In many modern problems and, in particular, in those arising in machine learning, the amount of data is too large to apply standard optimisation algorithms. EU-funded scientists developed new algorithms that rely on a fraction of the input data to reduce the running time.
Internet traffic logs and financial transactions are just two examples of massive data sets that appear more and more often in various applications. Analysing and managing such data sets force scientists to reconsider the conventional approaches to developing efficient optimisation algorithms.
Further details: Optimising optimisation algorithms