Why do Random Forests Work? Understanding Tree Ensembles as Self-Regularizing Adaptive Smoothers

no code implementations • 2 Feb 2024 • Alicia Curth, Alan Jeffares, Mihaela van der Schaar

Despite their remarkable effectiveness and broad application, the drivers of success underlying ensembles of trees are still not fully understood.

TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization

2 code implementations • 9 Mar 2023 • Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie, Mihaela van der Schaar

In this work, we introduce Tabular Neural Gradient Orthogonalization and Specialization (TANGOS), a novel framework for regularization in the tabular setting built on latent unit attributions.

Improving Adaptive Conformal Prediction Using Self-Supervised Learning

2 code implementations • 23 Feb 2023 • Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar

However, the use of self-supervision beyond model pretraining and representation learning has been largely unexplored.

Conformal Prediction Prediction Intervals +4

Spike-inspired Rank Coding for Fast and Accurate Recurrent Neural Networks

1 code implementation • ICLR 2022 • Alan Jeffares, Qinghai Guo, Pontus Stenetorp, Timoleon Moraitis

We demonstrate these in two toy problems of sequence classification, and in a temporally-encoded MNIST dataset where our RC model achieves 99. 19% accuracy after the first input time-step, outperforming the state of the art in temporal coding with SNNs, as well as in spoken-word classification of Google Speech Commands, outperforming non-RC-trained early inference with LSTMs.