Scott Sanner
Impact in
- Artificial Intelligence top 0.5%
- Topic Modeling
- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
- AI-based Problem Solving and Planning
- Advanced Text Analysis Techniques
- Information Systems top 0.5%
- Recommender Systems and Techniques
Papers in
-
- Bayesian Modeling and Causal Inference 24
- Reinforcement Learning in Robotics 20
- Topic Modeling 20
- Machine Learning and Algorithms 20
- AI-based Problem Solving and Planning 11
-
- Recommender Systems and Techniques 30
- Co-authors
- Lexing Xie (11 shared papers)Aditya Krishna Menon (4 shared papers)Zheda Mai (8 shared papers)Rishabh Mehrotra (1 shared paper)Wray Buntine (1 shared paper)Hyunwoo Kim (3 shared papers)William O’Brien (5 shared papers)Brent Huchuk (5 shared papers)
- Journals
- AI Magazine (4 papers)Artificial Intelligence (3 papers)ACM Transactions on the Web (2 papers)Building and Environment (2 papers)International Journal of Approximate Reasoning (1 paper)
- Partner nations
- CanadaAustraliaUnited States
In The Last Decade
Scott Sanner
143 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Artificial Intelligence 2.2k
- Information Systems 1.3k
- Computer Vision and Pattern Recognition 856
- Management Science and Operations Research 315
- Transportation 143
Countries citing papers authored by Scott Sanner
This map shows the geographic impact of Scott Sanner'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 Scott Sanner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Sanner more than expected).
Fields of papers citing papers by Scott Sanner
This network shows the impact of papers produced by Scott Sanner. 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 Scott Sanner. The network helps show where Scott Sanner may publish in the future.
Co-authors
The 25 scholars most cited alongside Scott Sanner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 149 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | AutoRec Hit paper breakdown → | 2015 | 764 |
| 2 | Improving LDA topic models for microblogs via tweet pooling and automatic labeling Hit paper breakdown → | 2013 | 321 |
| 3 | Online continual learning in image classification: An empirical survey Hit paper breakdown → | 2021 | 229 |
| 4 | 2018 | 170 | |
| 5 | 2021 | 99 | |
| 6 | 2021 | 96 | |
| 7 | 2019 | 88 | |
| 8 | 2014 | 81 | |
| 9 | 2012 | 74 | |
| 10 | 2019 | 72 | |
| 11 | 2020 | 70 | |
| 12 | 2015 | 69 | |
| 13 | 2018 | 65 | |
| 14 | 2003 | 65 | |
| 15 | 2023 | 59 | |
| 16 | 2017 | 56 | |
| 17 | 2012 | 42 | |
| 18 | 2023 | 41 | |
| 19 | Algorithms for Direct 01 Loss Optimization in Binary Classification | 2013 | 38 |
| 20 | Gaussian Process Preference Elicitation | 2010 | 38 |
About Scott Sanner
Scott Sanner is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 149 papers that have together received 3.7k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (30 papers), Bayesian Modeling and Causal Inference (24 papers), Reinforcement Learning in Robotics (20 papers), Topic Modeling (20 papers), Machine Learning and Algorithms (20 papers), Formal Methods in Verification (17 papers), Advanced Bandit Algorithms Research (13 papers) and AI-based Problem Solving and Planning (11 papers). The work is most often cited by research in Artificial Intelligence (2.2k citations), Information Systems (1.3k citations), Computer Vision and Pattern Recognition (856 citations), Management Science and Operations Research (315 citations) and Transportation (143 citations). Scott Sanner has collaborated with scholars based in Canada, Australia and United States. Frequent co-authors include Lexing Xie, Aditya Krishna Menon, Zheda Mai, Rishabh Mehrotra, Wray Buntine, Hyunwoo Kim, William O’Brien, Brent Huchuk, Ruiwen Li and Jihwan Jeong. Their work appears in journals such as AI Magazine, Artificial Intelligence, ACM Transactions on the Web, Building and Environment and International Journal of Approximate Reasoning.
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.