In this ACML 2013 workshop we intend to discuss what makes a
theory relevant for practical development of algorithms and how the gap
between theory and practice can be decreased. Several different forms
of theoretical foundations
for machine learning have been developed over the years for different
settings. Conversely, there has been a recent and dramatic uptake in the
application of machine learning techniques to an increasingly diverse
range of problems. Arguably, some of the most
successful algorithms on practical problems are not completely
understood theoretically. We are interested in contributions relating to
understanding or closing this gap, both specific technical contributions and general well-argued positions. |