{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:PU7B2A3UUT4QBIU6RQKKFXKO7X","short_pith_number":"pith:PU7B2A3U","canonical_record":{"source":{"id":"2002.11835","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-26T23:07:19Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"5cadc3620d9f87fe60d4f4ee699fce85f58f316b4a4f43e279508917b52920bc","abstract_canon_sha256":"01aef58497472fb0fc90a76d79cecaf6c4dc805430800386c751361ef83cbb73"},"schema_version":"1.0"},"canonical_sha256":"7d3e1d0374a4f900a29e8c14a2dd4efdd9125b1d9f0ddd1ba73c1655e53abe1c","source":{"kind":"arxiv","id":"2002.11835","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.11835","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"arxiv_version","alias_value":"2002.11835v1","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.11835","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"pith_short_12","alias_value":"PU7B2A3UUT4Q","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"pith_short_16","alias_value":"PU7B2A3UUT4QBIU6","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"pith_short_8","alias_value":"PU7B2A3U","created_at":"2026-07-05T00:44:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:PU7B2A3UUT4QBIU6RQKKFXKO7X","target":"record","payload":{"canonical_record":{"source":{"id":"2002.11835","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-26T23:07:19Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"5cadc3620d9f87fe60d4f4ee699fce85f58f316b4a4f43e279508917b52920bc","abstract_canon_sha256":"01aef58497472fb0fc90a76d79cecaf6c4dc805430800386c751361ef83cbb73"},"schema_version":"1.0"},"canonical_sha256":"7d3e1d0374a4f900a29e8c14a2dd4efdd9125b1d9f0ddd1ba73c1655e53abe1c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:44:09.530626Z","signature_b64":"HeD1jjGNykj5VcjMHLvaG4PHluaprUHepci1UMgxSsmXn/1DCRykSjdKq9GmtC2OBlhCZ1qZkv1KX7m7GAe3Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7d3e1d0374a4f900a29e8c14a2dd4efdd9125b1d9f0ddd1ba73c1655e53abe1c","last_reissued_at":"2026-07-05T00:44:09.530137Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:44:09.530137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.11835","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:44:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6+tCdB2DKwuWNHOpfbkYoWCtYuZtlZscB49vowLN/c5T6/eXGTZ2D60ZEEs4GqUA8LzN9X47JGJA5ir8Wz3kBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:55:25.758839Z"},"content_sha256":"a592e17399b33c98316e5e1c41d0cd745ee83a5caed609f124a5c74a9e041001","schema_version":"1.0","event_id":"sha256:a592e17399b33c98316e5e1c41d0cd745ee83a5caed609f124a5c74a9e041001"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:PU7B2A3UUT4QBIU6RQKKFXKO7X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tensor Decompositions in Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Danilo P. Mandic, Davide Bacciu","submitted_at":"2020-02-26T23:07:19Z","abstract_excerpt":"The paper surveys the topic of tensor decompositions in modern machine learning applications. It focuses on three active research topics of significant relevance for the community. After a brief review of consolidated works on multi-way data analysis, we consider the use of tensor decompositions in compressing the parameter space of deep learning models. Lastly, we discuss how tensor methods can be leveraged to yield richer adaptive representations of complex data, including structured information. The paper concludes with a discussion on interesting open research challenges."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.11835","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2002.11835/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:44:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QcR83s3Sa8E2dBGBqDWY/yUXZ89bJY49icIe8UaL5CoCHbtk/XzRKqBYlVwdc3TpHfWyTbzge9X5m2WWYeemCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:55:25.759476Z"},"content_sha256":"9d0404a5fec3057da7c227e9a36615c557ff438bd3e6fe9999009797d4d73f48","schema_version":"1.0","event_id":"sha256:9d0404a5fec3057da7c227e9a36615c557ff438bd3e6fe9999009797d4d73f48"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PU7B2A3UUT4QBIU6RQKKFXKO7X/bundle.json","state_url":"https://pith