Geoffrey J. Gordon

Robert F. Murphy, Geoffrey J. Gordon, Ting Zhao, 2006, 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

A New View of Predictive State Methods for Dynamical System Learning pdf

Geoffrey J. Gordon, Ahmed Hefny, Carlton Downey, 2015, ArXiv.

Spectral Approaches to Learning Predictive Representations

Byron Boots, Geoffrey J. Gordon, Byron Boots, 2011 .

Individualized Bayesian Knowledge Tracing Models

Kenneth R. Koedinger, Geoffrey J. Gordon, Michael Yudelson, 2013, AIED.

A novel approximate inference approach to automated classification of protein subcellular location patterns in multi-cell images

Robert F. Murphy, Geoffrey J. Gordon, Shann-Ching Chen, 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

Visibility-based Pursuit-evasion with Limited Field of View

Sebastian Thrun, Geoffrey J. Gordon, Brian P. Gerkey, 2004, Int. J. Robotics Res..

Distributed Planning in Hierarchical Factored MDPs pdf

Geoffrey J. Gordon, Carlos Guestrin, Carlos Guestrin, 2002, UAI.

On Learning Invariant Representations for Domain Adaptation

Han Zhao, Kun Zhang, Geoffrey J. Gordon, 2019, ICML.

No-regret learning and a mechanism for distributed multiagent planning

Geoffrey J. Gordon, Jan-P. Calliess, J. Calliess, 2008, AAMAS.

Anytime Point-Based Approximations for Large POMDPs

Joelle Pineau, Sebastian Thrun, Geoffrey J. Gordon, 2006, J. Artif. Intell. Res..

Online Fitted Reinforcement Learning

Geoffrey J. Gordon, 1995 .

Closing the learning-planning loop with predictive state representations

Byron Boots, Geoffrey J. Gordon, Sajid M. Siddiqi, 2009, Int. J. Robotics Res..

Exponential Family PCA for Belief Compression in POMDPs

Nicholas Roy, Geoffrey J. Gordon, N. Roy, 2002, NIPS.

Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games

Geoffrey J. Gordon, Chris Murray, C. Murray, 2006, NIPS.

Galerkin Methods for Complementarity Problems and Variational Inequalities pdf

Geoffrey J. Gordon, 2013, ArXiv.

Learning Neural Networks with Adaptive Regularization

Han Zhao, Ruslan Salakhutdinov, Geoffrey J. Gordon, 2019, NeurIPS.

Hybrid Theorem Proving of Aerospace Systems: Applications and Challenges

Jean-Baptiste Jeannin, André Platzer, Peter Capell, 2014, J. Aerosp. Inf. Syst..

A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games

Miroslav Dudík, Geoffrey J. Gordon, Miroslav Dudík, 2009, UAI.

On Learning Invariant Representation for Domain Adaptation pdf

Kun Zhang, Han Zhao, Geoffrey J. Gordon, 2019, ArXiv.

Learning low dimensional predictive representations

Sebastian Thrun, Geoffrey J. Gordon, Matthew Rosencrantz, 2004, ICML.

Adaptive Sampling for Multi-Robot Wide-Area Exploration

Kian Hsiang Low, Pradeep K. Khosla, Geoffrey J. Gordon, 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

Game Theoretic Control for Robot Teams

Jeff G. Schneider, Geoffrey J. Gordon, Sebastian Thrun, 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

A Constraint Generation Approach to Learning Stable Linear Dynamical Systems

Byron Boots, Geoffrey J. Gordon, Sajid M. Siddiqi, 2007, NIPS.

Planning under Uncertainty for Reliable Health Care Robotics

Sebastian Thrun, Nicholas Roy, Geoffrey J. Gordon, 2003, FSR.

Learning Filaments

Geoffrey J. Gordon, Andrew Moore, 2000, ICML.

Automated image analysis of protein localization in budding yeast

Robert F. Murphy, Geoffrey J. Gordon, Ting Zhao, 2007, ISMB/ECCB.

Model Uncertainty in Classical Conditioning

David S. Touretzky, Geoffrey J. Gordon, Aaron C. Courville, 2003, NIPS.

