Government
Fine-tuning language models to find agreement among humans with diverse preferences
Further, our best model's consensus statements are preferred
Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution
Better generalisation reduces the need for extensive and costly screens at single-cell resolution.
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in Neuroimaging
Examples include M/EEG inverse problems, neural encoding models for task-based fMRI analyses, and climate science.
A Theoretical Analysis
In this section, we provide detailed theoretical analysis and proofs in linear MDPs [23]. A.1 LSVI Solution In linear MDPs, we assume that the transition dynamics and reward function take the form of P Theorem (Theorem 1 restate) . In experiments, we do not use explicit constraints (e.g., Spectral regularization) for the upper bound Corollary (Corollary 1 restate) . I given in Corollary 1. To conclude, we obtain from Eq. (22) that |T V First, we give the following lemma.
The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers
We revisit the problem of supervised classification using quadratic features of the data. We do so to highlight the influence of properties of data distrbution on the generalization error.