Eric Eaton - RankMe

141 papers A* 33A 6Journal 85Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Model Agreement via Anchoring. CoRR Eric Eaton, Surbhi Goel, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell
2026	J	`jnl`	Observer: creation of a novel multimodal dataset for outpatient care research. J. Am. Medical Informatics Assoc. Kevin B. Johnson, Basam Alasaly, Kuk Jin Jang, Eric Eaton, Sriharsha Mopidevi, Ross Koppel
2026	J	`jnl`	OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies. CoRR Yunzhou Song, Long Le, Yong-Hyun Park, Jie Wang, Junyao Shi, Lingjie Liu, Jiatao Gu, Eric Eaton, Dinesh Jayaraman, Kostas Daniilidis
2026	J	`jnl`	Slot-BERT: Self-supervised object discovery in surgical video. Medical Image Anal. Guiqiu Liao, Matjaz Jogan, Marcel Hussing, Kenta Nakahashi, Kazuhiro Yasufuku, Amin Madani, Eric Eaton, Daniel A. Hashimoto
2025	J	`jnl`	A Multi-Robot Platform for Robotic Triage Combining Onboard Sensing and Foundation Models. CoRR Jason Hughes, Marcel Hussing, Edward Zhang, Shenbagaraj Kannapiran, Joshua Caswell, Kenneth Chaney, Ruichen Deng, Michaela Feehery, Agelos Kratimenos, Yi Fan Li, Britny Major, Ethan Sanchez, Sumukh Shrote, Youkang Wang, Jeremy Wang, Daudi Zein, Luying Zhang, Ruijun Zhang, Alex Zhou, Tenzi Zhouga, Jeremy Cannon, Zaffir Qasim, Jay Yelon, Fernando Cladera, Kostas Daniilidis, Camillo J. Taylor, Eric Eaton
2025	A*	`conf`	Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model. ICLR Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton
2025	A*	`conf`	Assessing Modality Bias in Video Question Answering Benchmarks with Multimodal Large Language Models. AAAI Jean Park, Kuk Jin Jang, Basam Alasaly, Sriharsha Mopidevi, Andrew Zolensky, Eric Eaton, Insup Lee, Kevin B. Johnson
2025	A	`conf`	Disentangling Spatio-Temporal Knowledge for Weakly Supervised Object Detection and Segmentation in Surgical Video. WACV Guiqiu Liao, Matjaz Jogan, Sai Koushik, Eric Eaton, Daniel A. Hashimoto
2025	J	`jnl`	FORLA:Federated Object-centric Representation Learning with Slot Attention. CoRR Guiqiu Liao, Matjaz Jogan, Eric Eaton, Daniel A. Hashimoto
2025	—	`conf`	Future Slot Prediction for Unsupervised Object Discovery in Surgical Video. MICCAI (11) Guiqiu Liao, Matjaz Jogan, Marcel Hussing, Edward Zhang, Eric Eaton, Daniel A. Hashimoto
2025	J	`jnl`	Future Slot Prediction for Unsupervised Object Discovery in Surgical Video. CoRR Guiqiu Liao, Matjaz Jogan, Marcel Hussing, Edward Zhang, Eric Eaton, Daniel A. Hashimoto
2025	A*	`conf`	Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces. ICML Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell
2025	J	`jnl`	Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces. CoRR Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell
2025	J	`jnl`	Iterative Compositional Data Generation for Robot Control. CoRR Anh-Quan Pham, Marcel Hussing, Shubhankar P. Patankar, Dani S. Bassett, Jorge Mendez-Mendez, Eric Eaton
2025	A*	`conf`	MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL. ICLR Claas Voelcker, Marcel Hussing, Eric Eaton, Amir-massoud Farahmand, Igor Gilitschenski
2025	J	`jnl`	MedVidDeID: Protecting privacy in clinical encounter video recordings. J. Biomed. Informatics Sriharsha Mopidevi, Kuk Jin Jang, Basam Alasaly, Sydney Pugh, Jean Park, Ashley Batugo, Sy Hwang, Eric Eaton, Danielle Lee Mowery, Kevin B. Johnson
2025	A*	`conf`	Neural Eulerian Scene Flow Fields. ICLR Kyle Vedder, Neehar Peri, Ishan Khatri, Siyi Li, Eric Eaton, Mehmet Kemal Kocamaz, Yue Wang, Zhiding Yu, Deva Ramanan, Joachim Pehserl
