Publication Information

{'id': 'https://openalex.org/W3102722370', 'doi': 'https://doi.org/10.1109/allerton.2015.7447163', 'title': 'A deep learning approach to structured signal recovery', 'display_name': 'A deep learning approach to structured signal recovery', 'publication_year': 2015, 'publication_date': '2015-09-01', 'ids': {'openalex': 'https://openalex.org/W3102722370', 'doi': 'https://doi.org/10.1109/allerton.2015.7447163', 'mag': '3102722370'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'https://doi.org/10.1109/allerton.2015.7447163', 'pdf_url': None, 'source': None, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'preprint', 'type_crossref': 'proceedings-article', 'indexed_in': ['arxiv', 'crossref', 'datacite'], 'open_access': {'is_oa': True, 'oa_status': 'green', 'oa_url': 'http://arxiv.org/pdf/1508.04065', 'any_repository_has_fulltext': True}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5003699159', 'display_name': 'Ali Mousavi', 'orcid': 'https://orcid.org/0000-0003-0360-2712'}, 'institutions': [{'id': 'https://openalex.org/I74775410', 'display_name': 'Rice University', 'ror': 'https://ror.org/008zs3103', 'country_code': 'US', 'type': 'education', 'lineage': ['https://openalex.org/I74775410']}], 'countries': ['US'], 'is_corresponding': False, 'raw_author_name': 'Ali Mousavi', 'raw_affiliation_strings': ['Department of Electrical and Computer Engineering, Rice University, Houston, TX'], 'affiliations': [{'raw_affiliation_string': 'Department of Electrical and Computer Engineering, Rice University, Houston, TX', 'institution_ids': ['https://openalex.org/I74775410']}]}, {'author_position': 'middle', 'author': {'id': 'https://openalex.org/A5033298605', 'display_name': 'Ankit Patel', 'orcid': 'https://orcid.org/0000-0001-9678-496X'}, 'institutions': [{'id': 'https://openalex.org/I74775410', 'display_name': 'Rice University', 'ror': 'https://ror.org/008zs3103', 'country_code': 'US', 'type': 'education', 'lineage': ['https://openalex.org/I74775410']}], 'countries': ['US'], 'is_corresponding': False, 'raw_author_name': 'Ankit B. Patel', 'raw_affiliation_strings': ['Department of Electrical and Computer Engineering, Rice University, Houston, TX'], 'affiliations': [{'raw_affiliation_string': 'Department of Electrical and Computer Engineering, Rice University, Houston, TX', 'institution_ids': ['https://openalex.org/I74775410']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5072713767', 'display_name': 'Richard G. Baraniuk', 'orcid': 'https://orcid.org/0000-0002-0721-8999'}, 'institutions': [{'id': 'https://openalex.org/I74775410', 'display_name': 'Rice University', 'ror': 'https://ror.org/008zs3103', 'country_code': 'US', 'type': 'education', 'lineage': ['https://openalex.org/I74775410']}], 'countries': ['US'], 'is_corresponding': False, 'raw_author_name': 'Richard G. Baraniuk', 'raw_affiliation_strings': ['Department of Electrical and Computer Engineering, Rice University, Houston, TX'], 'affiliations': [{'raw_affiliation_string': 'Department of Electrical and Computer Engineering, Rice University, Houston, TX', 'institution_ids': ['https://openalex.org/I74775410']}]}], 'institution_assertions': [], 'countries_distinct_count': 1, 'institutions_distinct_count': 1, 'corresponding_author_ids': [], 'corresponding_institution_ids': [], 'apc_list': None, 'apc_paid': None, 'fwci': None, 'has_fulltext': True, 'fulltext_origin': 'ngrams', 'cited_by_count': 442, 'citation_normalized_percentile': {'value': 0.989641, 'is_in_top_1_percent': False, 'is_in_top_10_percent': True}, 'cited_by_percentile_year': {'min': 99, 'max': 100}, 'biblio': {'volume': None, 'issue': None, 'first_page': '1336', 'last_page': '1343'}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T10500', 'display_name': 'Sparse and Compressive Sensing Techniques', 'score': 1.0, 'subfield': {'id': 'https://openalex.org/subfields/2206', 'display_name': 'Computational Mechanics'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, 'topics': [{'id': 'https://openalex.org/T10500', 'display_name': 'Sparse and Compressive Sensing Techniques', 'score': 1.0, 'subfield': {'id': 'https://openalex.org/subfields/2206', 'display_name': 'Computational Mechanics'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T11447', 