Anytime Dynamic A*: An Anytime, Replanning Algorithm

Sebastian Thrun, Geoffrey J. Gordon, Anthony Stentz, 2005, ICAPS.

Auction Mechanism Design for Multi-Robot Coordination

Sebastian Thrun, Geoffrey J. Gordon, Curt A. Bererton, 2003, NIPS.

Learning from Experience in Manipulation Planning: Setting the Right Goals

Siddhartha S. Srinivasa, Anca D. Dragan, Geoffrey J. Gordon, 2011, ISRR.

Decentralized Sensor Fusion with Distributed Particle Filters

Sebastian Thrun, Geoffrey J. Gordon, Matthew Rosencrantz, 2002, UAI.

Reinforcement Learning with Function Approximation Converges to a Region

Geoffrey J. Gordon, 2000, NIPS.

Locating moving entities in indoor environments with teams of mobile robots

Sebastian Thrun, Geoffrey J. Gordon, Matthew Rosencrantz, 2003, AAMAS '03.

Supervised Learning for Controlled Dynamical System Learning

Geoffrey J. Gordon, Ahmed Hefny, Carlton Downey, 2017 .

The support vector decomposition machine

Geoffrey J. Gordon, Francisco Pereira, Francisco Pereira, 2006, ICML.

Fast and Improved SLEX Analysis of High-Dimensional Time Series

Sanjeev Khanna, Geoffrey J. Gordon, Robert E. Kass, 2014, MLINI@NIPS.

An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems

Byron Boots, Geoffrey J. Gordon, Byron Boots, 2011, AAAI.

Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation

Yuan Tian, Geoffrey J. Gordon, Jianfeng Chi, 2020, NeurIPS.

Stable Function Approximation in Dynamic Programming

Geoffrey J. Gordon, 1995, ICML.

Nonparametric Statistical Methods for Experimental Evaluations of Speedup Learning

Geoffrey J. Gordon, Alberto Maria Segre, 1996, International Conference on Machine Learning.

A Game-Theoretic Approach to Modeling Cross-Cultural Negotiation

Miroslav Dudík, Geoffrey J. Gordon, Miroslav Dudík, 2013 .

ARA : formal analysis

Geoffrey J. Gordon, Maxim Likhachev, Thrun, 2003 .

Fast Exact Planning in Markov Decision Processes

Geoffrey J. Gordon, H. Brendan McMahan, H. B. McMahan, 2005, ICAPS.

Real-time fault diagnosis [robot fault diagnosis]

Sebastian Thrun, Reid G. Simmons, Geoffrey J. Gordon, 2004, IEEE Robotics & Automation Magazine.

A Generalization of SAT and #SAT for Robust Policy Evaluation

André Platzer, Geoffrey J. Gordon, Erik Zawadzki, 2013, IJCAI.

Adversarial Task-Specific Privacy Preservation under Attribute Attack pdf

Han Zhao, Yuan Tian, Geoffrey J. Gordon, 2019, ArXiv.

A Spectral Learning Approach to Range-Only SLAM

Byron Boots, Geoffrey J. Gordon, Byron Boots, 2012, ICML.

No-regret Algorithms for Online Convex Programs

Geoffrey J. Gordon, 2006, NIPS.

Identifying Culture and Leveraging Cultural Differences for Negotiation Agents

Miroslav Dudík, Katia P. Sycara, Geoffrey J. Gordon, 2012, 2012 45th Hawaii International Conference on System Sciences.

Generalized² Linear² Models

Geoffrey J. Gordon, 2003, NIPS 2003.

Adversarial Privacy Preservation under Attribute Inference Attack

Yuan Tian, Geoffrey J. Gordon, Jianfeng Chi, 2019 .

Principled Hybrids of Generative and Discriminative Domain Adaptation pdf

Han Zhao, Geoffrey J. Gordon, Adam Coates, 2017, ArXiv.

Reduced-Rank Hidden Markov Models pdf

Byron Boots, Geoffrey J. Gordon, Sajid M. Siddiqi, 2009, AISTATS.

