Balance & Integration Programme

Balance & Integration (B&I) is a watchdog and advisory programme that monitors the overall activity of the Network and attempts to ensure that :

• the various thematic programmes maintain an appropriate balance of activity between theory, algorithms and application-oriented research, and across different subject areas and input modalities ;
• Network resources are used in a way that will promote the overall goals of integrating theoretical and applied research on machine learning, statistical pattern recognition and multimodal interfaces.

B&I's main activities are thus consulting with other programmes, monitoring their activities, reflecting on the overall progress of the Network, and if necessary, intervening to correct any imbalances that seem to be arising.

At present, our main concerns are :

• To strengthen the Network's cognitive modelling activities, and in particular, the links between these and machine learning and statistical modelling research.
• To provide more tutorial and outreach material suitable for introducing outsiders and students to machine learning, statistical modelling and application domain techniques.
• To encourage the participation of female researchers in PASCAL2-related research areas.

Whenever possible, B&I functions by consultation and advice rather than direct intervention, but it does have a small discretionary budget that can be used to fund corrective actions when necessary. This funding can be allocated via targeted open calls of other thematic programmes as well as by direct B&I calls. Subject to budget being available, specific B&I related requests can also be made at any time.