irina rish dwtcusibmcom call papers value information inference learning decisionmaking wwwresearchibmcomnips05workshop workshop held 19th annual conference neural information processing systems nips 2005 whistler canada december 10 2005 overview goals common fundamental problem value information voi analysis arises inference learning sequential decisionmaking one allowed actively select rather passively observe input information voi provides principled methodology enables acquiring information way optimally trades cost information gathering expected benefit overall objective eg classification accuracy cumulative reward example bayesian problem diagnosis voi analysis aims selecting observations eg medical tests informative unknown variables eg diseases trying diagnose minimizing cost collecting information sequential decisionmaking problems voi provide principled solution wellknown exploration versus exploitation dilemma one optimally trade immediate cost exploratory actions expected improvement future decisions future reward yet another example active learning goal minimize cost observations eg number labeled samples maximizing learners objective function finally selecting relevant subset features supervised learning another example voi analysis provide principled solution clearly areas differ choices particular objective function approaches active exploration common goal selecting explorative actions maximize voi workshop plan bring together researchers several fields concerned voi analysis hope ignite crossfertilization areas could lead major theoretical progress well practical impact applications medical diagnosis quality control product design systems management troubleshooting dna library screening name suggested topics list possible topics includes limited following voi analysis probabilistic inference decision theory feature selection attributeefficient learning active learning query learning selective sampling explorationexploitation tradeoff reinforcement learning adaptive versus nonadaptive testing designs comparison different action selection criteria objective functions applications voi diagnosis systems control management coding theory computational biology neural coding etc format oneday workshop following 19th annual conference neural information processing systems nips 2005 several invited talks tutorials roughly 3040 minutes shorter contributed talks researchers industry academia well panel discussion hold poster session receive sufficient number good submissions workshop intended accessible broader nips community encourage communication different fields submission instructions invite submissions extended abstracts 2 pages including bibliography short contributed talks andor posters submission present highlevel description recent ongoing work related topics explore possibility publishing papers based invited submitted talks special issue appropriate journal email submissions qtut74bnrdjhxlwatsonibmcom attachments postscript pdf later october 24 2005 information workshop url wwwresearchibmcomnips05workshop submission qtut74bnrdjhxlwatsonibmcom nips httpwwwnipscc dates deadlines october 24 abstract submission october 31 acceptance notification organizing committee dr alina beygelzimer ibm j watson research lab usa dr rajarshi das ibm j watson research lab usa dr irina rish primary contact ibm j watson research lab usa dr gerry tesauro ibm j watson research lab usa invited speakers prof craig boutilier university toronto prof sanjoy dasgupta university california san diego prof carlos guestrin carnegie mellon university prof michael littman rutgers university prof dale schuurmans university alberta irina rish ibm tj watson research center 19 skyline drive hawthorne ny 10532 tel 9147847431 fax 9147846040 wwwresearchibmcompeoplerrish wed 06 aug 2008 140736 0400 uai cfp nips05 workshop value information inference learning decisionmaking