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Alex J. Chan
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2020 – today
- 2024
- [c10]Lorenzo Pacchiardi, Alex James Chan, Sören Mindermann, Ilan Moscovitz, Alexa Y. Pan, Yarin Gal, Owain Evans, Jan Markus Brauner:
How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions. ICLR 2024 - [c9]Alex James Chan, Hao Sun, Samuel Holt, Mihaela van der Schaar:
Dense Reward for Free in Reinforcement Learning from Human Feedback. ICML 2024 - [i13]Alex J. Chan, Hao Sun, Samuel Holt, Mihaela van der Schaar:
Dense Reward for Free in Reinforcement Learning from Human Feedback. CoRR abs/2402.00782 (2024) - [i12]Chris Lu, Samuel Holt, Claudio Fanconi, Alex J. Chan, Jakob N. Foerster, Mihaela van der Schaar, Robert Tjarko Lange:
Discovering Preference Optimization Algorithms with and for Large Language Models. CoRR abs/2406.08414 (2024) - 2023
- [c8]Jeroen Berrevoets, Daniel Jarrett, Alex J. Chan, Mihaela van der Schaar:
AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems. NeurIPS 2023 - [i11]Lorenzo Pacchiardi, Alex J. Chan, Sören Mindermann, Ilan Moscovitz, Alexa Y. Pan, Yarin Gal, Owain Evans, Jan Brauner:
How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions. CoRR abs/2309.15840 (2023) - [i10]Alex J. Chan, Alihan Hüyük, Mihaela van der Schaar:
Optimising Human-AI Collaboration by Learning Convincing Explanations. CoRR abs/2311.07426 (2023) - [i9]Hao Sun, Alex J. Chan, Nabeel Seedat, Alihan Hüyük, Mihaela van der Schaar:
When is Off-Policy Evaluation Useful? A Data-Centric Perspective. CoRR abs/2311.14110 (2023) - [i8]Alex J. Chan, José Luis Redondo García, Fabrizio Silvestri, Colm O'Donnel, Konstantina Palla:
Harmonizing Global Voices: Culturally-Aware Models for Enhanced Content Moderation. CoRR abs/2312.02401 (2023) - 2022
- [c7]Alex J. Chan, Alicia Curth, Mihaela van der Schaar:
Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies. ICLR 2022 - [c6]Alizée Pace, Alex J. Chan, Mihaela van der Schaar:
POETREE: Interpretable Policy Learning with Adaptive Decision Trees. ICLR 2022 - [c5]Alex J. Chan, Mihaela van der Schaar:
Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning. NeurIPS 2022 - [i7]Alex J. Chan, Alicia Curth, Mihaela van der Schaar:
Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies. CoRR abs/2203.07338 (2022) - [i6]Alizée Pace, Alex J. Chan, Mihaela van der Schaar:
POETREE: Interpretable Policy Learning with Adaptive Decision Trees. CoRR abs/2203.08057 (2022) - [i5]Alex J. Chan, Mihaela van der Schaar:
Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning. CoRR abs/2210.05320 (2022) - [i4]Tennison Liu, Alex J. Chan, Boris van Breugel, Mihaela van der Schaar:
Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes. CoRR abs/2211.06138 (2022) - 2021
- [c4]Ahmed M. Alaa, Alex James Chan, Mihaela van der Schaar:
Generative Time-series Modeling with Fourier Flows. ICLR 2021 - [c3]Alex James Chan, Mihaela van der Schaar:
Scalable Bayesian Inverse Reinforcement Learning. ICLR 2021 - [c2]Alex J. Chan, Ioana Bica, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar:
The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation. NeurIPS Datasets and Benchmarks 2021 - [i3]Alex J. Chan, Mihaela van der Schaar:
Scalable Bayesian Inverse Reinforcement Learning. CoRR abs/2102.06483 (2021) - [i2]Alex J. Chan, Ioana Bica, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar:
The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation. CoRR abs/2106.04240 (2021) - 2020
- [c1]Alex J. Chan, Ahmed M. Alaa, Zhaozhi Qian, Mihaela van der Schaar:
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift. ICML 2020: 1392-1402 - [i1]Alex J. Chan, Ahmed M. Alaa, Zhaozhi Qian, Mihaela van der Schaar:
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift. CoRR abs/2006.14988 (2020)
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