World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
7502
World Ranking
8380
National Ranking
335

Overview

Scott Sanner is affiliated with the University of Toronto in Canada and has a significant presence in the field of computer science. Their research primarily spans artificial intelligence, computer vision and pattern recognition, control and systems engineering, building and construction, and signal processing.

The scientist's recent notable papers include:

  • Online continual learning in image classification: An empirical survey, 2021, Neurocomputing
  • Online Class-Incremental Continual Learning with Adversarial Shapley Value, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays, 2020, IEEE Transactions on Smart Grid
  • TransCAM: Transformer attention-based CAM refinement for Weakly supervised semantic segmentation, 2023, Journal of Visual Communication and Image Representation
  • The Lifecyle of a Youtube Video: Phases, Content and Popularity, 2021, Proceedings of the International AAAI Conference on Web and Social Media

Frequent coauthors in their work include Zheda Mai, Baher Abdulhai, Michael Gimelfarb, Ayal Taitler, and Jihwan Jeong, indicating collaborative work across various projects and research themes.

Scott Sanner has published extensively in venues such as arXiv (Cornell University), with 48 publications, followed by the Proceedings of the AAAI Conference on Artificial Intelligence, ACM Transactions on the Web, Proceedings of the International Conference on Automated Planning and Scheduling, and Neurocomputing.

Their main field of study is computer science, with 159 publications in this area. Within this domain, the subfields with the highest representation are artificial intelligence, computer vision and pattern recognition, control and systems engineering, building and construction, and signal processing.

Their research focuses on several key topics including:

  • Topic Modeling
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Reinforcement Learning in Robotics
  • Machine Learning and Algorithms
  • Recommender Systems and Techniques
  • Traffic control and management

Best Publications

  • AutoRec: Autoencoders Meet Collaborative Filtering

    Suvash Sedhain;Aditya Krishna Menon;Scott Sanner;Lexing Xie

  • Improving LDA topic models for microblogs via tweet pooling and automatic labeling

    Rishabh Mehrotra;Scott Sanner;Wray Buntine;Lexing Xie

  • Online Continual Learning in Image Classification: An Empirical Survey

    Zheda Mai;Ruiwen Li;Jihwan Jeong;David Quispe

  • Deep Learning with Microfluidics for Biotechnology.

    Jason Riordon;Dušan Sovilj;Scott Sanner;David Sinton

  • Towards object mapping in non-stationary environments with mobile robots

    R. Biswas;B. Limketkai;S. Sanner;S. Thrun

  • Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity

    Marian-Andrei Rizoiu;Lexing Xie;Scott Sanner;Manuel Cebrian

  • Online Class-Incremental Continual Learning with Adversarial Shapley Value

    Dongsub Shim;Zheda Mai;Jihwan Jeong;Scott Sanner

  • Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning

    Zheda Mai;Ruiwen Li;Hyunwoo Kim;Scott Sanner

  • The 2014 International Planning Competition: Progress and Trends

    Mauro Vallati;Lukás Chrpa;Marek Grzes;Thomas Leo McCluskey

  • Social collaborative filtering for cold-start recommendations

    Suvash Sedhain;Scott Sanner;Darius Braziunas;Lexing Xie

  • A Survey of the Seventh International Planning Competition

    Amanda Coles;Andrew Coles;Angel García Olaya;Sergio Jiménez

  • Practical solution techniques for first-order MDPs

    Scott Sanner;Craig Boutilier

  • Algorithms for Direct 01 Loss Optimization in Binary Classification

    Tan Nguyen;Scott Sanner

  • Deep learning-based selection of human sperm with high DNA integrity.

    Christopher McCallum;Jason Riordon;Yihe Wang;Tian Kong

  • Affine algebraic decision diagrams (AADDs) and their application to structured probabilistic inference

    Scott Sanner;David McAllester

  • Efficient solutions to factored MDPs with imprecise transition probabilities

    Karina Valdivia Delgado;Scott Sanner;Leliane Nunes de Barros

  • Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences

    Unknown

  • Gaussian Process Preference Elicitation

    Shengbo Guo;Scott Sanner;Edwin Bonilla

  • Symbolic dynamic programming for first-order POMDPs

    Scott Sanner;Kristian Kersting

  • New objective functions for social collaborative filtering

    Joseph Noel;Scott Sanner;Khoi-Nguyen Tran;Peter Christen

  • Efficient solutions to factored MDPs with imprecise transition probabilities

    Karina Valdivia Delgado;Scott Sanner;Leliane Nunes de Barros;Fabio G. Cozman

  • Comparison of machine learning models for occupancy prediction in residential buildings using connected thermostat data

    Brent Huchuk;Scott Sanner;William O'Brien

  • Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries

    Shengbo Guo;Scott Sanner

Frequent Co-Authors

Lexing Xie
Lexing Xie Australian National University
Kristian Kersting
Kristian Kersting Technical University of Darmstadt
Craig Boutilier
Craig Boutilier Google (United States)
William O'Brien
William O'Brien Carleton University
Manuel Cebrian
Manuel Cebrian Carlos III University of Madrid
Aditya Krishna Menon
Aditya Krishna Menon Google (United States)
Pascal Van Hentenryck
Pascal Van Hentenryck Georgia Institute of Technology
Peter Christen
Peter Christen Australian National University
Mark Chignell
Mark Chignell University of Toronto
Deepa Kundur
Deepa Kundur University of Toronto

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