparison fields: 5 of 41
  • Artificial Intelligence 47
  • Statistics and Probability 43
  • Computational Mechanics 28
  • Control and Systems Engineering 14
  • Electrical and Electronic Engineering 13
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Countries citing papers authored by Murat A. Erdogdu

Since Specialization
Citations

This map shows the geographic impact of Murat A. Erdogdu'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 Murat A. Erdogdu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Murat A. Erdogdu more than expected).

Fields of papers citing papers by Murat A. Erdogdu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Murat A. Erdogdu. 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 Murat A. Erdogdu. The network helps show where Murat A. Erdogdu may publish in the future.

Co-authorship network of co-authors of Murat A. Erdogdu

This figure shows the co-authorship network connecting the top 25 collaborators of Murat A. Erdogdu. A scholar is included among the top collaborators of Murat A. Erdogdu 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 Murat A. Erdogdu. Murat A. Erdogdu 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 4
3 1
4
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias
1
5 5
6
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method
1
7
Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint
10
8
Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT
5
9
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
2
10
Towards Characterizing the High-dimensional Bias of Kernel-based Particle Inference Algorithms
3
11
Inference in Graphical Models via Semidefinite Programming Hierarchies
1
12
Robust Estimation of Neural Signals in Calcium Imaging
10
13
Scaled Least Squares Estimator for GLMs in Large-Scale Problems
3
14
Maximum Likelihood for Variance Estimation in High-Dimensional Linear Models
10
15
Privacy-Utility Trade-Off for Time-Series with Application to Smart-Meter Data.
8
16
Newton-Stein method: a second order method for GLMs via Stein's Lemma
5
17
Convergence rates of sub-sampled Newton methods
8
18 9
19 4
20
Estimating LASSO Risk and Noise Level
23

About Murat A. Erdogdu

Murat A. Erdogdu is a scholar working on Computational Mathematics, Statistics and Probability and Artificial Intelligence, having authored 20 papers that have together received 113 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (10 papers), Sparse and Compressive Sensing Techniques (8 papers) and Stochastic Gradient Optimization Techniques (6 papers). The work is most often cited by research in Statistics and Probability (43 citations), Numerical Analysis (11 citations) and Artificial Intelligence (47 citations). Murat A. Erdogdu has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Andrea Montanari, Mohsen Bayati, Nadia Fawaz, Lee H. Dicker, Hakan Inan, Mark J. Schnitzer, Krishnakumar Balasubramanian, Taiji Suzuki, Jimmy Ba and Mufan Li. Their work appears in journals such as Human and Ecological Risk Assessment An International Journal, Bernoulli and Journal of Statistical Mechanics Theory and Experiment.

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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