BEGIN:VCALENDAR PRODID:-//Microsoft Corporation//Outlook 16.0 MIMEDIR//EN VERSION:2.0 METHOD:REQUEST X-MS-OLK-FORCEINSPECTOROPEN:TRUE BEGIN:VTIMEZONE TZID:W. Europe Standard Time BEGIN:STANDARD DTSTART:16011028T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:16010325T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT ATTENDEE;CN="Nehal Soni";RSVP=TRUE:mailto:nehal.soni@stud.th-owl.de CLASS:PUBLIC CREATED:20211218T151511Z DESCRIPTION:Topic: Validate on Sim\, Detect on Real -- Model Selection for Domain\nRandomization\n \nhttps://arxiv.org/abs/2111.00765\n \n\n \nAbstra ct: Domain randomization (DR) is the popular technique to train\nthe polic y on a diverse set of randomly generated domains with the hope\nof better generalization and closing Sim2Real gap. Due to a large number\nof hyper-p arameters in both the policy learning and DR algorithms\, one\noften ends up with a large number of trained models\, here choosing the\nbest model a mong them demands costly evaluation in the real environment.\nIn this work Authors ask – can we rank the policies without running them\nin the rea l world? Out-of-distribution (testing distribution being\nunknown and diff erent from training) detection techniques can be\ninaccurate and very sens itive to the particular method used. With the\nnovel Validate on Sim\, Det ect on Real (VSDR) score\, the accuracy of\npolicy ranking is significantl y improved without requiring additional\nreal-world data. The effectivenes s of VSDR on sim2real transfer is\nevaluated in a robotic grasping task wi th image inputs.\n \n-- Den nachstehenden Text weder löschen noch ändern . -- \n \nTreten Sie Ihrem Webex-Meeting zum gegebenen Zeitpunkt hier bei. \n \n \nMeeting beitreten\n \n \nWeitere Methoden zum Beitreten: \n \nÜber den Meeting-Link beitreten \nhttps://th-owl.webex.com/th-owl/j.ph p?MTID=md5287d814c2a73253d5592954ed\n233c0\n \n \n \nMit Meeting-Ke nnnummer beitreten \nMeeting-Kennnummer (Zugriffscode): 2731 424 5357\nMee ting-Passwort: BcX63D4tprn \n \nHier tippen\, um mit Mobilgerät beizutre ten (nur für Teilnehmer) \n+49-619-6781-9736\,\,27314245357##\n Germany Toll \n+49-619-678 1-9736\,\,27314245357##\n Germany Toll \n\nÜber Telefon beitreten \n+49-619-6781-9736 Germ any Toll \n+49-619-6781-9736 Germany Toll \nGlobale Einwahlnummern\n \n \nMit Videosystem\, Anwendung oder Skype for Business teilnehmen\nWählen Sie 27314245357@webex.com \nSie können auch 62.109.219.4 wählen und Ihre Meeting-Nummer eingeben . \n \nWenn Sie ein Gastgeber sind\, klicken Sie hier\n \, um Gastge berinformationen anzuzeigen.\n \n \nBrauchen Sie Hilfe? Gehen Sie zu https ://help.webex.com\n \n \n \n \n DTEND;TZID="W. Europe Standard Time":20220111T173000 DTSTAMP:20211218T151408Z DTSTART;TZID="W. Europe Standard Time":20220111T160000 LAST-MODIFIED:20211218T151511Z LOCATION:https://th-owl.webex.com/th-owl/j.php?MTID=md5287d814c2a73253d5592 954ed233c0 ORGANIZER;CN="Markus Lange-Hegermann":mailto:markus.lange-hegermann@th-owl. de PRIORITY:5 SEQUENCE:1 SUMMARY;LANGUAGE=en-us:MLRG: Validate on Sim\, Detect on Real -- Model Sele ction for Domain Randomization TRANSP:OPAQUE UID:040000008200E00074C5B7101A82E0080000000010CFCD5B29F4D701000000000000000 010000000CF9549C91C9C1945B9FB5166F0983E33 X-ALT-DESC;FMTTYPE=text/html: < !--[if gte mso 10]>

Topic: \;Validate on Sim\, D etect on Real -- Model Selection for Domain Randomization

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https://arxiv.org/abs/2111.00765

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Abstract: < /span>Domain randomizatio n (DR) is the popular technique to train the policy on a diverse set of ra ndomly generated domains with the hope of better generalization and closin g Sim2Real gap. Due to a large number of hyper-parameters in both the poli cy learning and DR algorithms\, one often ends up with a large number of t rained models\, here choosing the best model among them demands costly eva luation in the real environment. In this work Authors ask –\; can we rank the policies without running them in the real world? Out-of-distribut ion (testing distribution being unknown and different from training) detec tion techniques can be inaccurate and very sensitive to the particular met hod used. With the novel Validate on Sim\, Detect on Real (VSDR) sc ore\, the accuracy of policy ranking is significantly improved without req uiring additional real-world data. The effectiveness of VSDR on sim2real t ransfer is evaluated in a robotic grasping task with image inputs.

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-- Den nachstehenden Text weder lö\;schen noch ä\;ndern. --

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Treten Sie Ihrem Webex-Meeting zum gegebenen Zeitpunkt hier bei.

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Meeting beitreten

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Weitere Methoden zum Beitreten:

< /td>

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Ü\;ber den Mee ting-Link beitreten

https://th-owl.webex.com/th-owl/j. php?MTID=md5287d814c2a73253d5592954ed233c0 < /span>

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Hie r tippen\, um mit Mobilgerä\;t beizutreten (nur fü\;r Teilnehmer)< /span> \ ;
+49-619-6781-9736\,\,27314245357## \;Germa ny Toll&n bsp\;
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Ü\;ber Telefon beitreten \; < br>+49-619-6781-9736 \;Germany Toll \;
< /span>+49-619-6781-9736 \;Germany Toll \;
Gl obale Einwahlnummern \;
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Mit Videosystem\, Anwendung oder Skype for Business teilnehmen
Wä\;hlen Sie< span style='mso-bookmark:WBX9F173'>
27314245357@webex.com \; < br>Sie kö\;nnen auch 62.109.219.4 wä\;hlen und Ihre Meeting-Nummer eingeben.

Mit Meeting-Kennnummer beitreten

Me eting-Kennnummer (Zugriffscode): 2731 424 5357

Meeting-Passwort: B cX63D4tprn \;

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& nbsp\;

Wenn Sie ein Gastgeber sind\, klicken Sie hier\, um Gastgeberinformationen anzuzeigen.

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