Horvitz, Eric

87 publications

ICLR 2025 Improving Instruction-Following in Language Models Through Activation Steering Alessandro Stolfo, Vidhisha Balachandran, Safoora Yousefi, Eric Horvitz, Besmira Nushi

ICLR 2025 Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification Santiago Cortes-Gomez, Carlos Miguel Patiño, Yewon Byun, Steven Wu, Eric Horvitz, Bryan Wilder

AAAI 2024 When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming Hussein Mozannar, Gagan Bansal, Adam Fourney, Eric Horvitz

AISTATS 2023 Ideal Abstractions for Decision-Focused Learning Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz

AAAI 2022 A Search Engine for Discovery of Scientific Challenges and Directions Dan Lahav, Jon Saad-Falcon, Bailey Kuehl, Sophie Johnson, Sravanthi Parasa, Noam Shomron, Duen Horng Chau, Diyi Yang, Eric Horvitz, Daniel S. Weld, Tom Hope

NeurIPSW 2021 A Search Engine for Discovery of Scientific Challenges and Directions Dan Lahav, Jon Saad-Falcon, Bailey Kuehl, Sophie Johnson, Sravanthi Parasa, Noam Shomron, Duen Horng Chau, Diyi Yang, Eric Horvitz, Daniel S Weld, Tom Hope

NeurIPSW 2021 Bursting Scientific Filter Bubbles: Boosting Innovation via Novel Author Discovery Jason Portenoy, Marissa Radensky, Jevin West, Eric Horvitz, Daniel S Weld, Tom Hope

ICML 2021 Exploiting Structured Data for Learning Contagious Diseases Under Incomplete Testing Maggie Makar, Lauren West, David Hooper, Eric Horvitz, Erica Shenoy, John Guttag

AAAI 2021 Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork Gagan Bansal, Besmira Nushi, Ece Kamar, Eric Horvitz, Daniel S. Weld

CVPR 2021 Understanding Failures of Deep Networks via Robust Feature Extraction Sahil Singla, Besmira Nushi, Shital Shah, Ece Kamar, Eric Horvitz

JAIR 2020 Blind Spot Detection for Safe Sim-to-Real Transfer Ramya Ramakrishnan, Ece Kamar, Debadeepta Dey, Eric Horvitz, Julie Shah

IJCAI 2020 Learning to Complement Humans Bryan Wilder, Eric Horvitz, Ece Kamar

AAAI 2020 Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi, Sean Andrist, Eric Horvitz

ICLRW 2019 Bias Correction of Learned Generative Models via Likelihood-Free Importance Weighting Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric Horvitz, Stefano Ermon

AAAI 2019 Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution Ramya Ramakrishnan, Ece Kamar, Besmira Nushi, Debadeepta Dey, Julie Shah, Eric Horvitz

AAAI 2019 Reverse-Engineering Satire, or "Paper on Computational Humor Accepted Despite Making Serious Advances" Robert West, Eric Horvitz

AAAI 2019 Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications Galia Nordon, Gideon Koren, Varda Shalev, Eric Horvitz, Kira Radinsky

ICMLW 2019 Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling Andrey Kolobov, Yuval Peres, Cheng Lu, Eric Horvitz

AAAI 2019 Traffic Updates: Saying a Lot While Revealing a Little John Krumm, Eric Horvitz

AAAI 2019 Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff Gagan Bansal, Besmira Nushi, Ece Kamar, Daniel S. Weld, Walter S. Lasecki, Eric Horvitz

AAAI 2018 Optimizing Interventions via Offline Policy Evaluation: Studies in Citizen Science Avi Segal, Kobi Gal, Ece Kamar, Eric Horvitz, Grant Miller

AAAI 2017 Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Eric Horvitz

AAAI 2017 Long-Term Trends in the Public Perception of Artificial Intelligence Ethan Fast, Eric Horvitz

AAAI 2017 On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems Besmira Nushi, Ece Kamar, Eric Horvitz, Donald Kossmann

AAAI 2017 Predicting Mortality of Intensive Care Patients via Learning About Hazard Dae Hyun Lee, Eric Horvitz

AAAI 2017 Risk-Aware Planning: Methods and Case Study for Safer Driving Routes John Krumm, Eric Horvitz