First-Order Mixed Integer Linear Programming pdf

Miroslav Dudík, Geoffrey J. Gordon, Sue Ann Hong, 2009, UAI.

Learning Beam Search Policies via Imitation Learning

Geoffrey J. Gordon, Matthew R. Gormley, Renato Negrinho, 2018, NeurIPS.

Practical Learning of Predictive State Representations pdf

Geoffrey J. Gordon, Ahmed Hefny, Carlton Downey, 2017, ArXiv.

An Instantiation-Based Theorem Prover for First-Order Programming

André Platzer, Geoffrey J. Gordon, Erik Zawadzki, 2011, AISTATS.

Planning in the Presence of Cost Functions Controlled by an Adversary

Avrim Blum, Geoffrey J. Gordon, H. Brendan McMahan, 2003, ICML.

Recurrent Predictive State Policy Networks pdf

Siddhartha S. Srinivasa, Zita Marinho, Geoffrey J. Gordon, 2018, ICML.

Policy-contingent abstraction for robust robot control

Joelle Pineau, Sebastian Thrun, Geoffrey J. Gordon, 2002, UAI.

Approximate Kalman Filters for Embedding Author-Word Co-occurrence Data over Time

Purnamrita Sarkar, Geoffrey J. Gordon, Sajid M. Siddiqi, 2006, SNA@ICML.

Online Spectral Identification of Dynamical Systems

Byron Boots, Geoffrey J. Gordon, 2011 .

Tractable planning under uncertainty: exploiting structure

Joelle Pineau, Sebastian Thrun, Geoffrey J. Gordon, 2004 .

Collapsed Variational Inference for Sum-Product Networks

Han Zhao, Geoffrey J. Gordon, Brandon Amos, 2016, ICML.

Relational learning via collective matrix factorization

Geoffrey J. Gordon, Ajit Paul Singh, A. P. Singh, 2008, KDD.

Decentralized planning under uncertainty for teams of communicating agents

Nikos A. Vlassis, Geoffrey J. Gordon, Matthijs T. J. Spaan, 2006, AAMAS '06.

A Data-Driven Approach for Inferring Student Proficiency from Game Activity Logs

Kristen E. DiCerbo, Geoffrey J. Gordon, Mohammad Hassan Falakmasir, 2016, L@S.

Sholom M. Weiss and Casimir A. Kulikowski, Computer Systems That Learn

Geoffrey J. Gordon, Alberto Maria Segre, 1993, Artificial Intelligence.

An Empirical Investigation of Beam-Aware Training in Supertagging pdf

Geoffrey J. Gordon, Matthew R. Gormley, Renato Negrinho, 2020, EMNLP.

Inherent Tradeoffs in Learning Fair Representation pdf

Han Zhao, Geoffrey J. Gordon, Han Zhao, 2019, NeurIPS.

Instructional Factors Analysis: A Cognitive Model For Multiple Instructional Interventions

Kurt VanLehn, Kenneth R. Koedinger, Pamela W. Jordan, 2011, EDM.

Hilbert Space Embeddings of Predictive State Representations pdf

Byron Boots, Arthur Gretton, Geoffrey J. Gordon, 2013, UAI.

Query-based Workload Forecasting for Self-Driving Database Management Systems

Lin Ma, Geoffrey J. Gordon, Andrew Pavlo, 2018, SIGMOD Conference.

A Latent Space Approach to Dynamic Embedding of Co-occurrence Data

Purnamrita Sarkar, Geoffrey J. Gordon, Sajid M. Siddiqi, 2007, AISTATS.

Strategy Transfer Learning via Parametric Deviation Sets

Kevin Waugh, Geoffrey J. Gordon, Katia Sycara, 2011 .

Learning latent variable and predictive models of dynamical systems

Geoffrey J. Gordon, Sajid M. Siddiqi, S. Siddiqi, 2009 .

Frank-Wolfe Optimization for Symmetric-NMF under Simplicial Constraint pdf

Han Zhao, Geoffrey J. Gordon, 2018, UAI.

