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Found 5 papers, 1 papers with code
West-of-N: Synthetic Preference Generation for Improved Reward Modeling
The success of reinforcement learning from human feedback (RLHF) in language model alignment is strongly dependent on the quality of the underlying reward model.
On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series
Recent findings in deep learning for tabular data are now surpassing these classical methods by better handling the severe heterogeneity of data input features.
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
A prominent challenge of offline reinforcement learning (RL) is the issue of hidden confounding: unobserved variables may influence both the actions taken by the agent and the observed outcomes.
Temporal Label Smoothing for Early Event Prediction
TLS reduces the number of missed events by up to a factor of two over previously used approaches in early event prediction.
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POETREE: Interpretable Policy Learning with Adaptive Decision Trees
Building models of human decision-making from observed behaviour is critical to better understand, diagnose and support real-world policies such as clinical care.