IJCAI 2016 Intervention Strategies for Increasing Engagement in Crowdsourcing: Platform, Predictions, and Experiments Avi Segal, Ya'akov (Kobi) Gal, Ece Kamar, Eric Horvitz, Alex Bowyer, Grant Miller

JMLR 2016 Patient Risk Stratification with Time-Varying Parameters: A Multitask Learning Approach Jenna Wiens, John Guttag, Eric Horvitz

IJCAI 2015 Information Gathering in Networks via Active Exploration Adish Singla, Eric Horvitz, Pushmeet Kohli, Ryen White, Andreas Krause

IJCAI 2015 Metareasoning for Planning Under Uncertainty Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz

AAAI 2014 Signals in the Silence: Models of Implicit Feedback in a Recommendation System for Crowdsourcing Christopher H. Lin, Ece Kamar, Eric Horvitz

AAAI 2014 Stochastic Privacy Adish Singla, Eric Horvitz, Ece Kamar, Ryen White

AAAI 2013 Automated Workflow Synthesis Haoqi Zhang, Eric Horvitz, David C. Parkes

IJCAI 2013 Lifelong Learning for Acquiring the Wisdom of the Crowd Ece Kamar, Ashish Kapoor, Eric Horvitz

IJCAI 2013 Look Versus Leap: Computing Value of Information with High-Dimensional Streaming Evidence Stephanie Rosenthal, Dan Bohus, Ece Kamar, Eric Horvitz

AAAI 2012 Learning to Learn: Algorithmic Inspirations from Human Problem Solving Ashish Kapoor, Bongshin Lee, Desney S. Tan, Eric Horvitz

CVPR 2012 Memory Constrained Face Recognition Ashish Kapoor, Simon Baker, Sumit Basu, Eric Horvitz

NeurIPS 2012 Patient Risk Stratification for Hospital-Associated C. Diff as a Time-Series Classification Task Jenna Wiens, Eric Horvitz, John V. Guttag

AAAI 2012 Performance and Preferences: Interactive Refinement of Machine Learning Procedures Ashish Kapoor, Bongshin Lee, Desney S. Tan, Eric Horvitz

JAIR 2010 A Utility-Theoretic Approach to Privacy in Online Services Andreas Krause, Eric Horvitz

AAAI 2010 Generalized Task Markets for Human and Machine Computation Dafna Shahaf, Eric Horvitz

NeurIPS 2009 Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition Ashish Kapoor, Eric Horvitz

IJCAI 2009 Collaboration and Shared Plans in the Open World: Studies of Ridesharing Ece Kamar, Eric Horvitz

IJCAI 2009 Investigations of Continual Computation Dafna Shahaf, Eric Horvitz

AAAI 2008 A Utility-Theoretic Approach to Privacy and Personalization Andreas Krause, Eric Horvitz

IJCAI 2007 Models of Searching and Browsing: Languages, Studies, and Application Doug Downey, Susan T. Dumais, Eric Horvitz

UAI 2007 On Discarding, Caching, and Recalling Samples in Active Learning Ashish Kapoor, Eric Horvitz

IJCAI 2007 Selective Supervision: Guiding Supervised Learning with Decision-Theoretic Active Learning Ashish Kapoor, Eric Horvitz, Sumit Basu

JMLR 2006 Considering Cost Asymmetry in Learning Classifiers Francis R. Bach, David Heckerman, Eric Horvitz

AAAI 2006 Trip Router with Individualized Preferences (TRIP): Incorporating Personalization into Route Planning Julia Letchner, John Krumm, Eric Horvitz

AISTATS 2005 On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers Francis Bach, David Heckerman, Eric Horvitz

UAI 2005 Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service Eric Horvitz, Johnson Apacible, Raman Sarin, Lin Liao

AAAI 2004 The Backdoor Key: A Path to Understanding Problem Hardness Yongshao Ruan, Henry A. Kautz, Eric Horvitz

UAI 2003 Web-Based Question Answering: A Decision-Making Perspective David Azari, Eric Horvitz, Susan T. Dumais, Eric Brill

