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We also  compare the lower boundof the resulting semidefinite (or Shor) relaxation with that of the standard LP-relaxation and the first semidefinite relaxationsassociated with the Lasserre hierarchy and the copositive formulations of $P$."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1505.06840","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2015-05-26T08:06:39Z","cross_cats_sorted":[],"title_canon_sha256":"9269cfd5df711ad1804cba2f7b4ab4902d8463d59dbc5f16e38c6243f312c081","abstract_canon_sha256":"8ea76d7cc776513c77eb3b07bb6a8a5d01bbd3e87223cf9ce2ed9b5349c62f21"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:23:58.202222Z","signature_b64":"TSYX2kqgo2f8lunzVjO8tPbl/44BqJjJ1EJ5O/j7Ga0vcSxFhQkZk9SJkHS2jl3KrNfr840RY6wnioR0MfoyDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0350362c956038142451622e20c4be86ebfab0e861f0319a606101b7230085bd","last_reissued_at":"2026-05-18T01:23:58.201543Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:23:58.201543Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A max-cut formulation of 0/1 programs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Jean-Bernard Lasserre (LAAS-MAC)","submitted_at":"2015-05-26T08:06:39Z","abstract_excerpt":"We show that the linear or quadratic 0/1 program\\[P:\\quad\\min\\{ c^Tx+x^TFx : \\:A\\,x =b;\\:x\\in\\{0,1\\}^n\\},\\]can be formulated as a MAX-CUT problem whose associated graph is simply related to the matrices $\\F$ and $\\A^T\\A$.Hence the whole arsenal  of approximation techniques for MAX-CUT can be applied. 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