# Geoffrey J. Gordon

Associate research professor

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I spent AY 2003-4 as a visiting professor at the Stanford Robotics Lab. Before joining CMU I used to work for Burning Glass Technologies, a company that provided intelligent searching and matching software for resumes and job postings. The company was headquartered in San Diego, but I worked at their Pittsburgh office.

Before that, I was a postdoctoral researcher at the AUTON lab in the Robotics Institute. Before that, I was a Computer Science PhD student, with advisor Tom Mitchell.

## Papers191 papers

Conditional Learning of Fair Representations

Learning General Latent-Variable Graphical Models with Predictive Belief Propagation

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

On Learning Invariant Representation for Domain Adaptation.

Deep Generative and Discriminative Domain Adaptation

Inherent Tradeoffs in Learning Fair Representation.

Inherent Tradeoffs in Learning Fair Representations.

Principled Hybrids of Generative and Discriminative Domain Adaptation.

Learning Hidden Quantum Markov Models.

Recurrent Predictive State Policy Networks.

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

A Demonstration of the OtterTune Automatic Database Management System Tuning Service.

Learning Beam Search Policies via Imitation Learning.

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

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

Adversarial Multiple Source Domain Adaptation.

DeepArchitect: Automatically Designing and Training Deep Architectures.

Multiple Source Domain Adaptation with Adversarial Learning

Frank-Wolfe Optimization for Symmetric-NMF under Simplicial Constraint

Efficient Computation of Moments in Sum-Product Networks.

Efficient Multi-task Feature and Relationship Learning.

Multiple Source Domain Adaptation with Adversarial Training of Neural Networks.

Automatic Database Management System Tuning Through Large-scale Machine Learning.

Predictive State Recurrent Neural Networks.

Linear Time Computation of Moments in Sum-Product Networks.

Unsupervised Learning for Nonlinear PieceWise Smooth Hybrid Systems.

Constant Size Molecular Descriptors For Use With Machine Learning

**4**|Bibtex

Practical Learning of Predictive State Representations.

Predictive State Recurrent Neural Networks

Linear Time Computation of Moments in Sum-Product Networks

Efficient Multitask Feature and Relationship Learning.

Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces

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

Collapsed Variational Inference for Sum-Product Networks.

Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces

Supervised Learning for Dynamical System Learning

Spectral Learning for Expressive Interactive Ensemble Music Performance.

Hybrid Theorem Proving of Aerospace Systems: Applications and Challenges.

Fast and Improved SLEX Analysis of High-dimensional Time Series

A Generalization of SAT and #SAT for Robust Policy Evaluation (CMU-CS-13-107)

**1**|Bibtex

Individualized Bayesian Knowledge Tracing Models.

Exploring friend's influence in cultures in Twitter

A Spectral Learning Approach to Range-Only SLAM

A generalization of SAT and #SAT for robust policy evaluation

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

**1**|Bibtex

Spectral approaches to learning predictive representations

**17**|EI|Bibtex

Two-Manifold Problems with Applications to Nonlinear System Identification

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

An Instantiation-Based Theorem Prover for First-Order Programming.

No-Regret Reductions for Imitation Learning and Structured Prediction

Closing the learning-planning loop with predictive state representations

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

Transdisciplinary Collaboration in Developing Robotic Assistive Technology for Older Adults

Closing the learning-planning loop with predictive state representations

Automatic state discovery for unstructured audio scene classification

A Bayesian Matrix Factorization Model for Relational Data.

Predictive State Temporal Difference Learning

Reduced-Rank Hidden Markov Models

Hilbert Space Embeddings of Hidden Markov Models

Predictive State Temporal Difference Learning

**44**|Bibtex

Closing the Learning-Planning Loop with Predictive State Representations

First-order mixed integer linear programming

A sampling-based approach to computing equilibria in succinct extensive-form games