{"id":3519,"date":"2025-09-17T17:06:37","date_gmt":"2025-09-17T17:06:37","guid":{"rendered":"https:\/\/172-234-197-23.ip.linodeusercontent.com\/?page_id=3519"},"modified":"2025-09-17T17:06:37","modified_gmt":"2025-09-17T17:06:37","slug":"goal-aware-sparsity-for-multi-subspace-retrieval-2","status":"publish","type":"page","link":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/?page_id=3519","title":{"rendered":"Goal-Aware Sparsity for Multi-Subspace Retrieval"},"content":{"rendered":"\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/Goal-Aware-Sparsity-for-Multi-Subspace-Retrieval.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of Goal-Aware Sparsity for Multi-Subspace Retrieval.\"><\/object><a id=\"wp-block-file--media-ef2b0890-68e2-44a3-b392-3ebfa24303ca\" href=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/Goal-Aware-Sparsity-for-Multi-Subspace-Retrieval.pdf\">Goal-Aware Sparsity for Multi-Subspace Retrieval<\/a><a href=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/Goal-Aware-Sparsity-for-Multi-Subspace-Retrieval.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-ef2b0890-68e2-44a3-b392-3ebfa24303ca\">Download<\/a><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">High-dimensional vector retrieval systems often suffer from the curse of dimensionality, leading to reduced efficiency and degraded performance in large-scale applications.<br>We introduce a goal-aware sparsity framework that learns<br>adaptive feature masks aligned with specific retrieval objectives,<br>enabling both computational efficiency through dimensionality<br>reduction and improved effectiveness by focusing on task-relevant<br>subspaces. Our approach integrates seamlessly with FAISSbased multi-subspace indexing, providing soft and hard masking<br>strategies with online adaptation capabilities. We demonstrate<br>that goal-specific masks can achieve 25-50% sparsity while<br>maintaining or improving retrieval accuracy across RF signal<br>processing and speech recognition tasks. The framework supports<br>standardized JSON outputs, mask diagnostics, and provides<br>interpretable explanations of feature importance. Experiments<br>show that our method outperforms PCA-based dimensionality<br>reduction by 15-30% in retrieval accuracy while providing 2-4\u00d7<br>speedup in query processing.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>High-dimensional vector retrieval systems often suffer from the curse of dimensionality, leading to reduced efficiency and degraded performance in large-scale applications.We introduce a goal-aware sparsity framework that learnsadaptive feature masks aligned with specific retrieval objectives,enabling both computational efficiency through dimensionalityreduction and improved effectiveness by focusing on task-relevantsubspaces. Our approach integrates seamlessly with FAISSbased multi-subspace indexing,&hellip;&nbsp;<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"class_list":["post-3519","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages\/3519","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3519"}],"version-history":[{"count":0,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages\/3519\/revisions"}],"wp:attachment":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3519"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}