International Workshop on
January 11th 2021, in conjunction with the
International Conference on Pattern Recognition (ICPR'20)
Anticipating patterns has become a crucial activity in the last years, due to the combined availability of huge amount of data, techniques for exploiting noisy information, transferring knowledge across domains, and the need of forecasting services within many heterogeneous domains, from computer science to environmental sciences, from economics to robotics and from bioinformatics to social sciences and humanities. A growing spectrum of applications in self-driving cars, weather forecasting, financial market prediction, real-time epidemic forecasting, and social network modeling needs to be explored within a same venue. This first workshop aims therefore to identify commonalities, gather lessons learnt across domains, discuss modern and most successful techniques, and foster the exchange of new ideas, which may extend to other novel fields too.
The International Workshop on Pattern Forecasting addresses the general problem of forecasting patterns. This is not just limited to a specific domain, but rather intended as cross-fertilization of different disciplines. By doing so, it seeks to highlight possible general-purpose approaches which may be applied to a large span of data types, promoting and motivating further studies in specific directions. As an example, techniques for predicting the diffusion of epidemics are currently adopted to forecasting activities within social networks. We are convinced that many other hybridations are ready to be explored.
The workshop seeks contributions from researchers and practitioners from different domains, to share current best algorithms and practices, to foster discussion among diverse communities and to define common grounds for joint progress, within the general artificial intelligence and pattern recognition.
4 April 2020. Web-page is up.