Eric Eaton

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 86

Top Venues

CoRR

AI Matters

AAAI

AI Mag.

Publications

Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan P. How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash, Vishwa S. Parekh, Kaushik Roy, Shahaf S. Shperberg, Hava T. Siegelmann, Peter Stone, Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, Soheil Kolouri
A collective AI via lifelong learning and sharing at the edge. Nat. Mac. Intell. 6 (3) (2024)
Meghna Gummadi, Cassandra Kent, Karl Schmeckpeper, Eric Eaton
A Metacognitive Approach to Out-of-Distribution Detection for Segmentation. ICRA (2024)
Eric Eaton, Susan L. Epstein
Artificial Intelligence in the CS2023 Undergraduate Computer Science Curriculum: Rationale and Challenges. AAAI (2024)
Long Le, Marcel Hussing, Eric Eaton
Distributed Continual Learning. CoRR (2024)
Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays
ZeroFlow: Scalable Scene Flow via Distillation. ICLR (2024)
Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton
Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence. CoRR (2024)
Guiqiu Liao, Matjaz Jogan, Sai Koushik, Eric Eaton, Daniel A. Hashimoto
Disentangling spatio-temporal knowledge for weakly supervised object detection and segmentation in surgical video. CoRR (2024)
Meghna Gummadi, Cassandra Kent, Karl Schmeckpeper, Eric Eaton
A Metacognitive Approach to Out-of-Distribution Detection for Segmentation. CoRR (2023)
Marcel Hussing, Jorge A. Mendez, Anisha Singrodia, Cassandra Kent, Eric Eaton
Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning. CoRR (2023)
Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays
ZeroFlow: Fast Zero Label Scene Flow via Distillation. CoRR (2023)
Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell
Replicable Reinforcement Learning. NeurIPS (2023)
Duo Lu, Eric Eaton, Matt Weg, Wei Wang, Steven Como, Jeffrey Wishart, Hongbin Yu, Yezhou Yang
CAROM Air - Vehicle Localization and Traffic Scene Reconstruction from Aerial Videos. ICRA (2023)
Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Dimitri Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael L. Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR (2023)
Samantha Haines, Eric Eaton, Md Liakat Ali
Machine Learning Models for Histopathological Breast Cancer Image Classification. AIIoT (2023)
Duo Lu, Eric Eaton, Matt Weg, Wei Wang, Steven Como, Jeffrey Wishart, Hongbin Yu, Yezhou Yang
CAROM Air - Vehicle Localization and Traffic Scene Reconstruction from Aerial Videos. CoRR (2023)
Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael L. Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks 160 (2023)
Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Gezheng Xu, Christian Gagné, Eric Eaton
Gap Minimization for Knowledge Sharing and Transfer. J. Mach. Learn. Res. 24 (2023)
Jorge A. Mendez, Eric Eaton
How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition. Trans. Mach. Learn. Res. 2023 (2023)
Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell
Replicable Reinforcement Learning. CoRR (2023)
Christian Servin, Brett A. Becker, Eric Eaton, Amruth N. Kumar
Fuzzy Logic++: Towards Developing Fuzzy Education Curricula Using ACM/IEEE/AAAI CS2023. NAFIPS (2023)
Pengyuan Lu, Michele Caprio, Eric Eaton, Insup Lee
Zero-shot Task Preference Addressing Enabled by Imprecise Bayesian Continual Learning. CoRR (2023)
Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
Prospective Learning: Principled Extrapolation to the Future. CoLLAs (2023)
Meghna Gummadi, David Kent, Jorge A. Mendez, Eric Eaton
SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries. CoRR (2022)
Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Christian Gagné, Eric Eaton
Gap Minimization for Knowledge Sharing and Transfer. CoRR (2022)
Jorge A. Mendez, Marcel Hussing, Meghna Gummadi, Eric Eaton
CompoSuite: A Compositional Reinforcement Learning Benchmark. CoLLAs (2022)
Jorge A. Mendez, Eric Eaton
How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition. CoRR (2022)
Jorge A. Mendez, Marcel Hussing, Meghna Gummadi, Eric Eaton
CompoSuite: A Compositional Reinforcement Learning Benchmark. CoRR (2022)
Jorge A. Mendez, Harm van Seijen, Eric Eaton
Modular Lifelong Reinforcement Learning via Neural Composition. CoRR (2022)
Jorge A. Mendez, Harm van Seijen, Eric Eaton
Modular Lifelong Reinforcement Learning via Neural Composition. ICLR (2022)
Kyle Vedder, Eric Eaton
Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems. IROS (2022)
Joshua T. Vogelstein, Timothy Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael Platt, Lyle Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
Prospective Learning: Back to the Future. CoRR (2022)
Meghna Gummadi, David Kent, Jorge A. Mendez, Eric Eaton
SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries. CoLLAs (2022)
Jorge A. Mendez, Shashank Shivkumar, Eric Eaton
Lifelong Inverse Reinforcement Learning. CoRR (2022)
Marcel Hussing, Karen Li, Eric Eaton
Land Use Prediction using Electro-Optical to SAR Few-Shot Transfer Learning. CoRR (2022)
Kyle Vedder, Eric Eaton
Sparse PointPillars: Exploiting Sparsity in Birds-Eye-View Object Detection. CoRR (2021)
Jorge A. Mendez, Eric Eaton
Lifelong Learning of Compositional Structures. ICLR (2021)
Ali Geisa, Ronak D. Mehta, Hayden S. Helm, Jayanta Dey, Eric Eaton, Carey E. Priebe, Joshua T. Vogelstein
Towards a theory of out-of-distribution learning. CoRR (2021)
Seungwon Lee, Sima Behpour, Eric Eaton
Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer. ICML (2021)
Jorge A. Mendez, Boyu Wang, Eric Eaton
Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting. NeurIPS (2020)
Jorge A. Mendez, Boyu Wang, Eric Eaton
Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting. CoRR (2020)
Mohammad Rostami, David Isele, Eric Eaton
Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer. J. Artif. Intell. Res. 67 (2020)
Jorge A. Mendez, Eric Eaton
Lifelong Learning of Compositional Structures. CoRR (2020)
Efstathios D. Gennatas, J. H. Friedman, Lyle H. Ungar, Romain Pirracchio, Eric Eaton, L. Reichman, Yannet Interian, Charles B. Simone II, A. Auerbach, E. Delgado, Mark J. van der Laan, Timothy D. Solberg, Gilmer Valdes
Expert-Augmented Machine Learning. CoRR (2019)
Seungwon Lee, James Stokes, Eric Eaton
Learning Shared Knowledge for Deep Lifelong Learning using Deconvolutional Networks. IJCAI (2019)
Eric Eaton
A Lightweight Approach to Academic Research Group Management Using Online Tools: Spend More Time on Research and Less on Management. AAAI (2019)
Julia E. Reid, Eric Eaton
Artificial Intelligence for Pediatric Ophthalmology. CoRR (2019)
Mohammad Rostami, Soheil Kolouri, Eric Eaton, Kyungnam Kim
Deep Transfer Learning for Few-Shot SAR Image Classification. Remote. Sens. 11 (11) (2019)
Mohammad Rostami, Soheil Kolouri, Eric Eaton, Kyungnam Kim
SAR Image Classification Using Few-Shot Cross-Domain Transfer Learning. CVPR Workshops (2019)
Boyu Wang, Jorge A. Mendez, Mingbo Cai, Eric Eaton
Transfer Learning via Minimizing the Performance Gap Between Domains. NeurIPS (2019)
Mohammad Rostami, Soheil Kolouri, Zak Murez, Yuri Owekcho, Eric Eaton, Kyungnam Kim
Zero-Shot Image Classification Using Coupled Dictionary Embedding. CoRR (2019)
Mohammad Rostami, Eric Eaton
Lifelong Learning Networks: Beyond Single Agent Lifelong Learning. AAAI (2018)
