Marc Pickett: AI and Machine Learning
I’m currently Principal AI Research Scientist at Emergence AI.
From 2014-2023 I was at Google AI in Mountain View, CA and Washington, DC under Ray Kurzweil.
I also run the DC/MD/VA AI Meetup Group.
myfirstname (no dot) mylastname thenumeral1 at gmail dot com
Debris
Publications
I am also on Google Scholar
- A Brief Study of In-Domain Transfer and Learning from Fewer Samples using A Few Simple Priors
- Pickett, Marc; Sekhari, Ayush; Davidson, James
- ICML workshop on Continual Learners (2nd Best Paper Award) 2017
- A Growing Long-term Episodic & Semantic Memory
- Pickett, Marc; Al-Rfou, Rami; Shao, Louis; Tar, Chris
- NIPS workshop on Continual Learning 2016
- On the Personalities of Dead Authors
- Pickett, Marc; Tar, Chris; Strope, Brian
- Google Research Blog 2016
- Conversational Contextual Cues: The Case of Personalization and History for Response Ranking
- Al-Rfou, Rami; Pickett, Marc; Snaider, Javier; Sung, Yun-hsuan; Strope, Brian; Kurzweil, Ray
- arXiv preprint 2016
- Building High Assurance Human-Centric Decision Systems
- Heitmeyer, C., Pickett, M., Leonard, E.I., Ray, I., Aha, D.W., Trafton, J.G., and Archer, M.M.
- Automated Software Engineering Special Issue on Realizing AI Synergies in Software Engineering, 2015
- Towards A Unified Framework for Learning and Processing Perceptual, Relational, and Meta Knowledge
- Pickett, M.
- In Advances in Cognitive Systems Workshop on Metacognition about Artificial Situated Agents, 2013 [Overview Presentation]
- Using Cortically-Inspired Algorithms for Analogical Learning and Reasoning
- Pickett, M. and Aha, D.W.
- In Biologically Inspired Cognitive Architectures, 2013 [preprint]
- Spontaneous Analogy by Piggybacking on a Perceptual System
- Pickett, M. and Aha, D.W.
- In Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci-2013), 2013 [poster]
- Building on Deep Learning
- Pickett, M.
- In AAAI Workshop on Learning Rich Representations from Low-Level Sensors, 2013
- High Assurance Human-Centric Decision Systems
- Heitmeyer, C., Pickett, M., Breslow, L., Aha, D.W., Trafton, J.G., and Leonard, E.I.
- In Proceedings of the 2nd International NSF sponsored Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE’13), 2013
- Acquiring User Models to test Automated Assistants
- Pickett, M., Aha, D.W., and Trafton, J.G.
- In Proceedings of the Twenty-Sixth International Florida Artificial Intelligence Research Society Conference (FLAIRS-26), 2013
- Towards Relational Theory Formation from Undifferentiated Sensor Data.
- Pickett, M.
- Doctoral Dissertation, University of Maryland, Baltimore County, 2011 [defense slides]
- Essential Phenomena of General Intelligence.
- Pickett, M., Miner, D., and Oates, T.
- In Proceedings of The First Conference on Artificial General Intelligence, 2008
- Representation Change in The Marchitecture.
- Pickett, M., Miner, D.
- In Working Notes of the AAAI Fall Symposium on Representation Change, 2007
- A Gauntlet for Evaluating Cognitive Architectures.
- Pickett, M., Miner, D., and Oates, T.
- In Working Notes of the AAAI Workshop on Evaluating Architectures for Intelligence, 2007
- The Marchitecture: A Cognitive Architecture for a Robot Baby.
- Pickett, M. and Oates, T.
- In Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-07), (student abstract and poster), 2007
- The Übercruncher: Concept Formation by Analogy Discovery.
- Pickett, M.
- In Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-07), Doctoral Consortium, 2007
- Using Analogy Discovery to Create Abstractions.
- Pickett, M.
- In proceedings of the 7th International Symposium on Abstraction, Reformulation and Approximation (SARA), Lecture Notes in Artificial Intelligence. Springer Verlag, 2007
- Models of Strategic Deficiency and Poker.
- Chaddock, G., Pickett, M., Armstrong, T., and Oates, T.
- In Working Notes of the AAAI Workshop on Plan, Activity, and Intent Recognition (PAIR), 2007
- The Cruncher: Automatic Concept Formation using Minimum Description Length.
- Pickett, M. and Oates, T.
- In proceedings of the 6th International Symposium on Abstraction, Reformulation and Approximation (SARA), Lecture Notes in Artificial Intelligence. Springer Verlag, 2005
- Computational Social Dynamic Modeling of Group Recruitment.
- Berry, N., Ko, T., Moy, T., Pickett, M., Smrcka, J., Turnley, J., and Wu, B.
- Sandia Report SAND2003-8754, Sandia National Laboratories, 2003
- Policyblocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning.
- Pickett, M. and Barto, A.G.
- In Proceedings of the International Conference on Machine Learning, 2002