Search Results for author: Magda Gregorova

Found 6 papers, 2 papers with code

Permutation Equivariant Generative Adversarial Networks for Graphs

no code implementations7 Dec 2021 Yoann Boget, Magda Gregorova, Alexandros Kalousis

One solution consists of using equivariant generative functions, which ensure the ordering invariance.

Sparse Learning for Variable Selection with Structures and Nonlinearities

no code implementations26 Mar 2019 Magda Gregorova

In this thesis we discuss machine learning methods performing automated variable selection for learning sparse predictive models.

Sparse Learning Variable Selection

Continual Classification Learning Using Generative Models

no code implementations24 Oct 2018 Frantzeska Lavda, Jason Ramapuram, Magda Gregorova, Alexandros Kalousis

Continual learning is the ability to sequentially learn over time by accommodating knowledge while retaining previously learned experiences.

Classification Continual Learning +1

Lifelong Generative Modeling

1 code implementation ICLR 2018 Jason Ramapuram, Magda Gregorova, Alexandros Kalousis

Lifelong learning is the problem of learning multiple consecutive tasks in a sequential manner, where knowledge gained from previous tasks is retained and used to aid future learning over the lifetime of the learner.

Transfer Learning

Learning Leading Indicators for Time Series Predictions

no code implementations7 Jul 2015 Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet

We consider the problem of learning models for forecasting multiple time-series systems together with discovering the leading indicators that serve as good predictors for the system.

Time Series

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