2025	J	`jnl`	Pixie: Fast and Generalizable Supervised Learning of 3D Physics from Pixels. CoRR Long Le, Ryan Lucas, Chen Wang, Chuhao Chen, Dinesh Jayaraman, Eric Eaton, Lingjie Liu
2025	J	`jnl`	Relative Entropy Pathwise Policy Optimization. CoRR Claas Voelcker, Axel Brunnbauer, Marcel Hussing, Michal Nauman, Pieter Abbeel, Eric Eaton, Radu Grosu, Amir-massoud Farahmand, Igor Gilitschenski
2025	J	`jnl`	Replicable Reinforcement Learning with Linear Function Approximation. CoRR Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell
2025	J	`jnl`	Slot-BERT: Self-supervised Object Discovery in Surgical Video. CoRR Guiqiu Liao, Matjaz Jogan, Marcel Hussing, Kenta Nakahashi, Kazuhiro Yasufuku, Amin Madani, Eric Eaton, Daniel A. Hashimoto
2024	A*	`conf`	A Metacognitive Approach to Out-of-Distribution Detection for Segmentation. ICRA Meghna Gummadi, Cassandra Kent, Karl Schmeckpeper, Eric Eaton
2024	J	`jnl`	A collective AI via lifelong learning and sharing at the edge. Nat. Mac. Intell. 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
2024	J	`jnl`	Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model. CoRR Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton
2024	A*	`conf`	Artificial Intelligence in the CS2023 Undergraduate Computer Science Curriculum: Rationale and Challenges. AAAI Eric Eaton, Susan L. Epstein
2024	J	`jnl`	Assessing Modality Bias in Video Question Answering Benchmarks with Multimodal Large Language Models. CoRR Jean Park, Kuk Jin Jang, Basam Alasaly, Sriharsha Mopidevi, Andrew Zolensky, Eric Eaton, Insup Lee, Kevin B. Johnson
2024	J	`jnl`	Can we hop in general? A discussion of benchmark selection and design using the Hopper environment. CoRR Claas Völcker, Marcel Hussing, Eric Eaton
2024	J	`jnl`	Disentangling spatio-temporal knowledge for weakly supervised object detection and segmentation in surgical video. CoRR Guiqiu Liao, Matjaz Jogan, Sai Koushik, Eric Eaton, Daniel A. Hashimoto
2024	J	`jnl`	Dissecting Deep RL with High Update Ratios: Combatting Value Divergence. RLJ Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton
2024	J	`jnl`	Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence. CoRR Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton
2024	J	`jnl`	Distributed Continual Learning. CoRR Long Le, Marcel Hussing, Eric Eaton
2024	J	`jnl`	MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL. CoRR Claas Völcker, Marcel Hussing, Eric Eaton, Amir-massoud Farahmand, Igor Gilitschenski
2024	J	`jnl`	Neural Eulerian Scene Flow Fields. CoRR Kyle Vedder, Neehar Peri, Ishan Khatri, Siyi Li, Eric Eaton, Mehmet Kemal Kocamaz, Yue Wang, Zhiding Yu, Deva Ramanan, Joachim Pehserl
2024	J	`jnl`	Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning. RLJ Marcel Hussing, Jorge A. Mendez, Anisha Singrodia, Cassandra Kent, Eric Eaton
2024	A*	`conf`	ZeroFlow: Scalable Scene Flow via Distillation. ICLR Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays
2023	J	`jnl`	A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR 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 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
2023	J	`jnl`	A Metacognitive Approach to Out-of-Distribution Detection for Segmentation. CoRR Meghna Gummadi, Cassandra Kent, Karl Schmeckpeper, Eric Eaton
2023	J	`jnl`	A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks 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 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
