{"id":346766,"date":"2017-01-05T09:33:55","date_gmt":"2017-01-05T17:33:55","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=346766"},"modified":"2018-10-16T19:56:57","modified_gmt":"2018-10-17T02:56:57","slug":"discrepancy-without-partial-colorings","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/discrepancy-without-partial-colorings\/","title":{"rendered":"Discrepancy Without Partial Colorings"},"content":{"rendered":"<p>Spencer\u2019s theorem asserts that, for any family of n subsets of ground set of size n, the elements of the ground set can be \u201ccolored\u201d by the values \u00b11 such that the sum of every set is O( \u221a n) in absolute value. All existing proofs of this result recursively construct \u201cpartial colorings\u201d, which assign \u00b11 values to half of the ground set. We devise the first algorithm for Spencer\u2019s theorem that directly computes a coloring, without recursively computing partial colorings.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Spencer\u2019s theorem asserts that, for any family of n subsets of ground set of size n, the elements of the ground set can be \u201ccolored\u201d by the values \u00b11 such that the sum of every set is O( \u221a n) in absolute value. All existing proofs of this result recursively construct \u201cpartial colorings\u201d, which assign [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"In International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX'2014)","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"In International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX'2014)","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2014-01-01","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":0,"msr_citation_count":0,"msr_influential_citations":0,"msr_reference_count":0,"msr_s2_match_confidence":0,"msr_microsoftintellectualproperty":true,"msr_s2_open_access":false,"msr_s2_author_ids":[],"msr_pub_ids":[],"msr_hide_image_in_river":0,"footnotes":""},"msr-research-highlight":[],"research-area":[13561],"msr-publication-type":[193716],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-346766","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-algorithms","msr-locale-en_us"],"msr_publishername":"","msr_edition":"In International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX'2014)","msr_affiliation":"","msr_published_date":"2014-01-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"346769","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"discrepancy1","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2017\/01\/discrepancy1.pdf","id":346769,"label_id":0}],"msr_related_uploader":"","msr_citation_count":0,"msr_citation_count_updated":"","msr_s2_paper_id":"","msr_influential_citations":0,"msr_reference_count":0,"msr_arxiv_id":"","msr_s2_author_ids":[],"msr_s2_open_access":false,"msr_s2_pdf_url":null,"msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Nicholas J. 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