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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal>=====================================================<o:p></o:p></p><p class=MsoNormal>NIPS 2015 Workshop: Multimodal Machine Learning<o:p></o:p></p><p class=MsoNormal>Montreal, Quebec, Canada<o:p></o:p></p><p class=MsoNormal><a href="https://sites.google.com/site/multiml2015/">https://sites.google.com/site/multiml2015/</a><o:p></o:p></p><p class=MsoNormal>=====================================================<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>IMPORTANT DATES<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l0 level1 lfo1'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Submission Deadline: October 9th, 2015<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l0 level1 lfo1'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Author Notification: October 24th, 2015 <o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l0 level1 lfo1'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Workshop: December 11, 2015<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>KEYNOTE SPEAKERS<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l0 level1 lfo1'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Shih-Fu Chang (Columbia University)<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l0 level1 lfo1'><![if !supportLists]><span lang=FR-CA style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=FR-CA>Li Deng (Microsoft Research)<o:p></o:p></span></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l0 level1 lfo1'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Raymond Mooney (University of Texas, Austin)<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l0 level1 lfo1'><![if !supportLists]><span lang=FR-CA style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=FR-CA>Ruslan Salakhutdinov (Carnegie Mellon University)<o:p></o:p></span></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>OVERVIEW<o:p></o:p></p><p class=MsoNormal>Multimodal machine learning aims at building models that can process and relate information from multiple modalities. From the early research on audio-visual speech recognition to the recent explosion of interest in models mapping images to natural language, multimodal machine learning is a vibrant multi-disciplinary field of increasing importance and with extraordinary potential. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Learning from paired multimodal sources offers the possibility of capturing correspondences between modalities and gain in-depth understanding of natural phenomena. Thus, multimodal data provides a means of reducing our dependence on the more standard supervised learning paradigm that is inherently limited by the availability of labeled examples.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>This research field brings some unique challenges for machine learning researchers given the heterogeneity of the data and the complementarity often found between modalities. This workshop will facilitate the progress in multimodal machine learning by bringing together researchers from natural language processing, multimedia, computer vision, speech processing and machine learning to discuss the current challenges and identify the research infrastructure needed to enable a stronger multidisciplinary collaboration.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>TOPICS<o:p></o:p></p><p class=MsoNormal>We are looking for contributed papers that apply machine learning to multimodal data. We are interested in both application-oriented papers as well as more fundamental algorithmic / theoretical works.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>A non-exhaustive list of relevant topics:<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Automatic image and video description<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Multimodal signal processing<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Audio-visual speech recognition<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Multimodal affect recognition<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Cross-modal multimedia retrieval<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Multi-view multi-task learning<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Multimodal representation learning<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Multi-sensory computational modeling<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Multilingual, multimodal language processing<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Multimodal modeling for robotics control<o:p></o:p></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l1 level1 lfo2'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>Multimodal human behavior modeling<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>SUBMISSIONS<o:p></o:p></p><p class=MsoNormal>Authors should submit an extended abstract between 4 and 6 pages (including references). We particularly encourage submissions that have been previously published outside the machine learning community (i.e. at NIPS and ICML) to emphasize the multidisciplinary aspect of this research area. We also encourage submission of relevant work in progress. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Submitted abstracts may be a shortened version of a longer paper or technical report, in which case the longer paper should be referred from the submission. Reviewers will be asked to judge the submission solely based on the submitted extended abstract. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>All submissions must be in PDF format, and we encourage authors to follow the style guidelines of NIPS 2015 at: <a href="https://nips.cc/Conferences/2015/PaperInformation/AuthorSubmissionInstructions">https://nips.cc/Conferences/2015/PaperInformation/AuthorSubmissionInstructions</a> <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Submissions must be made through: <o:p></o:p></p><p class=MsoNormal><a href="https://cmt.research.microsoft.com/MMML2015/">https://cmt.research.microsoft.com/MMML2015/</a> <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Submissions will be reviewed for relevance, quality and novelty. They will be presented as posters during the poster session (before the lunch break). A handful of submissions will be given a short talk. <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><span lang=FR-CA>ORGANIZERS<o:p></o:p></span></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l2 level1 lfo3'><![if !supportLists]><span lang=FR-CA style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=FR-CA>Louis-Philippe Morency (<a href="mailto:morency@cs.cmu.edu">morency@cs.cmu.edu</a>) <o:p></o:p></span></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l2 level1 lfo3'><![if !supportLists]><span lang=FR-CA style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=FR-CA>Tadas Baltrušaitis (<a href="mailto:tbaltrus@cs.cmu.edu">tbaltrus@cs.cmu.edu</a>) <o:p></o:p></span></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l2 level1 lfo3'><![if !supportLists]><span lang=FR-CA style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=FR-CA>Aaron Courville (<a href="mailto:aaron.courville@umontreal.ca">aaron.courville@umontreal.ca</a>) <o:p></o:p></span></p><p class=MsoListParagraph style='text-indent:-.25in;mso-list:l2 level1 lfo3'><![if !supportLists]><span style='font-family:Symbol'><span style='mso-list:Ignore'>·<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]>KyungHyun Cho (<a href="mailto:kyunghyun.cho@nyu.edu">kyunghyun.cho@nyu.edu</a>)<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>