Melinda T. Gervasio

Publication Activity (10 Years)

Years Active: 1989-2023
Publications (10 Years): 15

Top Topics

Covariate Shift

Reinforcement Learning

Top Venues

Publications

Yunye Gong, Yi Yao, Xiao Lin, Ajay Divakaran, Melinda T. Gervasio
Confidence Calibration for Systems with Cascaded Predictive Modules. CoRR (2023)
Pedro Sequeira, Melinda T. Gervasio
IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit Based on Analyses of Interestingness. xAI (1) (2023)
Pedro Sequeira, Melinda T. Gervasio
IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit based on Analyses of Interestingness. CoRR (2023)
Eric Yeh, Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio
Outcome-Guided Counterfactuals from a Jointly Trained Generative Latent Space. xAI (3) (2023)
Eric Yeh, Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio
Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space. CoRR (2022)
Pedro Sequeira, Daniel Elenius, Jesse Hostetler, Melinda T. Gervasio
A Framework for Understanding and Visualizing Strategies of RL Agents. CoRR (2022)
Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio
Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning. CoRR (2022)
Yunye Gong, Xiao Lin, Yi Yao, Thomas G. Dietterich, Ajay Divakaran, Melinda T. Gervasio
Confidence Calibration for Domain Generalization under Covariate Shift. ICCV (2021)
Yunye Gong, Xiao Lin, Yi Yao, Thomas G. Dietterich, Ajay Divakaran, Melinda T. Gervasio
Confidence Calibration for Domain Generalization under Covariate Shift. CoRR (2021)
Pedro Sequeira, Melinda T. Gervasio
Interestingness elements for explainable reinforcement learning: Understanding agents' capabilities and limitations. Artif. Intell. 288 (2020)
Pedro Sequeira, Eric Yeh, Melinda T. Gervasio
Interestingness Elements for Explainable Reinforcement Learning through Introspection. IUI Workshops (2019)
Pedro Sequeira, Melinda T. Gervasio
Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations. CoRR (2019)
Melinda T. Gervasio, Karen L. Myers, Eric Yeh, Boone Adkins
Explanation to Avert Surprise. IUI Workshops (2018)
Pauline M. Berry, Thierry Donneau-Golencer, Khang Duong, Melinda T. Gervasio, Bart Peintner, Neil Yorke-Smith
Evaluating intelligent knowledge systems: experiences with a user-adaptive assistant agent. Knowl. Inf. Syst. 52 (2) (2017)
Karen L. Myers, Melinda T. Gervasio
Solution Authoring via Demonstration and Annotation: An Empirical Study. ICALT (2016)
Karen L. Myers, Melinda T. Gervasio, Christian Jones, Kyle McIntyre, Kellie Keifer
Drill Evaluation for Training Procedural Skills. AIED (2013)
Melinda T. Gervasio, Thomas J. Lee
Discovering action idioms bridging the gap between system-level events and human-level actions. VL/HCC (2013)
Karen L. Myers, Jake Kolojejchick, Carl Angiolillo, Tim Cummings, Tom Garvey, Matthew E. Gaston, Melinda T. Gervasio, Will Haines, Chris Jones, Kellie Keifer, Janette Knittel, David N. Morley, William Ommert, Scott Potter
Learning by Demonstration for a Collaborative Planning Environment. AI Mag. 33 (2) (2012)
Karen L. Myers, Jake Kolojejchick, Carl Angiolillo, Tim Cummings, Tom Garvey, Melinda T. Gervasio, Will Haines, Chris Jones, Janette Knittel, David N. Morley, William Ommert, Scott Potter
Learning by Demonstration Technology for Military Planning and Decision Making: A Deployment Story. IAAI (2011)
Pauline M. Berry, Melinda T. Gervasio, Bart Peintner, Neil Yorke-Smith
PTIME: Personalized assistance for calendaring. ACM Trans. Intell. Syst. Technol. 2 (4) (2011)
Melinda T. Gervasio, Will Haines, David N. Morley, Thomas J. Lee, C. Adam Overholtzer, Shahin Saadati, Aaron Spaulding
