{"id":190985,"date":"2014-06-12T00:00:00","date_gmt":"2014-06-12T17:09:52","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/msr-research-item\/ml-day-2014-perceptual-annotation-from-biologically-inspired-to-biologically-informed-machine-learning\/"},"modified":"2016-07-15T15:17:41","modified_gmt":"2016-07-15T22:17:41","slug":"ml-day-2014-perceptual-annotation-from-biologically-inspired-to-biologically-informed-machine-learning","status":"publish","type":"msr-video","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/video\/ml-day-2014-perceptual-annotation-from-biologically-inspired-to-biologically-informed-machine-learning\/","title":{"rendered":"ML Day 2014 &#8211; &#8220;Perceptual Annotation&#8221;: from Biologically Inspired, to Biologically Informed Machine Learning"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Many machine learning applications, explicitly or implicitly, attempt to mimic natural human abilities in a machine.  Indeed, any setting where human-provided labels are used as ground truth \u2013 whether the system aspires to be biologically-inspired or not \u2013 is ultimately driven by the human visual and cognitive system and its ability to provide accurate exemplary labels.  However, human-provided ground-truth labels are in many ways just the tip of the iceberg of the information that can be extracted from human judgments. I will describe a new approach \u2013 called &#8220;perceptual annotation&#8221; \u2013 in which we use an advanced online psychometric testing platform to acquire new kinds of human annotation data, and we incorporate these data directly into the formulation of a machine learning algorithm. A key intuition for this approach is that while it may be infeasible to dramatically increase the amount of data and high-quality labels available for the training of a given system, measuring the latent exemplar-by-exemplar landscape of difficulty and patterns of human errors can provide important information for regularizing the solution of the system at hand. Finally, I will conclude by exploring how this approach can be extended to incorporate an even greater diversity of different kinds of biological data<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Many machine learning applications, explicitly or implicitly, attempt to mimic natural human abilities in a machine. Indeed, any setting where human-provided labels are used as ground truth \u2013 whether the system aspires to be biologically-inspired or not \u2013 is ultimately driven by the human visual and cognitive system and its ability to provide accurate exemplary [&hellip;]<\/p>\n","protected":false},"featured_media":198404,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-190985","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/LjbpzDBdenE","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/190985","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/190985\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/media\/198404"}],"wp:attachment":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/media?parent=190985"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=190985"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=190985"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=190985"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=190985"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=190985"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=190985"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=190985"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=190985"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=190985"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}