Eric Eaton, Amy McGovern
Welcome to AI matters, volume 3, issue 4. AI Matters 3 (4) (2018)
Eric Eaton, Sven Koenig, Claudia Schulz, Francesco Maurelli, John S. Y. Lee, Joshua Eckroth, Mark Crowley, Richard G. Freedman, Rogelio Enrique Cardona-Rivera, Tiago Machado, Tom Williams
Blue sky ideas in artificial intelligence education from the EAAI 2017 new and future AI educator program. AI Matters 3 (4) (2018)
Mohammad Rostami, Soheil Kolouri, Kyungnam Kim, Eric Eaton
Multi-Agent Distributed Lifelong Learning for Collective Knowledge Acquisition. AAMAS (2018)
Jorge A. Mendez, Shashank Shivkumar, Eric Eaton
Lifelong Inverse Reinforcement Learning. NeurIPS (2018)
Amy McGovern, Eric Eaton
Welcome to AI matters 4(1). AI Matters 4 (1) (2018)
David Isele, Eric Eaton, Mark Roberts, David W. Aha
Modeling Consecutive Task Learning with Task Graph Agendas. AAMAS (2018)
Amy McGovern, Eric Eaton
An interview with Ayanna Howard. AI Matters 3 (4) (2018)
Sheila A. McIlraith, Kilian Q. Weinberger, G. Michael Youngblood, Karen L. Myers, Eric Eaton, Michael Wollowski
A Recap of the AAAI and IAAI 2018 Conferences and the EAAI Symposium. AI Mag. 39 (4) (2018)
Amy McGovern, Eric Eaton
AI profiles: an interview with Maja Matarić. AI Matters 3 (3) (2017)
Amy McGovern, Eric Eaton
AI profiles: an interview with Jim Kurose. AI Matters 3 (1) (2017)
Eric Eaton, Sven Koenig, Claudia Schulz, Francesco Maurelli, John Lee, Joshua Eckroth, Mark Crowley, Richard G. Freedman, Rogelio Enrique Cardona-Rivera, Tiago Machado, Tom Williams
Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program. CoRR (2017)
Sven Koenig, Sanmay Das, Rosemary D. Paradis, Eric Eaton, Yolanda Gil, Katherine Guo, Bojun Huang, Albert Jiang, Benjamin Kuipers, Nicholas Mattei, Amy McGovern, Larry R. Medsker, Todd W. Neller, Plamen Petrov, Michael Rovatsos, David G. Stork
ACM SIGAI activity report. AI Matters 3 (3) (2017)
Amy McGovern, Eric Eaton
AI profiles: an interview with Peter Stone. AI Matters 3 (2) (2017)
David Isele, Mohammad Rostami, Eric Eaton
Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer. CoRR (2017)
Christopher Clingerman, Eric Eaton
Lifelong Learning with Gaussian Processes. ECML/PKDD (2) (2017)
Eric Eaton, Amy McGovern
Welcome to AI matters, volume 3, issue 3. AI Matters 3 (3) (2017)
Mohammad Rostami, Soheil Kolouri, Kyungnam Kim, Eric Eaton
Multi-Agent Distributed Lifelong Learning for Collective Knowledge Acquisition. CoRR (2017)
Decebal Constantin Mocanu, Haitham Bou-Ammar, Luis Puig, Eric Eaton, Antonio Liotta
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines. Pattern Recognit. 69 (2017)
Eric Eaton, Amy McGovern
Welcome to AI matters, volume 3, issue 2. AI Matters 3 (2) (2017)
José-Marcio Luna, Eric Eaton, Lyle H. Ungar, Eric Diffenderfer, Shane T. Jensen, Efstathios D. Gennatas, Mateo Wirth, Charles B. Simone II, Timothy D. Solberg, Gilmer Valdes
Tree-Structured Boosting: Connections Between Gradient Boosted Stumps and Full Decision Trees. CoRR (2017)
Eric Eaton
Teaching Integrated AI through Interdisciplinary Project-Driven Courses. AI Mag. 38 (2) (2017)
David Isele, Mohammad Rostami, Eric Eaton
Using Task Features for Zero-Shot Knowledge Transfer in Lifelong Learning. IJCAI (2016)
Eric Eaton, Amy McGovern
Welcome to AI Matters, volume 2, issue 3. AI Matters 2 (3) (2016)
David Isele, José-Marcio Luna, Eric Eaton, Gabriel Victor de la Cruz, James Irwin, Brandon Kallaher, Matthew E. Taylor
Lifelong learning for disturbance rejection on mobile robots. IROS (2016)
Decebal Constantin Mocanu, Haitham Bou-Ammar, Luis Puig, Eric Eaton, Antonio Liotta
Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines. CoRR (2016)