'display_name': 'Blind Source Separation Techniques', 'score': 0.9997, 'subfield': {'id': 'https://openalex.org/subfields/1711', 'display_name': 'Signal Processing'}, 'field': {'id': 'https://openalex.org/fields/17', 'display_name': 'Computer Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T10688', 'display_name': 'Image and Signal Denoising Methods', 'score': 0.9994, 'subfield': {'id': 'https://openalex.org/subfields/1707', 'display_name': 'Computer Vision and Pattern Recognition'}, 'field': {'id': 'https://openalex.org/fields/17', 'display_name': 'Computer Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/autoencoder', 'display_name': 'Autoencoder', 'score': 0.7258785}, {'id': 'https://openalex.org/keywords/signal', 'display_name': 'SIGNAL (programming language)', 'score': 0.62840027}, {'id': 'https://openalex.org/keywords/feature', 'display_name': 'Feature (linguistics)', 'score': 0.61574805}, {'id': 'https://openalex.org/keywords/feature-learning', 'display_name': 'Feature Learning', 'score': 0.59455425}, {'id': 'https://openalex.org/keywords/representation', 'display_name': 'Representation', 'score': 0.52887535}, {'id': 'https://openalex.org/keywords/signal-reconstruction', 'display_name': 'Signal reconstruction', 'score': 0.46043912}], 'concepts': [{'id': 'https://openalex.org/C101738243', 'wikidata': 'https://www.wikidata.org/wiki/Q786435', 'display_name': 'Autoencoder', 'level': 3, 'score': 0.7258785}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.70551085}, {'id': 'https://openalex.org/C124851039', 'wikidata': 'https://www.wikidata.org/wiki/Q2665459', 'display_name': 'Compressed sensing', 'level': 2, 'score': 0.65200555}, {'id': 'https://openalex.org/C2779843651', 'wikidata': 'https://www.wikidata.org/wiki/Q7390335', 'display_name': 'SIGNAL (programming language)', 'level': 2, 'score': 0.62840027}, {'id': 'https://openalex.org/C2776401178', 'wikidata': 'https://www.wikidata.org/wiki/Q12050496', 'display_name': 'Feature (linguistics)', 'level': 2, 'score': 0.61574805}, {'id': 'https://openalex.org/C59404180', 'wikidata': 'https://www.wikidata.org/wiki/Q17013334', 'display_name': 'Feature learning', 'level': 2, 'score': 0.59455425}, {'id': 'https://openalex.org/C154945302', 'wikidata': 'https://www.wikidata.org/wiki/Q11660', 'display_name': 'Artificial intelligence', 'level': 1, 'score': 0.58569556}, {'id': 'https://openalex.org/C2776359362', 'wikidata': 'https://www.wikidata.org/wiki/Q2145286', 'display_name': 'Representation (politics)', 'level': 3, 'score': 0.52887535}, {'id': 'https://openalex.org/C163294075', 'wikidata': 'https://www.wikidata.org/wiki/Q581861', 'display_name': 'Noise reduction', 'level': 2, 'score': 0.5163804}, {'id': 'https://openalex.org/C153180895', 'wikidata': 'https://www.wikidata.org/wiki/Q7148389', 'display_name': 'Pattern recognition (psychology)', 'level': 2, 'score': 0.5035388}, {'id': 'https://openalex.org/C70958404', 'wikidata': 'https://www.wikidata.org/wiki/Q7512728', 'display_name': 'Signal reconstruction', 'level': 4, 'score': 0.46043912}, {'id': 'https://openalex.org/C108583219', 'wikidata': 'https://www.wikidata.org/wiki/Q197536', 'display_name': 'Deep learning', 'level': 2, 'score': 0.4586307}, {'id': 'https://openalex.org/C158622935', 'wikidata': 'https://www.wikidata.org/wiki/Q660848', 'display_name': 'Nonlinear system', 'level': 2, 'score': 0.44995928}, {'id': 'https://openalex.org/C124066611', 'wikidata': 'https://www.wikidata.org/wiki/Q28684319', 'display_name': 'Sparse approximation', 'level': 2, 'score': 0.43088713}, {'id': 'https://openalex.org/C51823790', 'wikidata': 'https://www.wikidata.org/wiki/Q504353', 'display_name': 'Greedy algorithm', 'level': 2, 'score': 0.42303157}, {'id': 'https://openalex.org/C2776502983', 'wikidata': 'https://www.wikidata.org/wiki/Q690182', 'display_name': 'Contrast (vision)', 'level': 2, 'score': 0.4212342}, {'id': 'https://openalex.org/C157972887', 'wikidata': 'https://www.wikidata.org/wiki/Q463359', 'display_name': 'Convex optimization', 'level': 3, 'score': 0.41368717}, {'id': 'https://openalex.org/C119857082', 'wikidata': 'https://www.wikidata.org/wiki/Q2539', 'display_name': 'Machine learning', 'level': 1, 'score': 0.4029433}, {'id': 