Training deep networks and tuning hyperparameters on large datasets is
c...
Efficient model selection for identifying a suitable pre-trained neural
...
In complex tasks where the reward function is not straightforward and
co...
Knowledge transfer from a complex high performing model to a simpler and...
Many automated machine learning methods, such as those for hyperparamete...
There is a rich and growing literature on producing local point wise
con...
Data science is labor-intensive and human experts are scarce but heavily...
Recently, a method [7] was proposed to generate contrastive explanations...
The growing interest in both the automation of machine learning and deep...
The recent advent of automated neural network architecture search led to...
Application of neural networks to a vast variety of practical applicatio...
Recent work shows unequal performance of commercial face classification
...
Electroencephalography (EEG) is an extensively-used and well-studied
tec...
Current tools for exploratory data analysis (EDA) require users to manua...
Current tools for exploratory data analysis (EDA) require users to manua...