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05/26/2023
Three Towers: Flexible Contrastive Learning with Pretrained Image Models
We introduce Three Towers (3T), a flexible method to improve the contras...
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04/12/2023
SmartChoices: Augmenting Software with Learned Implementations
We are living in a golden age of machine learning. Powerful models are b...
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02/18/2022
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information
Supervised learning datasets often have privileged information, in the f...
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05/19/2021
Correlated Input-Dependent Label Noise in Large-Scale Image Classification
Large scale image classification datasets often contain noisy labels. We...
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09/09/2020
Routing Networks with Co-training for Continual Learning
The core challenge with continual learning is catastrophic forgetting, t...
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03/15/2020
Analysis of Softmax Approximation for Deep Classifiers under Input-Dependent Label Noise
Modelling uncertainty arising from input-dependent label noise is an inc...
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11/26/2019
Ranking architectures using meta-learning
Neural architecture search has recently attracted lots of research effor...
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10/10/2019
Gumbel-Matrix Routing for Flexible Multi-task Learning
This paper proposes a novel per-task routing method for multi-task appli...
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03/17/2019
General techniques for approximate incidences and their application to the camera posing problem
We consider the classical camera pose estimation problem that arises in ...
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02/15/2019
