{"62240":{"#nid":"62240","#data":{"type":"event","title":"Monitoring a Large Number of Data Streams via Thresholding","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE:\u003C\/strong\u003E Monitoring a Large Number of Data Streams via Thresholding\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER: \u003C\/strong\u003EYajun Mei\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn the modern information age one often monitors a large number of data \nstreams with the aim of offering the potential for early detection of a \n\u0022trigger\u0022 event. In this talk, we are interested in detecting the event as \nsoon as possible, but we do not know when the event will occur, nor do we \nknow which subset of data streams will be affected by the event. Motivated \nby the applications in censoring sensor networks and by the case when one \nhas a prior knowledge that at most r data streams will be affected, we \npropose scalable global monitoring schemes based on the sum of the local \ndetection statistics that are \u0022large\u0022 under either hard thresholding or \ntop-r thresholding rules or both. The proposed schemes are shown to \npossess certain asymptotic optimality properties.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Monitoring a Large Number of Data Streams via Thresholding"}],"uid":"27187","created_gmt":"2010-10-19 09:53:37","changed_gmt":"2016-10-08 01:53:16","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2010-10-21T12:00:00-04:00","event_time_end":"2010-10-21T13:00:00-04:00","event_time_end_last":"2010-10-21T13:00:00-04:00","gmt_time_start":"2010-10-21 16:00:00","gmt_time_end":"2010-10-21 17:00:00","gmt_time_end_last":"2010-10-21 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}