Concept

Transfer learning

Related publications (71)

Leveraging over prior knowledge for online learning of visual categories

Barbara Caputo, Tatiana Tommasi, Mohsen Kaboli

Open ended learning is a dynamic process based on the continuous analysis of new data, guided by past experience. On one side it is helpful to take advantage of prior knowledge when only few information on a new task is available (transfer learning). On th ...

2012

Improving Object Classification using Pose Information

François Fleuret, Hugo Augusto Penedones Fernandes, Ronan Collobert, David Grangier

We propose a method that exploits pose information in order to improve object classification. A lot of research has focused in other strategies, such as engineering feature extractors, trying different classifiers and even using transfer learning. Here, we ...

Idiap2012

Transfer Learning of Visual Concepts across Robots: a Discriminative Approach

Barbara Caputo, Tatiana Tommasi

While there is a general consensus that autonomous robots should be able to learn continuously over time, the learning process is traditionally envisioned for each specific robot situated in a given environment. This does not consider the fact that robots ...

Idiap2012

Improving Articulatory Feature and Phoneme Recognition using Multitask Learning

Ramya Rasipuram

Speech sounds can be characterized by articulatory features. Articulatory features are typically estimated using a set of multilayer perceptrons (MLPs), i.e., a separate MLP is trained for each articulatory feature. In this paper, we investigate multitask ...

Springer Berlin / Heidelberg2011

MULTITASK LEARNING TO IMPROVE ARTICULATORY FEATURE ESTIMATION AND PHONEME RECOGNITION

Ramya Rasipuram

Idiap2011

Multiple task learning in recurrent neural networks using layered reservoirs

Martin Hasler, Ali Ajdari Rad, Mahdi Jalili

In this paper, to learn multiple tasks sharing same inputs, a two-layer architecture for a reservoir based recurrent neural network is proposed. The inputs are fed into the general workspace layer where the weights are adapted to provide maximum informatio ...

2009

Semi-supervised Adapted HMMs for Unusual Event Detection

Daniel Gatica-Perez, Samy Bengio, Dong Zhang

We address the problem of temporal unusual event detection. Unusual events are characterized by a number of features (rarity, unexpectedness, and relevance) that limit the application of traditional supervised model-based approaches. We propose a semi-supe ...

2005

Semi-supervised Adapted HMMs for Unusual Event Detection

Daniel Gatica-Perez, Samy Bengio, Dong Zhang

IDIAP2004

An Evolutionary Active-Vision System

Dario Floreano

We describe an evolutionary vision system capable of autonomously scanning through an image while zooming in and out and changing filtering strategy in order to perform shape discrimination. The system consists of a small artificial retina controlled by an ...

2001

Signal recognition by synchronization of chaotic systems

Martin Hasler

It is shown that the synchronization of two coupled tent maps can be used for a practical signal classification task. Hebbian learning is used to set the coupling coefficients for correct classification. For the problem with real data considered, it is sur ...

1997

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