UAI 2002 Coordinates: Probabilistic Forecasting of Presence and Availability Eric Horvitz, Paul Koch, Carl Myers Kadie, Andy Jacobs

AAAI 2002 Dynamic Restart Policies Henry A. Kautz, Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Bart Selman

UAI 2001 A Bayesian Approach to Tackling Hard Computational Problems Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering

ICML 2000 A Normative Examination of Ensemble Learning Algorithms David M. Pennock, Pedrito Maynard-Reid Ii, C. Lee Giles, Eric Horvitz

UAI 2000 Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach David M. Pennock, Eric Horvitz, Steve Lawrence, C. Lee Giles

UAI 2000 Conversation as Action Under Uncertainty Tim Paek, Eric Horvitz

AAAI 2000 Social Choice Theory and Recommender Systems: Analysis of the Axiomatic Foundations of Collaborative Filtering David M. Pennock, Eric Horvitz, C. Lee Giles

UAI 1999 Attention-Sensitive Alerting Eric Horvitz, Andy Jacobs, David Hovel

IJCAI 1999 Continual Computation Policies for Allocating Offline and Real-Time Resources Eric Horvitz

UAI 1998 Inferring Informational Goals from Free-Text Queries: A Bayesian Approach David Heckerman, Eric Horvitz

UAI 1998 The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users Eric Horvitz, Jack S. Breese, David Heckerman, David Hovel, Koos Rommelse

AAAI 1997 Models of Continual Computation Eric Horvitz

UAI 1997 Perception, Attention, and Resources: A Decision-Theoretic Approach to Graphics Rendering Eric Horvitz, Jed Lengyel

UAI 1997 Time-Critical Action: Representations and Application Eric Horvitz, Adam Seiver

UAI 1996 A Graph-Theoretic Analysis of Information Value Kim-Leng Poh, Eric Horvitz

AAAI 1996 Challenge Problems for Artificial Intelligence (Panel Statements) Bart Selman, Rodney A. Brooks, Thomas L. Dean, Eric Horvitz, Tom M. Mitchell, Nils J. Nilsson

UAI 1996 UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, Reed College, Portland, Oregon, USA, August 1-4, 1996 Eric Horvitz, Finn Verner Jensen

UAI 1995 Display of Information for Time-Critical Decision Making Eric Horvitz, Matthew Barry

UAI 1995 Exploiting System Hierarchy to Compute Repair Plans in Probabilistic Model-Based Diagnosis Sampath Srinivas, Eric Horvitz

UAI 1995 Reasoning, Metareasoning, and Mathematical Truth: Studies of Theorem Proving Under Limited Resources Eric Horvitz, Adrian C. Klein

UAI 1993 Reasoning About the Value of Decision-Model Refinement: Methods and Application Kim-Leng Poh, Eric Horvitz

UAI 1993 Utility-Based Abstraction and Categorization Eric Horvitz, Adrian C. Klein

UAI 1992 Dynamic Network Models for Forecasting Paul Dagum, Adam Galper, Eric Horvitz

UAI 1992 Reformulating Inference Problems Through Selective Conditioning Paul Dagum, Eric Horvitz

UAI 1990 Ideal Reformulation of Belief Networks Jack S. Breese, Eric Horvitz

UAI 1990 Problem Formulation as the Reduction of a Decision Model David Heckerman, Eric Horvitz

IJCAI 1989 Reflection and Action Under Scarce Resources: Theoretical Principles and Empirical Study Eric Horvitz, Gregory F. Cooper, David Heckerman

AAAI 1988 Reasoning Under Varying and Uncertain Resource Constraints Eric Horvitz

AAAI 1987 On the Expressiveness of Rule-Based Systems for Reasoning with Uncertainty David Heckerman, Eric Horvitz

UAI 1987 Reasoning About Beliefs and Actions Under Computational Resource Constraints Eric Horvitz

AAAI 1986 A Framework for Comparing Alternative Formalisms for Plausible Reasoning Eric Horvitz, David Heckerman, Curtis P. Langlotz

UAI 1986 The Myth of Modularity in Rule-Based Systems for Reasoning with Uncertainty David Heckerman, Eric Horvitz

UAI 1985 The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research Eric Horvitz, David Heckerman