{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:WXAIICEEHEB6L47BNHCZ2YVBM4","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":"62baeb049dd2dc6ffbf0f545a195129bbc591d69c5ea9d3df24846fc4f572b8f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-10-17T04:17:07Z","title_canon_sha256":"9f1412c22c362004135d6b9ecdd03d9c79aefd270556375df0d62eb1a8f1f668"},"schema_version":"1.0","source":{"id":"1710.06085","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.06085","created_at":"2026-05-18T00:32:37Z"},{"alias_kind":"arxiv_version","alias_value":"1710.06085v1","created_at":"2026-05-18T00:32:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.06085","created_at":"2026-05-18T00:32:37Z"},{"alias_kind":"pith_short_12","alias_value":"WXAIICEEHEB6","created_at":"2026-05-18T12:31:53Z"},{"alias_kind":"pith_short_16","alias_value":"WXAIICEEHEB6L47B","created_at":"2026-05-18T12:31:53Z"},{"alias_kind":"pith_short_8","alias_value":"WXAIICEE","created_at":"2026-05-18T12:31:53Z"}],"graph_snapshots":[{"event_id":"sha256:f69fbeec6fe98cf5fc5cf972f2d45a505de7be71d7383b46355e29e410970653","target":"graph","created_at":"2026-05-18T00:32:37Z","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"},"paper":{"abstract_excerpt":"We study parameter estimation in Nonlinear Factor Analysis (NFA) where the generative model is parameterized by a deep neural network. Recent work has focused on learning such models using inference (or recognition) networks; we identify a crucial problem when modeling large, sparse, high-dimensional datasets -- underfitting. We study the extent of underfitting, highlighting that its severity increases with the sparsity of the data. We propose methods to tackle it via iterative optimization inspired by stochastic variational inference \\citep{hoffman2013stochastic} and improvements in the spars","authors_text":"Dawen Liang, Matthew Hoffman, Rahul G. Krishnan","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-10-17T04:17:07Z","title":"On the challenges of learning with inference networks on sparse, high-dimensional data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.06085","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":"sha256:88f7cdfe9bd625ed742aa876192464e7e5cf989b46b574c1718879d8ece26e3a","target":"record","created_at":"2026-05-18T00:32:37Z","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":"62baeb049dd2dc6ffbf0f545a195129bbc591d69c5ea9d3df24846fc4f572b8f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-10-17T04:17:07Z","title_canon_sha256":"9f1412c22c362004135d6b9ecdd03d9c79aefd270556375df0d62eb1a8f1f668"},"schema_version":"1.0","source":{"id":"1710.06085","kind":"arxiv","version":1}},"canonical_sha256":"b5c08408843903e5f3e169c59d62a1671d0793214620505c9f76486e582fa534","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b5c08408843903e5f3e169c59d62a1671d0793214620505c9f76486e582fa534","first_computed_at":"2026-05-18T00:32:37.821517Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:32:37.821517Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3xtrqhzeae0w9YIc/zaMg7vAO+01Lu4RZzXSKrrr8ef1xaapIcvHa0FT2dCtVSPOuGsQA5IVBFn06mACpGNMBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:32:37.822396Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.06085","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:88f7cdfe9bd625ed742aa876192464e7e5cf989b46b574c1718879d8ece26e3a","sha256:f69fbeec6fe98cf5fc5cf972f2d45a505de7be71d7383b46355e29e410970653"],"state_sha256":"a156c3979842992133e2bf87dd2fbe8afe723f3b9f4b8f3b01e205ac8fabce82"}