Optimization lies at the heart of many machine learning algorithms and enjoys great interest in our community. Indeed, this intimate relation of optimization with ML is the key motivation for the OPT series of workshops. We aim to foster discussion, discovery, and dissemination of the state-of-the-art in optimization relevant to ML.

This year, as the seventh in its series, the workshop's special topic will be the challenges in non-convex optimization, with contributions spanning both the challenges (hardness results) and the opportunities (modeling flexibility) of non-convex optimization. Irrespective of the special topic, the workshop will again warmly welcome contributed talks and posters on all topics in optimization for machine learning.

The confirmed invited speakers for this year are:

* Amir Beck (Technion, Israel)
* Jean Bernard Lasserre (CNRS, France)
* Yoshua Bengio (University of Montreal, Canada)