Amy McGovern, Eric Eaton
AI profiles: an interview with Peter Norvig. AI Matters 2 (4) (2016)
Decebal Constantin Mocanu, Maria Torres Vega, Eric Eaton, Peter Stone, Antonio Liotta
Online Contrastive Divergence with Generative Replay: Experience Replay without Storing Data. CoRR (2016)
Stefano V. Albrecht, J. Christopher Beck, David L. Buckeridge, Adi Botea, Cornelia Caragea, Chi-Hung Chi, Theodoros Damoulas, Bistra Dilkina, Eric Eaton, Pooyan Fazli, Sam Ganzfried, Marius Lindauer, Marlos C. Machado, Yuri Malitsky, Gary Marcus, Sebastiaan A. Meijer, Francesca Rossi, Arash Shaban-Nejad, Sylvie Thiébaux, Manuela M. Veloso, Toby Walsh, Can Wang, Jie Zhang, Yu Zheng
Reports from the 2015 AAAI Workshop Program. AI Mag. 36 (2) (2015)
Haitham Bou-Ammar, Rasul Tutunov, Eric Eaton
Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret. CoRR (2015)
Haitham Bou-Ammar, Eric Eaton, Paul Ruvolo, Matthew E. Taylor
Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment. AAAI (2015)
Haitham Bou-Ammar, Eric Eaton, José-Marcio Luna, Paul Ruvolo
Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning. IJCAI (2015)
Eric Eaton, Tom Dietterich, Maria L. Gini, Barbara J. Grosz, Charles L. Isbell Jr., Subbarao Kambhampati, Michael L. Littman, Francesca Rossi, Stuart J. Russell, Peter Stone, Toby Walsh, Michael J. Wooldridge
Who speaks for AI? AI Matters 2 (2) (2015)
Eric Eaton, Kiri L. Wagstaff
Welcome to AI Matter: volume 2, issue 1. AI Matters 2 (1) (2015)
Eric Eaton, Amy McGovern
Welcome to AI Matters, volume 2, issue 2. AI Matters 2 (2) (2015)
Haitham Bou-Ammar, Rasul Tutunov, Eric Eaton
Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret. ICML (2015)
Paul Ruvolo, Eric Eaton
Online Multi-Task Learning via Sparse Dictionary Optimization. AAAI (2014)
Eric Eaton, Marie desJardins, Sara Jacob
Multi-view constrained clustering with an incomplete mapping between views. Knowl. Inf. Syst. 38 (1) (2014)
Eric Eaton, Carla P. Gomes, Brian Charles Williams
Computational Sustainability. AI Mag. 35 (2) (2014)
Vishnu Purushothaman Sreenivasan, Haitham Bou-Ammar, Eric Eaton
Online Multi-Task Gradient Temporal-Difference Learning. AAAI (2014)
Rasul Tutunov, Haitham Bou-Ammar, Ali Jadbabaie, Eric Eaton
On the Degree Distribution of Pólya Urn Graph Processes. CoRR (2014)
Haitham Bou-Ammar, Eric Eaton, Paul Ruvolo, Matthew E. Taylor
Online Multi-Task Learning for Policy Gradient Methods. ICML (2014)
Eric Eaton, Carla P. Gomes, Brian Charles Williams
Computational Sustainability: Editorial Introduction to the Summer and Fall Issues. AI Mag. 35 (3) (2014)
Paul Ruvolo, Eric Eaton
ELLA: An Efficient Lifelong Learning Algorithm. ICML (1) (2013)
Vita Markman, Georgi Stojanov, Bipin Indurkhya, Takashi Kido, Keiki Takadama, George Dimitri Konidaris, Eric Eaton, Naohiro Matsumura, Renate Fruchter, Donald A. Sofge, William F. Lawless, Omid Madani, Rahul Sukthankar
Reports of the 2013 AAAI Spring Symposium Series. AI Mag. 34 (3) (2013)
Paul Ruvolo, Eric Eaton
Scalable Lifelong Learning with Active Task Selection. AAAI Spring Symposium: Lifelong Machine Learning (2013)
Paul Ruvolo, Eric Eaton
Active Task Selection for Lifelong Machine Learning. AAAI (2013)
Eric Eaton, Rachael Mansbach
A Spin-Glass Model for Semi-Supervised Community Detection. AAAI (2012)
Douglas H. Fisher, Bistra Dilkina, Eric Eaton, Carla Gomes
Incorporating Computational Sustainability into AI Education through a Freely-Available, Collectively-Composed Supplementary Lab Text. EAAI (2012)
Eric Eaton, Marie desJardins, Sara Jacob
Multi-view constrained clustering with an incomplete mapping between views CoRR (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Eric Eaton