'https://openalex.org/C11413529', 'wikidata': 'https://www.wikidata.org/wiki/Q8366', 'display_name': 'Algorithm', 'level': 1, 'score': 0.36524594}, {'id': 'https://openalex.org/C104267543', 'wikidata': 'https://www.wikidata.org/wiki/Q208163', 'display_name': 'Signal processing', 'level': 3, 'score': 0.36129743}, {'id': 'https://openalex.org/C112680207', 'wikidata': 'https://www.wikidata.org/wiki/Q714886', 'display_name': 'Regular polygon', 'level': 2, 'score': 0.28155202}, {'id': 'https://openalex.org/C33923547', 'wikidata': 'https://www.wikidata.org/wiki/Q395', 'display_name': 'Mathematics', 'level': 0, 'score': 0.15346813}, {'id': 'https://openalex.org/C76155785', 'wikidata': 'https://www.wikidata.org/wiki/Q418', 'display_name': 'Telecommunications', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C41895202', 'wikidata': 'https://www.wikidata.org/wiki/Q8162', 'display_name': 'Linguistics', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C138885662', 'wikidata': 'https://www.wikidata.org/wiki/Q5891', 'display_name': 'Philosophy', 'level': 0, 'score': 0.0}, {'id': 'https://openalex.org/C554190296', 'wikidata': 'https://www.wikidata.org/wiki/Q47528', 'display_name': 'Radar', 'level': 2, 'score': 0.0}, {'id': 'https://openalex.org/C121332964', 'wikidata': 'https://www.wikidata.org/wiki/Q413', 'display_name': 'Physics', 'level': 0, 'score': 0.0}, {'id': 'https://openalex.org/C2524010', 'wikidata': 'https://www.wikidata.org/wiki/Q8087', 'display_name': 'Geometry', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C62520636', 'wikidata': 'https://www.wikidata.org/wiki/Q944', 'display_name': 'Quantum mechanics', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C94625758', 'wikidata': 'https://www.wikidata.org/wiki/Q7163', 'display_name': 'Politics', 'level': 2, 'score': 0.0}, {'id': 'https://openalex.org/C17744445', 'wikidata': 'https://www.wikidata.org/wiki/Q36442', 'display_name': 'Political science', 'level': 0, 'score': 0.0}, {'id': 'https://openalex.org/C199539241', 'wikidata': 'https://www.wikidata.org/wiki/Q7748', 'display_name': 'Law', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C199360897', 'wikidata': 'https://www.wikidata.org/wiki/Q9143', 'display_name': 'Programming language', 'level': 1, 'score': 0.0}], 'mesh': [], 'locations_count': 4, 'locations': [{'is_oa': False, 'landing_page_url': 'https://doi.org/10.1109/allerton.2015.7447163', 'pdf_url': None, 'source': None, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, {'is_oa': True, 'landing_page_url': 'http://arxiv.org/abs/1508.04065', 'pdf_url': 'http://arxiv.org/pdf/1508.04065', 'source': {'id': 'https://openalex.org/S4306400194', 'display_name': 'arXiv (Cornell University)', 'issn_l': None, 'issn': None, 'is_oa': True, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I205783295', 'host_organization_name': 'Cornell University', 'host_organization_lineage': ['https://openalex.org/I205783295'], 'host_organization_lineage_names': ['Cornell University'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, {'is_oa': True, 'landing_page_url': 'https://arxiv.org/abs/1508.04065', 'pdf_url': 'https://arxiv.org/pdf/1508.04065', 'source': {'id': 'https://openalex.org/S4306400194', 'display_name': 'arXiv (Cornell University)', 'issn_l': None, 'issn': None, 'is_oa': True, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I205783295', 'host_organization_name': 'Cornell University', 'host_organization_lineage': ['https://openalex.org/I205783295'], 'host_organization_lineage_names': ['Cornell University'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, {'is_oa': False, 'landing_page_url': 'https://api.datacite.org/dois/10.48550/arxiv.1508.04065', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S4393179698', 'display_name': 'DataCite API', 'issn_l': None, 'issn': None, 'is_oa': True, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I4210145204', 'host_organization_name': 'DataCite', 'host_organization_lineage': ['https://openalex.org/I4210145204'], 'host_organization_lineage_names': ['DataCite'], 'type': 'metadata'}, 'license': None, 'license_id': None, 'version': None}], 'best_oa_location': {'is_oa': True, 'landing_page_url': 'http://arxiv.org/abs/1508.04065', 'pdf_url': 'http://arxiv.org/pdf/1508.04065', 