Alex J. Chan

According to our database1, Alex J. Chan authored at least 14 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Awards

IEEE Fellow

IEEE Fellow 1992, "For contributions to the advancement of electric drives and electric vehicles.".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Dense Reward for Free in Reinforcement Learning from Human Feedback.
CoRR, 2024

2023
Harmonizing Global Voices: Culturally-Aware Models for Enhanced Content Moderation.
CoRR, 2023

When is Off-Policy Evaluation Useful? A Data-Centric Perspective.
CoRR, 2023

Optimising Human-AI Collaboration by Learning Convincing Explanations.
CoRR, 2023

How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions.
CoRR, 2023

AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes.
CoRR, 2022

Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

POETREE: Interpretable Policy Learning with Adaptive Decision Trees.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Scalable Bayesian Inverse Reinforcement Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Generative Time-series Modeling with Fourier Flows.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift.
Proceedings of the 37th International Conference on Machine Learning, 2020


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