← Authors

Geoffrey J. Gordon

28 papers · 2006–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (19) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (5) πŸ† Keyword Champion 🀝 Dynamic Duo (12) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (8) πŸ’Ž Century Club (28) πŸ—ƒοΈ Keyword Collector (121) ❓ The Questioner πŸ“ˆ Trend Setter

Conferences

NIPS (15) ICML (5) ICLR (3) JMLR (3) RSS (1) UAI (1)

Top co-authors

Han Zhao (12) Byron Boots (6) Carlton Downey (2) Ahmed Hefny (2) Renato Negrinho (2) Stephanie Milani (2) Ruslan Salakhutdinov (2) Wen Sun (2) Jianfeng Chi (2) Matthew Gormley (2)

Research topics

Reinforcement Learning (1)

Keywords

domain adaptation (3) information theory (2) policy learning (2) predictive state representation (2) neural network (2) imitation learning (2) dynamical system (2) system identification (2) representation learning (2) sum-product network (2) convex optimization (2) reinforcement learning (2) domain generalization (2) privacy-preserving learning (2) adversarial learning (2) structured prediction (1) bayesian inference (1) feature learning (1) game theory (1) multi-task learning (1)

Papers

CurvGAD: Leveraging Curvature for Enhanced Graph Anomaly Detection ICML 2025
LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning ICLR 2025
When is Transfer Learning Possible? ICML 2024
Inherent Tradeoffs in Learning Fair Representations JMLR 2022
Fundamental Limits and Tradeoffs in Invariant Representation Learning JMLR 2022
Understanding and Mitigating Accuracy Disparity in Regression ICML 2021
Information Obfuscation of Graph Neural Networks ICML 2021
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift NIPS 2020
Conditional Learning of Fair Representations ICLR 2020
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation NIPS 2020
Efficient Multitask Feature and Relationship Learning UAI 2019
Learning Neural Networks with Adaptive Regularization NIPS 2019
Towards modular and programmable architecture search NIPS 2019
An Empirical Study of Example Forgetting during Deep Neural Network Learning ICLR 2019
Adversarial Multiple Source Domain Adaptation NIPS 2018
Dual Policy Iteration NIPS 2018
Learning Beam Search Policies via Imitation Learning NIPS 2018
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction ICML 2017
Linear Time Computation of Moments in Sum-Product Networks NIPS 2017
Predictive State Recurrent Neural Networks NIPS 2017
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces RSS 2016
A Unified Approach for Learning the Parameters of Sum-Product Networks NIPS 2016
Supervised Learning for Dynamical System Learning NIPS 2015
Predictive State Temporal Difference Learning NIPS 2010
Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns JMLR 2008
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems NIPS 2007
No-regret Algorithms for Online Convex Programs NIPS 2006
Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games NIPS 2006