How to serve soup: interleaving demonstration and assisted editing to support nonprogrammers. IUI (2011)
Melinda T. Gervasio, Eric Yeh, Karen L. Myers
Learning to ask the right questions to help a learner learn. IUI (2011)
Pauline M. Berry, Thierry Donneau-Golencer, Khang Duong, Melinda T. Gervasio, Bart Peintner, Neil Yorke-Smith
Evaluating User-Adaptive Systems: Lessons from Experiences with a Personalized Meeting Scheduling Assistant. IAAI (2009)
Melinda T. Gervasio, Karen L. Myers, Marie desJardins, Fusun Yaman
Question Asking to Inform Preference Learning: A Case Study. AAAI Spring Symposium: Agents that Learn from Human Teachers (2009)
Melinda T. Gervasio, Janet L. Murdock
What were you thinking?: filling in missing dataflow through inference in learning from demonstration. IUI (2009)
Steven Eker, Thomas J. Lee, Melinda T. Gervasio
Iteration Learning by Demonstration. AAAI Spring Symposium: Agents that Learn from Human Teachers (2009)
Thomas D. Garvey, Melinda T. Gervasio, Thomas J. Lee, Karen L. Myers, Carl Angiolillo, Matthew E. Gaston, Janette Knittel, Jake Kolojejchick
Learning by Demonstration to Support Military Planning and Decision Making. IAAI (2009)
Aaron Spaulding, Jim Blythe, Will Haines, Melinda T. Gervasio
From geek to sleek: integrating task learning tools to support end users in real-world applications. IUI (2009)
Karen L. Myers, Pauline Berry, Jim Blythe, Ken Conley, Melinda T. Gervasio, Deborah L. McGuinness, David N. Morley, Avi Pfeffer, Martha E. Pollack, Milind Tambe
An Intelligent Personal Assistant for Task and Time Management. AI Mag. 28 (2) (2007)
Pauline M. Berry, Melinda T. Gervasio, Bart Peintner, Tomás E. Uribe, Neil Yorke-Smith
Multi-Criteria Evaluation in User-Centric Distributed Scheduling Agents. AAAI Spring Symposium: Distributed Plan and Schedule Management (2006)
Pauline Berry, Bart Peintner, Ken Conley, Melinda T. Gervasio, Tomás E. Uribe, Neil Yorke-Smith
Deploying a personalized time management agent. AAMAS (2006)
Melinda T. Gervasio, Michael D. Moffitt, Martha E. Pollack, Joseph M. Taylor, Tomás E. Uribe
Active preference learning for personalized calendar scheduling assistance. IUI (2005)
Pauline M. Berry, Melinda T. Gervasio, Tomás E. Uribe, Martha E. Pollack, Michael D. Moffitt
A Personalized Time Management Assistant: Research Directions. AAAI Spring Symposium: Persistent Assistants: Living and Working with AI (2005)
Jungsoon P. Yoo, Melinda T. Gervasio, Pat Langley
An adaptive stock tracker for personalized trading advice. IUI (2003)
Jungsoon P. Yoo, Melinda T. Gervasio, Pat Langley
Personalized trading recommendation system. IUI (2003)
Wayne Iba, Melinda T. Gervasio
Adapting to User Preferences in Crisis Response. IUI (1999)
Melinda T. Gervasio, Wayne Iba, Pat Langley
Learning User Evaluation Functions for Adaptive Scheduling Assistance. ICML (1999)
Melinda T. Gervasio, Wayne Iba, Pat Langley
Learning to Predict User Operations for Adaptive Scheduling. AAAI/IAAI (1998)
Melinda T. Gervasio, Gerald DeJong
An Incremental Learning Approach for Completable Planning. ICML (1994)
Sang-Chan Park, Melinda T. Gervasio, Michael J. Shaw, Gerald DeJong
Explanation-based learning for intelligent process planning. IEEE Trans. Syst. Man Cybern. 23 (6) (1993)
Steve A. Chien, Melinda T. Gervasio, Gerald DeJong
On Becoming Decreasingly Reactive: Learning to Deliberate Minimally. ML (1991)
Melinda T. Gervasio
Learning General Completable Reactive Plans. AAAI (1990)
Melinda T. Gervasio, Gerald DeJong
Explanation-Based Learning of Reactive Operations. ML (1989)