2023	A*	`conf`	CAROM Air - Vehicle Localization and Traffic Scene Reconstruction from Aerial Videos. ICRA Duo Lu, Eric Eaton, Matt Weg, Wei Wang, Steven Como, Jeffrey Wishart, Hongbin Yu, Yezhou Yang
2023	J	`jnl`	CAROM Air - Vehicle Localization and Traffic Scene Reconstruction from Aerial Videos. CoRR Duo Lu, Eric Eaton, Matt Weg, Wei Wang, Steven Como, Jeffrey Wishart, Hongbin Yu, Yezhou Yang
2023	—	`conf`	Fuzzy Logic++: Towards Developing Fuzzy Education Curricula Using ACM/IEEE/AAAI CS2023. NAFIPS Christian Servin, Brett A. Becker, Eric Eaton, Amruth N. Kumar
2023	J	`jnl`	Gap Minimization for Knowledge Sharing and Transfer. J. Mach. Learn. Res. Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Gezheng Xu, Christian Gagné, Eric Eaton
2023	J	`jnl`	How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition. Trans. Mach. Learn. Res. Jorge A. Mendez, Eric Eaton
2023	—	`conf`	Machine Learning Models for Histopathological Breast Cancer Image Classification. AIIoT Samantha Haines, Eric Eaton, Md Liakat Ali
2023	—	`conf`	Prospective Learning: Principled Extrapolation to the Future. CoLLAs Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael L. Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam S. 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
2023	A*	`conf`	Replicable Reinforcement Learning. NeurIPS Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell
2023	J	`jnl`	Replicable Reinforcement Learning. CoRR Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell
2023	J	`jnl`	Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning. CoRR Marcel Hussing, Jorge A. Mendez, Anisha Singrodia, Cassandra Kent, Eric Eaton
2023	J	`jnl`	Zero-shot Task Preference Addressing Enabled by Imprecise Bayesian Continual Learning. CoRR Pengyuan Lu, Michele Caprio, Eric Eaton, Insup Lee
2023	J	`jnl`	ZeroFlow: Fast Zero Label Scene Flow via Distillation. CoRR Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays
2022	—	`conf`	CompoSuite: A Compositional Reinforcement Learning Benchmark. CoLLAs Jorge A. Mendez, Marcel Hussing, Meghna Gummadi, Eric Eaton
2022	J	`jnl`	CompoSuite: A Compositional Reinforcement Learning Benchmark. CoRR Jorge A. Mendez, Marcel Hussing, Meghna Gummadi, Eric Eaton
2022	J	`jnl`	Gap Minimization for Knowledge Sharing and Transfer. CoRR Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Christian Gagné, Eric Eaton
2022	J	`jnl`	How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition. CoRR Jorge A. Mendez, Eric Eaton
2022	J	`jnl`	Land Use Prediction using Electro-Optical to SAR Few-Shot Transfer Learning. CoRR Marcel Hussing, Karen Li, Eric Eaton
2022	J	`jnl`	Lifelong Inverse Reinforcement Learning. CoRR Jorge A. Mendez, Shashank Shivkumar, Eric Eaton
2022	A*	`conf`	Modular Lifelong Reinforcement Learning via Neural Composition. ICLR Jorge A. Mendez, Harm van Seijen, Eric Eaton
2022	J	`jnl`	Modular Lifelong Reinforcement Learning via Neural Composition. CoRR Jorge A. Mendez, Harm van Seijen, Eric Eaton
2022	J	`jnl`	Prospective Learning: Back to the Future. CoRR Joshua T. Vogelstein, Timothy D. 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 S. 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 L. Platt, Lyle H. 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
2022	—	`conf`	SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries. CoLLAs Meghna Gummadi, David Kent, Jorge A. Mendez, Eric Eaton
2022	J	`jnl`	SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries. CoRR Meghna Gummadi, David Kent, Jorge A. Mendez, Eric Eaton
2022	A	`conf`	Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems. IROS Kyle Vedder, Eric Eaton
