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07/17/2023
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study
Coping with distributional shifts is an important part of transfer learn...
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06/26/2023
Multivariate Time Series Early Classification Across Channel and Time Dimensions
Nowadays, the deployment of deep learning models on edge devices for add...
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01/25/2023
Modelling Long Range Dependencies in N-D: From Task-Specific to a General Purpose CNN
Performant Convolutional Neural Network (CNN) architectures must be tail...
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12/13/2022
Improving generalization in reinforcement learning through forked agents
An eco-system of agents each having their own policy with some, but limi...
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10/31/2022
Disentangled (Un)Controllable Features
In the context of MDPs with high-dimensional states, reinforcement learn...
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10/14/2022
An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions
In current research, machine and deep learning solutions for the classif...
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06/07/2022
Towards a General Purpose CNN for Long Range Dependencies in ND
The use of Convolutional Neural Networks (CNNs) is widespread in Deep Le...
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04/13/2022
Improving generalization to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents
Adapting a Reinforcement Learning (RL) agent to an unseen environment is...
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04/04/2022
Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS
Nowadays, with the rising number of sensors in sectors such as healthcar...
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03/24/2022
The Dutch Draw: Constructing a Universal Baseline for Binary Prediction Models
Novel prediction methods should always be compared to a baseline to know...
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02/10/2022
Transfer-Learning Across Datasets with Different Input Dimensions: An Algorithm and Analysis for the Linear Regression Case
With the development of new sensors and monitoring devices, more sources...
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10/15/2021
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes
When designing Convolutional Neural Networks (CNNs), one must select the...
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08/13/2021
Jasmine: A New Active Learning Approach to Combat Cybercrime
Over the past decade, the advent of cybercrime has accelarated the resea...
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07/22/2021
A Framework for Imbalanced Time-series Forecasting
Time-series forecasting plays an important role in many domains. Boosted...
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03/29/2021
pH-RL: A personalization architecture to bring reinforcement learning to health practice
While reinforcement learning (RL) has proven to be the approach of choic...
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02/04/2021
CKConv: Continuous Kernel Convolution For Sequential Data
Conventional neural architectures for sequential data present important ...
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11/03/2020
Mixing Consistent Deep Clustering
Finding well-defined clusters in data represents a fundamental challenge...
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06/09/2020
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms
Inducing symmetry equivariance in deep neural architectures has resolved...
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02/07/2020
Attentive Group Equivariant Convolutional Networks
Although group convolutional networks are able to learn powerful represe...
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01/10/2020
Trace Clustering on Very Large Event Data in Healthcare Using Frequent Sequence Patterns
Trace clustering has increasingly been applied to find homogenous proces...
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11/18/2019
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data
Equivariance is a nice property to have as it produces much more paramet...
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08/01/2019
Reinforcement Learning for Personalized Dialogue Management
Language systems have been of great interest to the research community a...
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04/11/2019
GP-HD: Using Genetic Programming to Generate Dynamical Systems Models for Health Care
The huge wealth of data in the health domain can be exploited to create ...
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04/03/2019
Identifying Patient Groups based on Frequent Patterns of Patient Samples
Grouping patients meaningfully can give insights about the different typ...
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04/10/2018