<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>Memory-Immersed Collaborative Digitization for Area-Efficient Compute-in-Memory Deep Learning</dc:title><dc:creator>Nasrin, Shamma; Hashem, Maeesha Binte; Darabi, Nastaran; Parpillon, Benjamin; Fahim, Farah; Gomes, Wilfred; Trivedi, Amit Ranjan</dc:creator><dc:corporate_author/><dc:editor/><dc:description/><dc:publisher>IEEE</dc:publisher><dc:date>2023-06-11</dc:date><dc:nsf_par_id>10503744</dc:nsf_par_id><dc:journal_name/><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation>1 to 5</dc:page_range_or_elocation><dc:issn/><dc:isbn>979-8-3503-3267-4</dc:isbn><dc:doi>https://doi.org/10.1109/AICAS57966.2023.10168632</dc:doi><dcq:identifierAwardId>2046435</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location>Hangzhou, China</dc:location><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>