2021	A*	`conf`	Lifelong Learning of Compositional Structures. ICLR Jorge A. Mendez, Eric Eaton
2021	A*	`conf`	Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer. ICML Seungwon Lee, Sima Behpour, Eric Eaton
2021	J	`jnl`	Sparse PointPillars: Exploiting Sparsity in Birds-Eye-View Object Detection. CoRR Kyle Vedder, Eric Eaton
2021	J	`jnl`	Towards a theory of out-of-distribution learning. CoRR Ali Geisa, Ronak D. Mehta, Hayden S. Helm, Jayanta Dey, Eric Eaton, Carey E. Priebe, Joshua T. Vogelstein
2020	J	`jnl`	Lifelong Learning of Compositional Structures. CoRR Jorge A. Mendez, Eric Eaton
2020	A*	`conf`	Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting. NeurIPS Jorge A. Mendez, Boyu Wang, Eric Eaton
2020	J	`jnl`	Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting. CoRR Jorge A. Mendez, Boyu Wang, Eric Eaton
2020	J	`jnl`	Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer. J. Artif. Intell. Res. Mohammad Rostami, David Isele, Eric Eaton
2019	A*	`conf`	A Lightweight Approach to Academic Research Group Management Using Online Tools: Spend More Time on Research and Less on Management. AAAI Eric Eaton
2019	J	`jnl`	Artificial Intelligence for Pediatric Ophthalmology. CoRR Julia E. Reid, Eric Eaton
2019	J	`jnl`	Deep Transfer Learning for Few-Shot SAR Image Classification. Remote. Sens. Mohammad Rostami, Soheil Kolouri, Eric Eaton, Kyungnam Kim
2019	J	`jnl`	Expert-Augmented Machine Learning. CoRR Efstathios D. Gennatas, Jerome 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
2019	A*	`conf`	Learning Shared Knowledge for Deep Lifelong Learning using Deconvolutional Networks. IJCAI Seungwon Lee, James Stokes, Eric Eaton
2019	—	`conf`	SAR Image Classification Using Few-Shot Cross-Domain Transfer Learning. CVPR Workshops Mohammad Rostami, Soheil Kolouri, Eric Eaton, Kyungnam Kim
2019	A*	`conf`	Transfer Learning via Minimizing the Performance Gap Between Domains. NeurIPS Boyu Wang, Jorge A. Mendez, Mingbo Cai, Eric Eaton
2019	J	`jnl`	Zero-Shot Image Classification Using Coupled Dictionary Embedding. CoRR Mohammad Rostami, Soheil Kolouri, Zak Murez, Yuri Owekcho, Eric Eaton, Kyungnam Kim
2018	J	`jnl`	A Recap of the AAAI and IAAI 2018 Conferences and the EAAI Symposium. AI Mag. Sheila A. McIlraith, Kilian Q. Weinberger, G. Michael Youngblood, Karen L. Myers, Eric Eaton, Michael Wollowski
2018	J	`jnl`	An interview with Ayanna Howard. AI Matters Amy McGovern, Eric Eaton
2018	J	`jnl`	Blue sky ideas in artificial intelligence education from the EAAI 2017 new and future AI educator program. AI Matters 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
2018	A*	`conf`	Lifelong Inverse Reinforcement Learning. NeurIPS Jorge A. Mendez, Shashank Shivkumar, Eric Eaton
2018	A*	`conf`	Lifelong Learning Networks: Beyond Single Agent Lifelong Learning. AAAI Mohammad Rostami, Eric Eaton
2018	A	`conf`	Modeling Consecutive Task Learning with Task Graph Agendas. AAMAS David Isele, Eric Eaton, Mark Roberts, David W. Aha
2018	A	`conf`	Multi-Agent Distributed Lifelong Learning for Collective Knowledge Acquisition. AAMAS Mohammad Rostami, Soheil Kolouri, Kyungnam Kim, Eric Eaton
2018	J	`jnl`	Welcome to AI matters 4(1). AI Matters Amy McGovern, Eric Eaton
2018	J	`jnl`	Welcome to AI matters, volume 3, issue 4. AI Matters Eric Eaton, Amy McGovern
2017	J	`jnl`	ACM SIGAI activity report. AI Matters 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
2017	J	`jnl`	AI profiles: an interview with Jim Kurose. AI Matters Amy McGovern, Eric Eaton