.science/pith/PU7B2A3UUT4QBIU6RQKKFXKO7X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PU7B2A3UUT4QBIU6RQKKFXKO7X/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-06T15:55:25Z","links":{"resolver":"https://pith.science/pith/PU7B2A3UUT4QBIU6RQKKFXKO7X","bundle":"https://pith.science/pith/PU7B2A3UUT4QBIU6RQKKFXKO7X/bundle.json","state":"https://pith.science/pith/PU7B2A3UUT4QBIU6RQKKFXKO7X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PU7B2A3UUT4QBIU6RQKKFXKO7X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:PU7B2A3UUT4QBIU6RQKKFXKO7X","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"01aef58497472fb0fc90a76d79cecaf6c4dc805430800386c751361ef83cbb73","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-26T23:07:19Z","title_canon_sha256":"5cadc3620d9f87fe60d4f4ee699fce85f58f316b4a4f43e279508917b52920bc"},"schema_version":"1.0","source":{"id":"2002.11835","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.11835","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"arxiv_version","alias_value":"2002.11835v1","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.11835","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"pith_short_12","alias_value":"PU7B2A3UUT4Q","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"pith_short_16","alias_value":"PU7B2A3UUT4QBIU6","created_at":"2026-07-05T00:44:09Z"},{"alias_kind":"pith_short_8","alias_value":"PU7B2A3U","created_at":"2026-07-05T00:44:09Z"}],"graph_snapshots":[{"event_id":"sha256:9d0404a5fec3057da7c227e9a36615c557ff438bd3e6fe9999009797d4d73f48","target":"graph","created_at":"2026-07-05T00:44:09Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2002.11835/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The paper surveys the topic of tensor decompositions in modern machine learning applications. It focuses on three active research topics of significant relevance for the community. After a brief review of consolidated works on multi-way data analysis, we consider the use of tensor decompositions in compressing the parameter space of deep learning models. Lastly, we discuss how tensor methods can be leveraged to yield richer adaptive representations of complex data, including structured information. The paper concludes with a discussion on interesting open research challenges.","authors_text":"Danilo P. Mandic, Davide Bacciu","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-26T23:07:19Z","title":"Tensor Decompositions in Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.11835","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:a592e17399b33c98316e5e1c41d0cd745ee83a5caed609f124a5c74a9e041001","target":"record","created_at":"2026-07-05T00:44:09Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"01aef58497472fb0fc90a76d79cecaf6c4dc805430800386c751361ef83cbb73","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-26T23:07:19Z","title_canon_sha256":"5cadc3620d9f87fe60d4f4ee699fce85f58f316b4a4f43e279508917b52920bc"},"schema_version":"1.0","source":{"id":"2002.11835","kind":"arxiv","version":1}},"canonical_sha256":"7d3e1d0374a4f900a29e8c14a2dd4efdd9125b1d9f0ddd1ba73c1655e53abe1c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7d3e1d0374a4f900a29e8c14a2dd4efdd9125b1d9f0ddd1ba73c1655e53abe1c","first_computed_at":"2026-07-05T00:44:09.530137Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:44:09.530137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HeD1jjGNykj5VcjMHLvaG4PHluaprUHepci1UMgxSsmXn/1DCRykSjdKq9GmtC2OBlhCZ1qZkv1KX7m7GAe3Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T00:44:09.530626Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.11835","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a592e17399b33c98316e5e1c41d0cd745ee83a5caed609f124a5c74a9e041001","sha256:9d0404a5fec3057da7c227e9a36615c557ff438bd3e6fe9999009797d4d73f48"],"state_sha256":"34c9d13ce8e0d2d3684d9a9b3deba8a372876edee8a38f49bba306e8e586c6c2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vkfmOIVkVzudyzM2oeT9c/698b7qQ1ywB/uENEDVFSB3BHBBTUC7yVTPpegi4ZRR8xWZ7ch8knZbA0YgAIe5Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T15:55:25.767291Z","bundle_sha256":"4b50126421267f7db080a365eed13eb42c36fec0ba3a25b91992a3a17618525e"}}