15 citations · 29 across the 5 of their papers we have counts for
5 papers
Integrated Weak Learning
Peter Hayes, Mingtian Zhang, Raza Habib +3
We introduce Integrated Weak Learning, a principled framework that integrates weak supervision into the training process of machine learning models. Our approach jointly trains the…
Sample Efficient Model Evaluation
Emine Yilmaz, Peter Hayes, Raza Habib +2
Labelling data is a major practical bottleneck in training and testing classifiers. Given a collection of unlabelled data points, we address how to select which subset to label to…
Semi-Supervised Generative Modeling for Controllable Speech Synthesis
Raza Habib, Soroosh Mariooryad, Matt Shannon +5
We present a novel generative model that combines state-of-the-art neural text-to-speech (TTS) with semi-supervised probabilistic latent variable models. By providing partial super…
Variational f-divergence Minimization
Mingtian Zhang, Thomas Bird, Raza Habib +2
Probabilistic models are often trained by maximum likelihood, which corresponds to minimizing a specific f-divergence between the model and data distribution. In light of recent su…
Spread Divergence
Mingtian Zhang, Peter Hayes, Tom Bird +2
For distributions and with different supports or undefined densities, the divergence may not exist. We define a Sprea…