Marcus A. Maloof

3.8k total citations · 2 hit papers
29 papers, 2.4k citations indexed

About

Marcus A. Maloof is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Marcus A. Maloof has authored 29 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 8 papers in Computer Networks and Communications and 5 papers in Information Systems. Recurrent topics in Marcus A. Maloof's work include Data Stream Mining Techniques (9 papers), Machine Learning and Data Classification (8 papers) and Network Security and Intrusion Detection (6 papers). Marcus A. Maloof is often cited by papers focused on Data Stream Mining Techniques (9 papers), Machine Learning and Data Classification (8 papers) and Network Security and Intrusion Detection (6 papers). Marcus A. Maloof collaborates with scholars based in United States, Poland and United Kingdom. Marcus A. Maloof's co-authors include J. Zico Kolter, Ryszard S. Michalski, Stephen H. Bach, Deanna D. Caputo, Thomas O. Binford, R. Nevatia, Pat Langley, Stephanie Sage, Robert F. Wagner and Sergey V. Beiden and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and Artificial Intelligence.

In The Last Decade

Marcus A. Maloof

29 papers receiving 2.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts

2007 449 citations J. Zico Kolter, Marcus A. Maloof Journal of Machine Learning Research profile →
Learning to Detect and Classify Malicious Executables in the Wild

2006 399 citations J. Zico Kolter, Marcus A. Maloof Journal of Machine Learning Research profile →

Peers

Marcus A. Maloof

AI

SP

CNC

IS

MSOR

Ricard Gavaldà Spain

Geoff Hulten United States

Dirk Van Gucht United States

Ben Kao Hong Kong

Zongmin Ma China

Vipin Kumar United States

Daniel Lowd United States

A. Nur Zincir‐Heywood Canada

Nael Abu‐Ghazaleh United States

Battista Biggio Italy

Ricard Gavaldà Spain

Marcus A. Maloof

1.9k ×1.1

AI

513 ×0.5

SP

926 ×1.0

CNC

679 ×1.1

IS

211 ×0.9

MSOR

Citations per year, relative to Marcus A. Maloof Marcus A. Maloof (= 1×) peers Ricard Gavaldà

Countries citing papers authored by Marcus A. Maloof

Since Specialization

Citations

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

Fields of papers citing papers by Marcus A. Maloof

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcus A. Maloof

This figure shows the co-authorship network connecting the top 25 collaborators of Marcus A. Maloof. A scholar is included among the top collaborators of Marcus A. Maloof 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 Marcus A. Maloof. Marcus A. Maloof is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Bach, Stephen H. & Marcus A. Maloof. (2008). Paired Learners for Concept Drift. 23–32. 87 indexed citations

2.

Kolter, J. Zico & Marcus A. Maloof. (2007). Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts. Journal of Machine Learning Research. 8(91). 2755–2790. 449 indexed citations breakdown →

3.

Kolter, J. Zico & Marcus A. Maloof. (2006). Learning to Detect and Classify Malicious Executables in the Wild. Journal of Machine Learning Research. 7(99). 2721–2744. 399 indexed citations breakdown →

4.

Maloof, Marcus A.. (2006). Machine Learning and Data Mining for Computer Security: Methods and Applications. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 35 indexed citations

5.

Maloof, Marcus A.. (2005). Machine Learning and Data Mining for Computer Security: Methods and Applications (Advanced Information and Knowledge Processing). Springer eBooks. 21 indexed citations

6.

Kolter, J. Zico & Marcus A. Maloof. (2005). Using additive expert ensembles to cope with concept drift. 449–456. 170 indexed citations

7.

Kolter, J. Zico & Marcus A. Maloof. (2004). Dynamic weighted majority: a new ensemble method for tracking concept drift. 123–130. 290 indexed citations

8.

Maloof, Marcus A. & Ryszard S. Michalski. (2003). Incremental learning with partial instance memory. Artificial Intelligence. 154(1-2). 95–126. 75 indexed citations

9.

Maloof, Marcus A.. (2003). Learning When Data Sets are Imbalanced and When Costs are Unequal and Unknown. 289 indexed citations

10.

Maloof, Marcus A., Pat Langley, Thomas O. Binford, R. Nevatia, & Stephanie Sage. (2003). Improved Rooftop Detection in Aerial Images with Machine Learning. Machine Learning. 53(1-2). 157–191. 49 indexed citations

11.

Maloof, Marcus A.. (2003). On machine learning, ROC analysis, and statistical tests of significance. 2. 204–207. 15 indexed citations

12.

Michalski, Ryszard S., Azriel Rosenfeld, Zoran Đurić, Marcus A. Maloof, & Qi Zhang. (2002). Learning Patterns in Images. 2 indexed citations

13.

Maloof, Marcus A., Pat Langley, Thomas O. Binford, & R. Nevatia. (2002). Generalizing over aspect and location for rooftop detection. 194–199. 8 indexed citations

14.

Maloof, Marcus A. & Krzysztof Kochut. (2002). Modifying Rete to reason temporally. 472–473. 3 indexed citations

15.

Maloof, Marcus A.. (2000). An Initial Study of an Adaptive Hierarchical Vision System. International Conference on Machine Learning. 567–574. 4 indexed citations

16.

Maloof, Marcus A. & Ryszard S. Michalski. (2000). Selecting Examples for Partial Memory Learning. Machine Learning. 41(1). 27–52. 88 indexed citations

17.

Maloof, Marcus A., Pat Langley, Thomas O. Binford, & Stephanie Sage. (1998). Improving Rooftop Detection in Aerial Images Through Machine Learning. 2 indexed citations

18.

Maloof, Marcus A.. (1997). Progressive partial memory learning. 8 indexed citations

19.

Maloof, Marcus A. & Ryszard S. Michalski. (1995). A Partial Memory Incremental Learning Methodology and its Application to Computer Intrusion Detection. George Mason University. 4 indexed citations

20.

Maloof, Marcus A. & Ryszard S. Michalski. (1994). Learning Descriptions of 2D Blob-Like Shapes for Object Recognition in X-Ray Images: An Initial Study. 2 indexed citations

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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