In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
The task of estimating causal effects from non-experimental data is notoriously difficult and unreliable. Nevertheless, precisely such estimates are commonly required in many fiel...
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen...
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Model-driven engineering (MDE) techniques address rapid changes anguages and platforms by lifting the abstraction level from code to models. On the one hand models are transformed ...
Abstract. To handle signal processing algorithms such as the Fast Fourrier Transform (FFT) or the Discrete Cosine Transform (DCT) system designers have traditionally resorted to sp...