Fundamental Limits and Tradeoffs in Invariant Representation Learning pdf

Tommi S. Jaakkola, Geoffrey J. Gordon, Chen Dan, 2020, ArXiv.

Planning for Markov Decision Processes with Sparse Stochasticity

Sebastian Thrun, Geoffrey J. Gordon, Maxim Likhachev, 2004, NIPS.

No-regret learning in convex games

Geoffrey J. Gordon, Amy Greenwald, Casey Marks, 2008, ICML '08.

A Unified View of Matrix Factorization Models

Geoffrey J. Gordon, Ajit Paul Singh, A. P. Singh, 2008, ECML/PKDD.

Stable Fitted Reinforcement Learning

Geoffrey J. Gordon, 1995, NIPS.

Approximate solutions for partially observable stochastic games with common payoffs

Jeff G. Schneider, Geoffrey J. Gordon, Sebastian Thrun, 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

Hilbert Space Embeddings of Hidden Markov Models

Le Song, Byron Boots, Alexander J. Smola, 2010, ICML.

DeepArchitect: Automatically Designing and Training Deep Architectures pdf

Geoffrey J. Gordon, Renato Negrinho, Renato Negrinho, 2017, ArXiv.

No-Regret Reductions for Imitation Learning and Structured Prediction pdf

Geoffrey J. Gordon, J. Andrew Bagnell, Stéphane Ross, 2010, ArXiv.

Automatic Database Management System Tuning Through Large-scale Machine Learning

Geoffrey J. Gordon, Andrew Pavlo, Bohan Zhang, 2017, SIGMOD Conference.

Learning Stable Multivariate Baseline Models for Outbreak Detection

Byron Boots, Geoffrey J. Gordon, Artur Dubrawski, 2007 .

Conditional Learning of Fair Representations pdf

Han Zhao, Geoffrey J. Gordon, Tameem Adel, 2019, ICLR.

A Bayesian Matrix Factorization Model for Relational Data pdf

Geoffrey J. Gordon, Ajit Paul Singh, A. P. Singh, 2010, UAI.

Unsupervised Learning for Nonlinear PieceWise Smooth Hybrid Systems pdf

Siddhartha S. Srinivasa, Zita Marinho, Aaron M. Johnson, 2017, ArXiv.

An Accelerated Gradient Method for Distributed Multi-Agent Planning with Factored MDPs

Geoffrey J. Gordon, Sue Ann Hong, 2011 .

A Fast Bundle-based Anytime Algorithm for Poker and other Convex Games

Geoffrey J. Gordon, H. Brendan McMahan, H. B. McMahan, 2007, AISTATS.

POMDP Planning for Robust Robot Control

Joelle Pineau, Geoffrey J. Gordon, Joelle Pineau, 2005, ISRR.

Decentralized estimation and control of graph connectivity in mobile sensor networks

Siddhartha S. Srinivasa, Randy A. Freeman, Kevin M. Lynch, 2008, ACC.

Optimal Distributed Market-Based Planning for Multi-Agent Systems with Shared Resources

Geoffrey J. Gordon, Sue Ann Hong, 2011, AISTATS.

Closing the learning-planning loop with predictive state representations

Byron Boots, Geoffrey J. Gordon, Sajid M. Siddiqi, 2011, Int. J. Robotics Res..

Fast Solutions to Projective Monotone Linear Complementarity Problems pdf

Geoffrey J. Gordon, 2012, ArXiv.

Exploratory Analysis of Speedup Learning Data Using Epectation Maximization

Charles Elkan, Geoffrey J. Gordon, Alberto Maria Segre, 1996, Artif. Intell..

Generalized2 Linear2 Models

Geoffrey J. Gordon, 2002, NIPS.

A Demonstration of the OtterTune Automatic Database Management System Tuning Service

Tao Dai, Geoffrey J. Gordon, Andrew Pavlo, 2018, Proc. VLDB Endow..

Two Manifold Problems with Applications to Nonlinear System Identification pdf

Byron Boots, Geoffrey J. Gordon, Byron Boots, 2012, ICML.

