Joseph Sill

433 total citations
10 papers, 137 citations indexed

About

Joseph Sill is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Joseph Sill has authored 10 papers receiving a total of 137 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Computer Networks and Communications. Recurrent topics in Joseph Sill's work include Machine Learning and Algorithms (3 papers), Machine Learning and Data Classification (2 papers) and Adversarial Robustness in Machine Learning (1 paper). Joseph Sill is often cited by papers focused on Machine Learning and Algorithms (3 papers), Machine Learning and Data Classification (2 papers) and Adversarial Robustness in Machine Learning (1 paper). Joseph Sill collaborates with scholars based in United States. Joseph Sill's co-authors include Yaser S. Abu‐Mostafa, Yehuda Koren, Xubo Song, Harvey L. Kasdan, Malik Magdon‐Ismail, Kagan Tumer, Misha Pavel, David H. Wolpert and Zehra Çataltepe and has published in prestigious journals such as Machine Learning, Information Fusion and Discrete Applied Mathematics.

In The Last Decade

Joseph Sill

10 papers receiving 121 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Joseph Sill United States	6	76	29	22	21	19	10	137
Janusz T. Starczewski Poland	8	159 2.1×	18 0.6×	67 3.0×	59 2.8×	16 0.8×	17	227
Dominik Olszewski Poland	7	173 2.3×	41 1.4×	15 0.7×	7 0.3×	8 0.4×	15	227
Edward T. Lee United States	7	163 2.1×	49 1.7×	36 1.6×	17 0.8×	31 1.6×	18	232
Albena Tchamova Bulgaria	7	103 1.4×	19 0.7×	67 3.0×	12 0.6×	20 1.1×	32	164
Jürgen Beringer Germany	5	265 3.5×	76 2.6×	12 0.5×	6 0.3×	13 0.7×	5	308
Yu. S. Kharin Belarus	9	65 0.9×	26 0.9×	13 0.6×	92 4.4×	58 3.1×	53	223
Yukihiro Hamasuna Japan	8	176 2.3×	115 4.0×	38 1.7×	12 0.6×	12 0.6×	53	228
Carlos Domingo Japan	6	189 2.5×	58 2.0×	11 0.5×	11 0.5×	4 0.2×	12	250
Dmitry Pechyony United States	9	175 2.3×	101 3.5×	18 0.8×	15 0.7×	4 0.2×	12	222
Jiachun Liao United States	10	178 2.3×	20 0.7×	8 0.4×	7 0.3×	18 0.9×	13	236

Countries citing papers authored by Joseph Sill

Since Specialization

Citations

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

Fields of papers citing papers by Joseph Sill

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joseph Sill

This figure shows the co-authorship network connecting the top 25 collaborators of Joseph Sill. A scholar is included among the top collaborators of Joseph Sill 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 Joseph Sill. Joseph Sill 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:

10 of 10 papers shown

1.

Koren, Yehuda & Joseph Sill. (2013). Collaborative filtering on ordinal user feedback. 3022–3026. 16 indexed citations

2.

Magdon‐Ismail, Malik & Joseph Sill. (2007). A linear fit gets the correct monotonicity directions. Machine Learning. 70(1). 21–43. 5 indexed citations

3.

Song, Xubo, Yaser S. Abu‐Mostafa, Joseph Sill, Harvey L. Kasdan, & Misha Pavel. (2002). Robust image recognition by fusion of contextual information. Information Fusion. 3(4). 277–287. 15 indexed citations

4.

Çataltepe, Zehra, et al.. (2002). A new error bound for the classifier chosen by early stopping. 2. 811–814. 1 indexed citations

5.

Wolpert, David H., Joseph Sill, & Kagan Tumer. (2001). Reinforcement learning in distributed domains: beyond team games. 819–824. 10 indexed citations

6.

Song, Xubo, Joseph Sill, Yaser S. Abu‐Mostafa, & Harvey L. Kasdan. (1999). Image Recognition in Context: Application to Microscopic Urinalysis. CaltechAUTHORS (California Institute of Technology). 12. 963–969. 5 indexed citations

7.

Sill, Joseph. (1998). The capacity of monotonic functions. Discrete Applied Mathematics. 86(1). 95–107. 3 indexed citations

8.

Song, Xubo, Yaser S. Abu‐Mostafa, Joseph Sill, & Harvey L. Kasdan. (1997). Incorporating Contextual Information in White Blood Cell Identification. CaltechAUTHORS (California Institute of Technology). 10. 950–956. 5 indexed citations

9.

Sill, Joseph. (1997). Monotonic Networks. Neural Information Processing Systems. 10. 661–667. 47 indexed citations

10.

Sill, Joseph & Yaser S. Abu‐Mostafa. (1996). Monotonicity Hints. Neural Information Processing Systems. 9. 634–640. 30 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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