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<bibitem type="C">   <ARLID>0410437</ARLID> <utime>20240103182214.0</utime><mtime>20060210235959.9</mtime>        <title language="eng" primary="1">Recent results regarding composition of distributions</title>  <publisher> <place>Rome</place> <name>Baltzer Science Publ.</name> <pub_time>2000</pub_time> </publisher> <specification> <page_count>4 s.</page_count> </specification>   <serial><title>Partial Knowledge and Uncertainty: Independence, Conditioning, Inference</title><part_num/><part_title/><page_num>9-12</page_num><editor><name1>Scozzafava</name1><name2>R.</name2></editor><editor><name1>Vantaggi</name1><name2>B.</name2></editor></serial>   <author primary="1"> <ARLID>cav_un_auth*0101118</ARLID> <name1>Jiroušek</name1> <name2>Radim</name2> <institution>UTIA-B</institution> <full_dept>Department of Decision Making Theory</full_dept>  <fullinstit>Ústav teorie informace a automatizace AV ČR, v. v. i.</fullinstit> </author>     <COSATI>12A</COSATI>    <cas_special> <project> <project_id>GA201/98/1487</project_id> <agency>GA ČR</agency> <ARLID>cav_un_auth*0005923</ARLID> </project> <research> <research_id>AV0Z1075907</research_id> </research>  <abstract language="eng" primary="1">The paper deals with recent results achieved in connection with an alternative apparatus to describe multidimensional probabilistic models which, in contrast to Graphical Markov Models, define distributions in a constructive way. The approach is based on the idea that multidimensional distributions can be constructed from low-dimensional ones by special operaors of composition.</abstract>  <action target=""> <ARLID>cav_un_auth*0212700</ARLID> <name>Workshop on Partial Knowledge and Uncertainty: Independence, Conditioning, Inference.</name> <place>Rome</place> <country>IT</country> <dates>04.05.2000-06.05.2000</dates> </action>     <RIV>BA</RIV>   <department>MTR</department>    <permalink>http://hdl.handle.net/11104/0130526</permalink>   <ID_orig>UTIA-B 20000153</ID_orig>     <arlyear>2000</arlyear>       <unknown tag="mrcbU10"> 2000 </unknown> <unknown tag="mrcbU10"> Rome Baltzer Science Publ. </unknown> <unknown tag="mrcbU63"> Partial Knowledge and Uncertainty: Independence, Conditioning, Inference 9 12 </unknown> <unknown tag="mrcbU67"> Scozzafava R. 340 </unknown> <unknown tag="mrcbU67"> Vantaggi B. 340 </unknown> </cas_special> </bibitem>