RADAR: A Personal Assistant that Learns to Reduce Email Overload

Michael Freed, Stephen F. Smith, Jaime G. Carbonell, 2008, AAAI.

Linear Time Computation of Moments in Sum-Product Networks

Han Zhao, Geoffrey J. Gordon, 2017, NIPS.

A Unification of Extensive-Form Games and Markov Decision Processes

Geoffrey J. Gordon, H. Brendan McMahan, H. B. McMahan, 2007, AAAI.

Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns

Robert F. Murphy, Geoffrey J. Gordon, Shann-Ching Chen, 2008, J. Mach. Learn. Res..

Predictive State Recurrent Neural Networks

Byron Boots, Geoffrey J. Gordon, Ahmed Hefny, 2017, NIPS.

Dual Policy Iteration

Byron Boots, Geoffrey J. Gordon, J. Andrew Bagnell, 2018, NeurIPS.

A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning

Geoffrey J. Gordon, J. Andrew Bagnell, Stéphane Ross, 2010, AISTATS.

Lagrangian Relaxation for Large-Scale Multi-agent Planning

Hoong Chuin Lau, Shih-Fen Cheng, Geoffrey J. Gordon, 2012, 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

Multiple Source Domain Adaptation with Adversarial Learning

José M. F. Moura, Han Zhao, Geoffrey J. Gordon, 2018, ICLR.

Transdisciplinary Collaboration in Developing Robotic Assistive Technology for Older Adults

Sebastian Thrun, Judith T. Matthews, Geoffrey J. Gordon, 2011 .

A Spectral Learning Approach to Knowledge Tracing

Zachary A. Pardos, Peter Brusilovsky, Geoffrey J. Gordon, 2013, EDM.

Tuning the Molecular Weight Distribution from Atom Transfer Radical Polymerization Using Deep Reinforcement Learning

Geoffrey J. Gordon, Tomasz Kowalewski, Haichen Li, 2017, 1712.04516.

A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data

Sebastian Thrun, Frank Pfenning, Geoffrey J. Gordon, 2003, IJCAI.

Anytime search in dynamic graphs

Sebastian Thrun, Geoffrey J. Gordon, Anthony Stentz, 2008, Artif. Intell..

Decomposition-Based Optimal Market-Based Planning for Multi-Agent Systems with Shared Resources

Geoffrey J. Gordon, Sue Ann Hong, 2011 .

An Empirical Study of Example Forgetting during Deep Neural Network Learning pdf

Yoshua Bengio, Geoffrey J. Gordon, Adam Trischler, 2018, ICLR.

The Block Diagonal Infinite Hidden Markov Model

Tai Sing Lee, Zoubin Ghahramani, Geoffrey J. Gordon, 2009, AISTATS.

Decentralized estimation and control of graph connectivity in mobile sensor networks

Siddhartha S. Srinivasa, Randy A. Freeman, Kevin M. Lynch, 2008, 2008 American Control Conference.

Planning under uncertainty in robotics

Joelle Pineau, Nikos A. Vlassis, Geoffrey J. Gordon, 2006, Robotics Auton. Syst..

Agendas for multi-agent learning

Geoffrey J. Gordon, 2007, Artif. Intell..

Statistical Modeling of Student Performance to Improve Chinese Dictation Skills with an Intelligent Tutor

Geoffrey J. Gordon, Yanhui Zhang, John Kowalski, 2014, EDM 2014.

Multiple Source Domain Adaptation with Adversarial Training of Neural Networks pdf

José M. F. Moura, Han Zhao, Geoffrey J. Gordon, 2017, ArXiv.

Adversarial Multiple Source Domain Adaptation

José M. F. Moura, Han Zhao, Geoffrey J. Gordon, 2018, NeurIPS.

Exploring friend's influence in cultures in Twitter

Katia P. Sycara, Geoffrey J. Gordon, Ahmed Hefny, 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).

Learning Hidden Quantum Markov Models

Byron Boots, Geoffrey J. Gordon, Siddarth Srinivasan, 2017, AISTATS.

