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Università della Svizzera italiana

Hard and soft EM in bayesian network learning from incomplete data

Ruggieri, Andrea ; Stranieri, Francesco ; Stella, Fabio ; Scutari, Marco

In: Algorithms, 2020, vol. 13, no. 12, p. 17

Incomplete data are a common feature in many domains, from clinical trials to industrial applications. Bayesian networks (BNs) are often used in these domains because of their graphical and causal interpretations. BN parameter learning from incomplete data is usually implemented with the Expectation-Maximisation algorithm (EM), which computes the relevant sufficient statistics (“soft EM”) ...

Université de Fribourg

Joint knowledge production in climate change adaptation networks

Muccione, Veruska ; Huggel, Christian ; Bresch, David N ; Jurt, Christine ; Wallimann-Helmer, Ivo ; Mehra, Meeta K ; Pabón Caicedo, José Daniel

In: Current Opinion in Environmental Sustainability, 2019, vol. 39, p. 147–152

Adaptation to changing and new environmental conditions is of fundamental importance to sustainability and requires concerted efforts amongst science, policy, and practice to produce solution-oriented knowledge. Joint knowledge production or co-production of knowledge have become increasingly popular terms to describe the process of scientists, policy makers and actors from the civil society...

Université de Fribourg

On the sustainability of photochemical reactions

Bochet, Christian G.

In: CHIMIA International Journal for Chemistry, 2019, vol. 73, no. 9, p. 720–723

Photochemical reactions are often presented as intrinsically environmentally friendly ('green'). This may be indeed the case, but only in particular circumstances. This short essay comments on various aspects of the greenness of photochemical reactions, both in a historical (when only mercury-based hard UV light sources were available) and a current (with the recent introduction of LED...

Université de Fribourg

Editorial - Erosion of the Middle Class?

Budowski, Monica ; Schief, Sebastian

In: sozialpolitik.ch, 2019, vol. 1, no. 1, p. Article: 1.1