Nikos Karampatziakis

2.0k citations
16 papers · 913 indexed · h-index 7

Nikos Karampatziakis

15 papers receiving 866 citations

Peers

Nikos Karampatziakis
Comparison fields: 5 of 128
  • Computer Vision and Pattern Recognition 380
  • Signal Processing 147
  • Artificial Intelligence 337
  • Computer Networks and Communications 138
  • Computational Mechanics 76
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Countries citing papers authored by Nikos Karampatziakis

Since Specialization
Citations

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

Fields of papers citing papers by Nikos Karampatziakis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nikos Karampatziakis. 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 Nikos Karampatziakis. The network helps show where Nikos Karampatziakis may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Nikos Karampatziakis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nikos Karampatziakis Line = papers co-authored together Nikos Karampatziakis links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 20240
2 20195
3
Gradient Coding: Avoiding Stragglers in Distributed Learning
2017196
4
Logarithmic Time One-Against-Some
20175
5
Fast Label Embeddings for Extremely Large Output Spaces
20152
6
Distributed and Scalable PCA in the Cloud
20141
7 20143
8 20136
9
Importance Weight Aware Gradient Updates
20104
10
Static Analysis of Binary Executables Using Structural SVMs
20107
11 201024
12 20091
13 2008339
14 2007297
15
Probabilistic Outputs for SVMs and Comparisons to Regularized Likelihood Methods
200720
16 20063

About Nikos Karampatziakis

Nikos Karampatziakis is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Software, having authored 16 papers that have together received 913 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (6 papers), Face and Expression Recognition (4 papers), Machine Learning and Data Classification (4 papers), Domain Adaptation and Few-Shot Learning (2 papers), Software Engineering Research (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Stochastic Gradient Optimization Techniques (2 papers) and Face recognition and analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (380 citations), Signal Processing (147 citations) and Artificial Intelligence (337 citations). Nikos Karampatziakis has collaborated with scholars based in United States, Greece and United Kingdom. Frequent co-authors include Rich Caruana, Ainur Yessenalina, Rashish Tandon, Qi Lei, Alexandros G. Dimakis, George Toderici, Ioannis A. Kakadiaris, Theoharis Theoharis, Georgios Passalis and John Langford. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Conference on Machine Learning, arXiv (Cornell University), Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE 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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