Decomposed Mutual Information Estimation for Contrastive Representation Learning pdf

Philip Bachman, Geoffrey J. Gordon, Hannes Schulz, 2021, ICML.

Understanding and Mitigating Accuracy Disparity in Regression pdf

Yuan Tian, Geoffrey J. Gordon, Jianfeng Chi, 2021, ICML.

Successor Feature Sets: Generalizing Successor Representations Across Policies

Geoffrey J. Gordon, Kiant'e Brantley, Soroush Mehri, 2021, AAAI.

Approximate solutions to markov decision processes

Geoffrey J. Gordon, Tom Michael Mitchell, 1999 .

Finding Approximate POMDP solutions Through Belief Compression

Geoffrey J. Gordon, S. Thrun, N. Roy, 2011, J. Artif. Intell. Res..

Generalized^2 Linear^2 Models

Geoffrey J. Gordon, 2002, NIPS 2002.

Predicting Structure in Handwritten Algebra Data From Low Level Features

Geoffrey J. Gordon, James Duyck, 2015 .

Point-based approximations for fast POMDP solving

Geoffrey J. Gordon, S. Thrun, Joelle Pineau, 2006 .

Robust planning in domains with stochastic outcomes, adversaries, and partial observability

Geoffrey J. Gordon, H. B. McMahan, A. Blum, 2006 .

Generalizing Dijkstra's Algorithm and Gaussian Elimination for Solving MDPs

Geoffrey J. Gordon, H. B. McMahan, 2005 .

Deep Generative and Discriminative Domain Adaptation

Geoffrey J. Gordon, A. Coates, Zhenyao Zhu, 2019, AAMAS.

Generalization Bound for Multiple Source Domain Adaptation

José M. F. Moura, Geoffrey J. Gordon, H. Zhao, 2018 .

Constant size descriptors for accurate machine learning models of molecular properties.

Geoffrey J. Gordon, Christopher R. Collins, O. A. von Lilienfeld, 2018, The Journal of chemical physics.

A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians.

Geoffrey J. Gordon, Haichen Li, Christopher R. Collins, 2018, Journal of chemical theory and computation.

Multi-robot coordination and competition using mixed integer and linear programs

Geoffrey J. Gordon, Curt A. Bererton, P. Khosla, 2004 .

Depth without distress

Geoffrey J. Gordon, Shiva Kaul, 2017 .

Fast Exact Planning in Markov Decision Processes DRAFT — please check for updates before redistributing

Geoffrey J. Gordon, H. B. McMahan, 2022 .

Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation

Geoffrey J. Gordon, Han Zhao, Jianfeng Chi, 2019, NeurIPS.

On Automatic Database Management SystemTuning Using Machine Learning

Michael J. Cafarella, Geoffrey J. Gordon, Dana Van Aken, 2020 .

Graph Adversarial Networks: Protecting Information against Adversarial Attacks

Geoffrey J. Gordon, R. Salakhutdinov, T. Jaakkola, 2020, ArXiv.

A Bayesian Matrix Model for Relational Data

Geoffrey J. Gordon, A. P. Singh, 2009 .

DURING DEEP NEURAL NETWORK LEARNING

Geoffrey J. Gordon, Alessandro Sordoni, Mariya Toneva, 2019 .

Random Walks with Random Projections

Geoffrey J. Gordon, 2009 .

Effective Multi-Model Tracking Using Team Actuation Models

Geoffrey J. Gordon, M. Hebert, B. Browning, 2005 .

Approximate Empirical Bayes for Deep Neural Networks

Geoffrey J. Gordon, Yao-Hung Hubert Tsai, R. Salakhutdinov, 2018 .

Fundamental Limits and Tradeoffs in Invariant Representation Learning pdf

Pradeep Ravikumar, Tommi S. Jaakkola, Chen Dan, 2020, ArXiv.

Constant Size Molecular Descriptors For Use With Machine Learning

Geoffrey J. Gordon, David J. Yaron, O. Anatole von Lilienfeld, 2017 .

Learning From the Experience of Others: Approximate Empirical Bayes in Neural Networks

Han Zhao, Ruslan Salakhutdinov, Geoffrey J. Gordon, 2018 .