'source': {'id': 'https://openalex.org/S4306400194', 'display_name': 'arXiv (Cornell University)', 'issn_l': None, 'issn': None, 'is_oa': True, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I205783295', 'host_organization_name': 'Cornell University', 'host_organization_lineage': ['https://openalex.org/I205783295'], 'host_organization_lineage_names': ['Cornell University'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, 'sustainable_development_goals': [], 'grants': [], 'datasets': [], 'versions': ['https://openalex.org/W2219727625', 'https://openalex.org/W3102722370'], 'referenced_works_count': 37, 'referenced_works': ['https://openalex.org/W1498436455', 'https://openalex.org/W1533861849', 'https://openalex.org/W1798821657', 'https://openalex.org/W1822073640', 'https://openalex.org/W2013035813', 'https://openalex.org/W2015418199', 'https://openalex.org/W2037642501', 'https://openalex.org/W2060038468', 'https://openalex.org/W2082029531', 'https://openalex.org/W2087326866', 'https://openalex.org/W2100495367', 'https://openalex.org/W2100556411', 'https://openalex.org/W2104266187', 'https://openalex.org/W2110798204', 'https://openalex.org/W2115755118', 'https://openalex.org/W2116064496', 'https://openalex.org/W2116581300', 'https://openalex.org/W2117539524', 'https://openalex.org/W2121835854', 'https://openalex.org/W2129638195', 'https://openalex.org/W2134929491', 'https://openalex.org/W2140622310', 'https://openalex.org/W2145096794', 'https://openalex.org/W2153518451', 'https://openalex.org/W2154232923', 'https://openalex.org/W2154815154', 'https://openalex.org/W2160547390', 'https://openalex.org/W2161914416', 'https://openalex.org/W2289917018', 'https://openalex.org/W2296616510', 'https://openalex.org/W2400972628', 'https://openalex.org/W2963322354', 'https://openalex.org/W2963676935', 'https://openalex.org/W3118608800', 'https://openalex.org/W4235765578', 'https://openalex.org/W4250955649', 'https://openalex.org/W54257720'], 'related_works': ['https://openalex.org/W4389832810', 'https://openalex.org/W4313561566', 'https://openalex.org/W4281663961', 'https://openalex.org/W4220682630', 'https://openalex.org/W3208888551', 'https://openalex.org/W3208386644', 'https://openalex.org/W3181622257', 'https://openalex.org/W3163146846', 'https://openalex.org/W2983142544', 'https://openalex.org/W2891059443'], 'abstract_inverted_index': {'In': [0, 14, 61], 'this': [1], 'paper,': [2], 'we': [3, 32, 63], 'develop': [4], 'a': [5, 34, 48, 58, 65], 'new': [6], 'framework': [7, 37], 'for': [8], 'sensing': [9, 18], 'and': [10, 27, 42, 54, 89], 'recovering': [11], 'structured': [12, 49], 'signals.': [13], 'contrast': [15], 'to': [16, 78, 96], 'compressive': [17], '(CS)': [19], 'systems': [20], 'that': [21, 38, 46, 55], 'employ': [22], 'linear': [23, 41], 'measurements,': [24, 45], 'sparse': [25], 'representations,': [26], 'computationally': [28], 'complex': [29], 'convex/greedy': [30], 'algorithms,': [31], 'introduce': [33], 'deep': [35], 'learning': [36], 'supports': [39], 'both': [40], 'mildly': [43], 'nonlinear': [44], 'learns': [47], 'representation': [50], 'from': [51], 'training': [52], 'data,': [53], 'efficiently': [56], 'computes': [57], 'signal': [59, 91], 'estimate.': [60], 'particular,': [62], 'apply': [64], 'stacked': [66], 'denoising': [67], 'autoencoder': [68], '(SDA),': [69], 'as': [70, 94], 'an': [71], 'unsupervised': [72], 'feature': [73], 'learner.': [74], 'SDA': [75], 'enables': [76], 'us': [77], 'capture': [79], 'statistical': [80], 'dependencies': [81], 'between': [82], 'the': [83, 97], 'different': [84], 'elements': [85], 'of': [86], 'certain': [87], 'signals': [88], 'improve': [90], 'recovery': [92], 'performance': [93], 'compared': [95], 'CS': [98], 'approach.': [99]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W3102722370', 'counts_by_year': [{'year': 2024, 'cited_by_count': 27}, {'year': 2023, 'cited_by_count': 38}, {'year': 2022, 'cited_by_count': 50}, {'year': 2021, 'cited_by_count': 74}, {'year': 2020, 'cited_by_count': 87}, {'year': 2019, 'cited_by_count': 73}, {'year': 2018, 'cited_by_count': 48}, {'year': 2017, 'cited_by_count': 27}, {'year': 2016, 'cited_by_count': 17}], 'updated_date': '2025-01-07T19:54:13.890285', 'created_date': '2020-11-23'}