Data efficiency
Numerous applications of Machine Learning in business intelligence, process optimization, product development or sales do not benefit from true “big data”. Blind application of state-of-the-art methods can lead to catastrophic failure. Proper data acquisition and modelling are key to successful applications.

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Resolving Training Biases via Influence-based Data Relabeling

Influence functions are used to correct corrupt labels in a dataset that would significantly decrease a trained model’s performance. …

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Data Efficiency
Seminar

An introduction to Unsupervised Neural Machine Translation

Lack of large parallel corpora or dictionaries for most language pairs and modern data-hungry models make the need for unsupervised …

Sebastian Wagner
Data Efficiency
Seminar

Dealing with imbalanced classes

In this talk Wolfgang shares some of his personal experience and methods while training classifier CNNs on image datasets with highly …

Wolfgang Reuter
Data Efficiency
Seminar

Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning

Paper abstract: Model-free deep reinforcement learning algorithms have been shown to be capable of learning a wide range of robotic skills, …

Fabian Hainzl
Data Efficiency
Efficient RL
Seminar

A short introduction to model-based Reinforcement Learning

Model-based RL learns a deterministic or probabilistic forward model of the dynamics of an environment for action planning or direct policy …

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Data Efficiency
Efficient RL
Seminar

An introduction to data distillation

Distillation ensembles predictions from multiple transformations of unlabeled data, using a single model, to automatically generate new …

Ishmeet Kaur
Data Efficiency

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Data valuation

Attributions of value to training samples can be used to examine data, improve data acquisition, debug and improve models or compensate …

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Representation Learning

Representation learning is concerned with finding semantically useful and compact, i.e., low dimensional, representations for inputs from …

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Efficient RL

Recent and popular advances in Reinforcement Learning are known to be data-hungry. Attempts to handle this deficit include developing …

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