Search Results for author: Gerald Woo

Found 5 papers, 5 papers with code

DeepTIMe: Deep Time-Index Meta-Learning for Non-Stationary Time-Series Forecasting

1 code implementation13 Jul 2022 Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

Yet, despite the attractive properties of time-index based models, such as being a continuous signal function over time leading to smooth representations, little attention has been given to them.

Meta-Learning Time Series Forecasting

CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting

1 code implementation ICLR 2022 Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi

Motivated by the recent success of representation learning in computer vision and natural language processing, we argue that a more promising paradigm for time series forecasting, is to first learn disentangled feature representations, followed by a simple regression fine-tuning step -- we justify such a paradigm from a causal perspective.

Contrastive Learning Representation Learning +1

Model Agnostic Defence against Backdoor Attacks in Machine Learning

2 code implementations6 Aug 2019 Sakshi Udeshi, Shanshan Peng, Gerald Woo, Lionell Loh, Louth Rawshan, Sudipta Chattopadhyay

In this work, we present NEO, a model agnostic framework to detect and mitigate such backdoor attacks in image classification ML models.

BIG-bench Machine Learning Decision Making +3

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