Optimistic bounds for multi-output learning

no code implementations • ICML 2020 • Henry Reeve, Ata Kaban

We investigate the challenge of multi-output learning, where the goal is to learn a vector-valued function based on a supervised data set.

General Classification Multi-class Classification +2

A Unified Theory of Diversity in Ensemble Learning

1 code implementation • 10 Jan 2023 • Danny Wood, Tingting Mu, Andrew Webb, Henry Reeve, Mikel Luján, Gavin Brown

We present a theory of ensemble diversity, explaining the nature of diversity for a wide range of supervised learning scenarios.

Ensemble Learning Open-Ended Question Answering

Margin Maximization as Lossless Maximal Compression

1 code implementation • 28 Jan 2020 • Nikolaos Nikolaou, Henry Reeve, Gavin Brown

The ultimate goal of a supervised learning algorithm is to produce models constructed on the training data that can generalize well to new examples.

General Classification

To Ensemble or Not Ensemble: When does End-To-End Training Fail?

1 code implementation • 12 Feb 2019 • Andrew M. Webb, Charles Reynolds, Wenlin Chen, Henry Reeve, Dan-Andrei Iliescu, Mikel Lujan, Gavin Brown

An interesting question is whether this trend will continue-are there any clear failure cases for E2E training?