1 code implementation • 22 Oct 2023 • Mike Huisman, Thomas M. Moerland, Aske Plaat, Jan N. van Rijn
Meta-learning overcomes this limitation by learning how to learn.
1 code implementation • 13 Oct 2023 • Mike Huisman, Aske Plaat, Jan N. van Rijn
Gradient-based meta-learning techniques aim to distill useful prior knowledge from a set of training tasks such that new tasks can be learned more efficiently with gradient descent.
1 code implementation • 9 Oct 2023 • Mike Huisman, Aske Plaat, Jan N. van Rijn
Whilst meta-learning techniques have been observed to be successful at this in various scenarios, recent results suggest that when evaluated on tasks from a different data distribution than the one used for training, a baseline that simply finetunes a pre-trained network may be more effective than more complicated meta-learning techniques such as MAML, which is one of the most popular meta-learning techniques.
3 code implementations • NeurIPS 2022 • Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera, Isabelle Guyon, Mike Huisman, Felix Mohr, Jan N van Rijn, Haozhe Sun, Joaquin Vanschoren, Phan Anh Vu
We introduce Meta-Album, an image classification meta-dataset designed to facilitate few-shot learning, transfer learning, meta-learning, among other tasks.
no code implementations • 15 Jun 2022 • Adrian El Baz, Ihsan Ullah, Edesio Alcobaça, André C. P. L. F. Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Chaoyu Guan, Isabelle Guyon, Timothy Hospedales, Shell Hu, Mike Huisman, Frank Hutter, Zhengying Liu, Felix Mohr, Ekrem Öztürk, Jan N. van Rijn, Haozhe Sun, Xin Wang, Wenwu Zhu
Although deep neural networks are capable of achieving performance superior to humans on various tasks, they are notorious for requiring large amounts of data and computing resources, restricting their success to domains where such resources are available.
1 code implementation • 21 Apr 2021 • Mike Huisman, Aske Plaat, Jan N. van Rijn
Deep learning typically requires large data sets and much compute power for each new problem that is learned.
no code implementations • 7 Oct 2020 • Mike Huisman, Jan N. van Rijn, Aske Plaat
Meta-learning is one approach to address this issue, by enabling the network to learn how to learn.