I am a PhD student in the College of Information and Computer Sciences at UMass Amherst. I work with Prof. Philip Thomas in the Autonmous Learning Labratory. I am interested in reinforcement learning and representation learning, with an emphasis on developing and evaluting practical algorithms for real world use.
Publications and Papers
- Using Cumulative Distribution Based Performance Analysis to Benchmark Models
Scott M. Jordan, Daniel Cohen, Philip S. Thomas, In Critiquing and Correcting Trends in ML Workshop, NeurIPS 2018.
- Distributed Evaluations: Ending Neural Point Metrics
Daniel Cohen, Scott M. Jordan, W. Bruce Croft, SIGIR 2018 Workshop on Learning from Limited or Noisy Data
- Learning to Use a Ratchet by Modeling Spatial Relations in Demonstrations
Li Yang Ku, Scott M. Jordan, Julia Badger, Erik Learned-Miller, and Rod A. Grupen, Workshop on Learning from Demonstrations for High Level Robotics Tasks, at Robotics: Science and Systems 2018
- Summary of Experiments in Belief-Space Planning at the laboratory for Perceptual Robotics
Scott M. Jordan, Dirk Ruiken, Tiffany Q. Liu, Takeshi Takahashi, Michael W. Lanighan, Roderic A. Grupen, AAAI Spring Symposium 2017.