Fast Algorithms for Proximity Search on Large Graphs Purnamrita

Geoffrey J. Gordon, A. Moore, Anupam Gupta, 2008 .

Embedding parameters in ab initio theory to develop well-controlled approximations based on molecular similarity

Geoffrey J. Gordon, D. Yaron, Matteus Tanha, 2013, 1311.3440.

Polynomials for directed graphs

Geoffrey J. Gordon, L. Traldi, 1994 .

Fundamental Limits and Tradeoffs in Invariant Representation Learning

Geoffrey J. Gordon, T. Jaakkola, Pradeep Ravikumar, 2020, J. Mach. Learn. Res..

Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces pdf

Byron Boots, Zita Marinho, Geoffrey J. Gordon, 2016, Robotics: Science and Systems.

Towards modular and programmable architecture search

Darshan Patil, Geoffrey J. Gordon, Daniel C. Ferreira, 2019, NeurIPS.

Spectral Learning for Expressive Interactive Ensemble Music Performance

Roger B. Dannenberg, Geoffrey J. Gordon, Yun Wang, 2015, ISMIR.

Learning General Latent-Variable Graphical Models with Predictive Belief Propagation and Hilbert Space Embeddings

Geoffrey J. Gordon, Geoffrey Gordon, Borui Wang, 2017, AAAI.

Policy-contingent state abstraction for hierarchical MDPs

Geoffrey J. Gordon, Joelle Pineau, 2002 .

Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift pdf

Geoffrey J. Gordon, Geoff Gordon, Remi Tachet des Combes, 2020, NeurIPS.

Conditional Learning of Fair Representations

Geoffrey J. Gordon, Han Zhao, T. Adel, 2019, ICLR.

Inherent Tradeoffs in Learning Fair Representations

Geoffrey J. Gordon, Han Zhao, 2019, NeurIPS.

Efficient Multitask Feature and Relationship Learning

Han Zhao, Geoffrey J. Gordon, Geoff Gordon, 2017, UAI.

Information Obfuscation of Graph Neural Networks

Geoffrey J. Gordon, R. Salakhutdinov, T. Jaakkola, 2020, ICML.

Bayesian Methods for Identifying Faults on Robots for Planetary Exploration

Geoffrey J. Gordon, V. Verma, 2007 .

Expressiveness and Learning of Hidden Quantum Markov Models pdf

Byron Boots, Geoffrey J. Gordon, Geoff Gordon, 2019, AISTATS.

A Reduction from Reinforcement Learning to No-Regret Online Learning

Geoffrey J. Gordon, Byron Boots, Ching-An Cheng, 2019, AISTATS.

Multiple Source Domain Adaptation with Adversarial Training of Neural Networks

José M. F. Moura, Geoffrey J. Gordon, H. Zhao, 2017, ArXiv.

Learning General Latent-Variable Graphical Models with Predictive Belief Propagation

Geoffrey J. Gordon, Borui Wang, 2017, AAAI.

Conditional Learning of Fair Representations

Geoffrey J. Gordon, Han Zhao, T. Adel, 2019, ICLR.

Artificial intelligence in medicine

Geoffrey J. Gordon, Tom Michael Mitchell, P J Drew, 1989, Singapore medical journal.

Artificial Intelligence in Medicine: 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26–29, 2019, Proceedings

Geoffrey J. Gordon, Johanna D. Moore, Tom Michael Mitchell, 2019, Lecture Notes in Computer Science.

Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift

Geoffrey J. Gordon, Yu-Xiang Wang, Han Zhao, 2020, NeurIPS.

Artificial intelligence in medicine

Diana E. Forsythe, Bruce G. Buchanan, Geoffrey J. Gordon, 1989, Springer US.

Recurrent Predictive State Policy Networks

Geoffrey J. Gordon, S. Srinivasa, Ahmed S. Hefny, 2018, ICML.

A New View of Predictive State Methods for Dynamical System Learning

Geoffrey J. Gordon, Ahmed S. Hefny, Carlton Downey, 2015, ArXiv.