{"49034":{"#nid":"49034","#data":{"type":"event","title":"Directed Regression","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE:\u003C\/strong\u003E Directed Regression\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER:\u003C\/strong\u003E Professor Ben Van Roy\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWhen used to guide decisions, linear regression analysis typically\u0026nbsp; \ninvolves estimation of regression coefficients via ordinary least\u0026nbsp; \nsquares and their subsequent use in an optimization problem. When\u0026nbsp; \nfeatures are not chosen perfectly, it can be beneficial to account for\u0026nbsp; \nthe decision objective when computing regression coefficients.\u0026nbsp; \nEmpirical optimization does so but sacrifices performance when\u0026nbsp; \nfeatures are well-chosen or training data are insufficient. We propose\u0026nbsp; \ndirected regression, an efficient algorithm that combines merits of\u0026nbsp; \nordinary least squares and empirical optimization. We demonstrate\u0026nbsp; \nthrough computational studies that directed regression generates\u0026nbsp; \nperformance gains over either alternative. We also develop a theory\u0026nbsp; \nthat motivates the algorithm.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"Directed Regression","format":"limited_html"}],"field_summary_sentence":[{"value":"Directed Regression"}],"uid":"27187","created_gmt":"2010-01-20 14:05:31","changed_gmt":"2016-10-08 01:49:32","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2010-02-09T10:00:00-05:00","event_time_end":"2010-02-09T11:00:00-05:00","event_time_end_last":"2010-02-09T11:00:00-05:00","gmt_time_start":"2010-02-09 15:00:00","gmt_time_end":"2010-02-09 16:00:00","gmt_time_end_last":"2010-02-09 16:00:00","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":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}