2017	J	`jnl`	AI profiles: an interview with Maja Matarić. AI Matters Amy McGovern, Eric Eaton
2017	J	`jnl`	AI profiles: an interview with Peter Stone. AI Matters Amy McGovern, Eric Eaton
2017	J	`jnl`	Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program. CoRR 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
2017	J	`jnl`	Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines. Pattern Recognit. Decebal Constantin Mocanu, Haitham Bou-Ammar, Luis Puig, Eric Eaton, Antonio Liotta
2017	—	`conf`	Lifelong Learning with Gaussian Processes. ECML/PKDD (2) Christopher Clingerman, Eric Eaton
2017	J	`jnl`	Multi-Agent Distributed Lifelong Learning for Collective Knowledge Acquisition. CoRR Mohammad Rostami, Soheil Kolouri, Kyungnam Kim, Eric Eaton
2017	J	`jnl`	Teaching Integrated AI through Interdisciplinary Project-Driven Courses. AI Mag. Eric Eaton
2017	J	`jnl`	Tree-Structured Boosting: Connections Between Gradient Boosted Stumps and Full Decision Trees. CoRR José-Marcio Luna, Eric Eaton, Lyle H. Ungar, Eric S. Diffenderfer, Shane T. Jensen, Efstathios D. Gennatas, Mateo Wirth, Charles B. Simone II, Timothy D. Solberg, Gilmer Valdes
2017	J	`jnl`	Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer. CoRR David Isele, Mohammad Rostami, Eric Eaton
2017	J	`jnl`	Welcome to AI matters, volume 3, issue 2. AI Matters Eric Eaton, Amy McGovern
2017	J	`jnl`	Welcome to AI matters, volume 3, issue 3. AI Matters Eric Eaton, Amy McGovern
2016	J	`jnl`	AI profiles: an interview with Peter Norvig. AI Matters Amy McGovern, Eric Eaton
2016	J	`jnl`	Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines. CoRR Decebal Constantin Mocanu, Haitham Bou-Ammar, Luis Puig, Eric Eaton, Antonio Liotta
2016	A	`conf`	Lifelong learning for disturbance rejection on mobile robots. IROS David Isele, José-Marcio Luna, Eric Eaton, Gabriel Victor de la Cruz, James Irwin, Brandon Kallaher, Matthew E. Taylor
2016	J	`jnl`	Online Contrastive Divergence with Generative Replay: Experience Replay without Storing Data. CoRR Decebal Constantin Mocanu, Maria Torres Vega, Eric Eaton, Peter Stone, Antonio Liotta
2016	A*	`conf`	Using Task Features for Zero-Shot Knowledge Transfer in Lifelong Learning. IJCAI David Isele, Mohammad Rostami, Eric Eaton
2016	J	`jnl`	Welcome to AI Matters, volume 2, issue 3. AI Matters Eric Eaton, Amy McGovern
2015	A*	`conf`	Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning. IJCAI Haitham Bou-Ammar, Eric Eaton, José-Marcio Luna, Paul Ruvolo
2015	—	`ed.`	Knowledge, Skill, and Behavior Transfer in Autonomous Robots, Papers from the 2015 AAAI Workshop, Austin, Texas, USA, January 25, 2015. AAAI Workshop: Knowledge, Skill, and Behavior Transfer in Autonomous Robots Matteo Leonetti, Eric Eaton
2015	J	`jnl`	Reports from the 2015 AAAI Workshop Program. AI Mag. 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
2015	A*	`conf`	Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret. ICML Haitham Bou-Ammar, Rasul Tutunov, Eric Eaton
2015	J	`jnl`	Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret. CoRR Haitham Bou-Ammar, Rasul Tutunov, Eric Eaton
2015	A*	`conf`	Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment. AAAI Haitham Bou-Ammar, Eric Eaton, Paul Ruvolo, Matthew E. Taylor
2015	J	`jnl`	Welcome to AI Matter: volume 2, issue 1. AI Matters Eric Eaton, Kiri L. Wagstaff
2015	J	`jnl`	Welcome to AI Matters, volume 2, issue 2. AI Matters Eric Eaton, Amy McGovern
2015	J	`jnl`	Who speaks for AI? AI Matters Eric Eaton, Tom Dietterich, Maria L. Gini, Barbara J. Grosz, Charles L. Isbell Jr., Subbarao Kambhampati, Michael L. Littman, Francesca Rossi, Stuart Russell, Peter Stone, Toby Walsh, Michael J. Wooldridge
