Mark S. Squillante
About
In The Last Decade
Mark S. Squillante
141 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 78
- Computer Networks and Communications 1.6k
- Information Systems 814
- Hardware and Architecture 539
- Management Information Systems 537
- Electrical and Electronic Engineering 279
Countries citing papers authored by Mark S. Squillante
This map shows the geographic impact of Mark S. Squillante'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 Mark S. Squillante with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark S. Squillante more than expected).
Fields of papers citing papers by Mark S. Squillante
This network shows the impact of papers produced by Mark S. Squillante. 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 Mark S. Squillante. The network helps show where Mark S. Squillante may publish in the future.
Co-authorship network of co-authors of Mark S. Squillante
This figure shows the co-authorship network connecting the top 25 collaborators of Mark S. Squillante. A scholar is included among the top collaborators of Mark S. Squillante 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 Mark S. Squillante. Mark S. Squillante is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Efficient Generalization with Distributionally Robust Learning | 0 |
| 3 | Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality | 4 |
| 4 | A Family of Robust Stochastic Operators for Reinforcement Learning | 1 |
| 5 | PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach | 12 |
| 6 | A Control-Model-Based Approach for Reinforcement Learning. | 2 |
| 7 | 21 | |
| 8 | 0 | |
| 9 | 11 | |
| 10 | 5 | |
| 11 | Optimal scheduling of multiclass parallel machines | 11 |
| 12 | Extensible Resource Scheduling for Parallel Scientific Applications. | 2 |
| 13 | Optimal Scheduling of Coarse-Grained Parallel Scientific Applications. | 1 |
| 14 | Analysis of optimal scheduling in distributed parallel queueing systems | 1 |
| 15 | PET: A Parallel Performance Estimation Tool. | 3 |
| 16 | Scheduling of Large Scientific Applications on Distributed Memory Multiprocessor Systems. | 10 |
| 17 | 42 | |
| 18 | 11 | |
| 19 | Analysis of Contention in Multiprocessor Scheduling | 9 |
| 20 | An RPC/LWP System for Interconnecting Heterogeneous Systems. | 1 |
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.