2014	J	`jnl`	Computational Sustainability. AI Mag. Eric Eaton, Carla P. Gomes, Brian Charles Williams
2014	J	`jnl`	Computational Sustainability: Editorial Introduction to the Summer and Fall Issues. AI Mag. Eric Eaton, Carla P. Gomes, Brian Charles Williams
2014	J	`jnl`	Multi-view constrained clustering with an incomplete mapping between views. Knowl. Inf. Syst. Eric Eaton, Marie desJardins, Sara Jacob
2014	J	`jnl`	On the Degree Distribution of Pólya Urn Graph Processes. CoRR Rasul Tutunov, Haitham Bou-Ammar, Ali Jadbabaie, Eric Eaton
2014	A*	`conf`	Online Multi-Task Gradient Temporal-Difference Learning. AAAI Vishnu Purushothaman Sreenivasan, Haitham Bou-Ammar, Eric Eaton
2014	A*	`conf`	Online Multi-Task Learning for Policy Gradient Methods. ICML Haitham Bou-Ammar, Eric Eaton, Paul Ruvolo, Matthew E. Taylor
2014	A*	`conf`	Online Multi-Task Learning via Sparse Dictionary Optimization. AAAI Paul Ruvolo, Eric Eaton
2013	A*	`conf`	Active Task Selection for Lifelong Machine Learning. AAAI Paul Ruvolo, Eric Eaton
2013	—	`conf`	ELLA: An Efficient Lifelong Learning Algorithm. ICML (1) Paul Ruvolo, Eric Eaton
2013	J	`jnl`	Reports of the 2013 AAAI Spring Symposium Series. AI Mag. 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
2013	—	`conf`	Scalable Lifelong Learning with Active Task Selection. AAAI Spring Symposium: Lifelong Machine Learning Paul Ruvolo, Eric Eaton
2012	A*	`conf`	A Spin-Glass Model for Semi-Supervised Community Detection. AAAI Eric Eaton, Rachael A. Mansbach
2012	—	`conf`	Incorporating Computational Sustainability into AI Education through a Freely-Available, Collectively-Composed Supplementary Lab Text. EAAI Douglas H. Fisher, Bistra Dilkina, Eric Eaton, Carla Gomes
2012	J	`jnl`	Multi-view constrained clustering with an incomplete mapping between views CoRR Eric Eaton, Marie desJardins, Sara Jacob
2011	A*	`conf`	Selective Transfer Between Learning Tasks Using Task-Based Boosting. AAAI Eric Eaton, Marie desJardins
2011	—	`conf`	The Importance of Selective Knowledge Transfer for Lifelong Learning. Lifelong Learning Eric Eaton, Terran Lane
2010	A*	`conf`	Interactive Learning Using Manifold Geometry. AAAI Eric Eaton, Gary Holness, Daniel McFarlane
2010	J	`jnl`	Modelling and learning user preferences over sets. J. Exp. Theor. Artif. Intell. Kiri L. Wagstaff, Marie desJardins, Eric Eaton
2010	A	`conf`	Multi-view clustering with constraint propagation for learning with an incomplete mapping between views. CIKM Eric Eaton, Marie desJardins, Sara Jacob
2009	—	`conf`	Interactive Learning Using Manifold Geometry. AAAI Fall Symposium: Manifold Learning and Its Applications Eric Eaton, Gary Holness, Daniel McFarlane
2009	—	`conf`	Set-Based Boosting for Instance-Level Transfer. ICDM Workshops Eric Eaton, Marie desJardins
2008	—	`conf`	Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer. ECML/PKDD (1) Eric Eaton, Marie desJardins, Terran Lane
2007	A*	`conf`	Using Multiresolution Learning for Transfer in Image Classification. AAAI Eric Eaton, Marie desJardins, John Stevenson
2006	A*	`conf`	Learning user preferences for sets of objects. ICML Marie desJardins, Eric Eaton, Kiri Wagstaff
2006	A*	`conf`	Multi-Resolution Learning for Knowledge Transfer. AAAI Eric Eaton
2005	—	`conf`	A Context-Sensitive and User-Centric Approach to Developing Personal Assistants. AAAI Spring Symposium: Persistent Assistants: Living and Working with AI Marie desJardins, Eric Eaton, Kiri Wagstaff