{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:26:50Z","timestamp":1750220810932,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,9,10]],"date-time":"2019-09-10T00:00:00Z","timestamp":1568073600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,9,10]]},"DOI":"10.1145\/3298689.3347034","type":"proceedings-article","created":{"date-parts":[[2019,9,11]],"date-time":"2019-09-11T13:21:31Z","timestamp":1568208091000},"page":"119-127","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Relaxed softmax for PU learning"],"prefix":"10.1145","author":[{"given":"Ugo","family":"Tanielian","sequence":"first","affiliation":[{"name":"UPMC, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Flavian","family":"Vasile","sequence":"additional","affiliation":[{"name":"Criteo Research, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,9,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/3305381.3305413"},{"key":"e_1_3_2_1_2_1","first-page":"1137","article-title":"A neural probabilistic language model","author":"Bengio Yoshua","year":"2003","unstructured":"Yoshua Bengio , R\u00e9jean Ducharme , Pascal Vincent , and Christian Jauvin . 2003 . A neural probabilistic language model . Journal of machine learning research 3 , Feb (2003), 1137 -- 1155 . Yoshua Bengio, R\u00e9jean Ducharme, Pascal Vincent, and Christian Jauvin. 2003. A neural probabilistic language model. Journal of machine learning research 3, Feb (2003), 1137--1155.","journal-title":"Journal of machine learning research 3"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2007.912312"},{"key":"e_1_3_2_1_4_1","unstructured":"Yoshua Bengio Jean-S\u00e9bastien Sen\u00e9cal etal 2003. Quick Training of Probabilistic Neural Nets by Importance Sampling.. In AISTATS. 1--9.  Yoshua Bengio Jean-S\u00e9bastien Sen\u00e9cal et al. 2003. Quick Training of Probabilistic Neural Nets by Importance Sampling.. In AISTATS . 1--9."},{"key":"e_1_3_2_1_5_1","first-page":"993","article-title":"Latent dirichlet allocation","author":"Blei David M","year":"2003","unstructured":"David M Blei , Andrew Y Ng , and Michael I Jordan . 2003 . Latent dirichlet allocation . Journal of machine Learning research 3 , Jan (2003), 993 -- 1022 . David M Blei, Andrew Y Ng, and Michael I Jordan. 2003. Latent dirichlet allocation. Journal of machine Learning research 3, Jan (2003), 993--1022.","journal-title":"Journal of machine Learning research 3"},{"key":"e_1_3_2_1_6_1","volume-title":"Enriching Word Vectors with Subword Information. CoRR abs\/1607.04606","author":"Bojanowski Piotr","year":"2016","unstructured":"Piotr Bojanowski , Edouard Grave , Armand Joulin , and Tomas Mikolov . 2016. Enriching Word Vectors with Subword Information. CoRR abs\/1607.04606 ( 2016 ). arXiv:1607.04606 http:\/\/arxiv.org\/abs\/1607.04606 Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2016. Enriching Word Vectors with Subword Information. CoRR abs\/1607.04606 (2016). arXiv:1607.04606 http:\/\/arxiv.org\/abs\/1607.04606"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159695"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401920"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_1_10_1","article-title":"Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. JMLR WCP, Vol. 9","author":"Gutmann M.","year":"2010","unstructured":"M. Gutmann and A. Hyv\u00e4rinen . 2010 . Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. JMLR WCP, Vol. 9 . Journal of Machine Learning Research - Proceedings Track, 297--304. M. Gutmann and A. Hyv\u00e4rinen. 2010. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. JMLR WCP, Vol. 9. Journal of Machine Learning Research - Proceedings Track, 297--304.","journal-title":"Journal of Machine Learning Research - Proceedings Track, 297--304."},{"key":"e_1_3_2_1_11_1","unstructured":"Tzu-Kuo Huang Alekh Agarwal Daniel J Hsu John Langford and Robert E Schapire. 2015. Efficient and parsimonious agnostic active learning. In Advances in Neural Information Processing Systems. 2755--2763.   Tzu-Kuo Huang Alekh Agarwal Daniel J Hsu John Langford and Robert E Schapire. 2015. Efficient and parsimonious agnostic active learning. In Advances in Neural Information Processing Systems . 2755--2763."},{"key":"e_1_3_2_1_12_1","volume-title":"On Using Very Large Target Vocabulary for Neural Machine Translation. CoRR abs\/1412.2007","author":"Jean S\u00e9bastien","year":"2014","unstructured":"S\u00e9bastien Jean , Kyunghyun Cho , Roland Memisevic , and Yoshua Bengio . 2014. On Using Very Large Target Vocabulary for Neural Machine Translation. CoRR abs\/1412.2007 ( 2014 ). arXiv:1412.2007 http:\/\/arxiv.org\/abs\/1412.2007 S\u00e9bastien Jean, Kyunghyun Cho, Roland Memisevic, and Yoshua Bengio. 2014. On Using Very Large Target Vocabulary for Neural Machine Translation. CoRR abs\/1412.2007 (2014). arXiv:1412.2007 http:\/\/arxiv.org\/abs\/1412.2007"},{"key":"e_1_3_2_1_13_1","volume-title":"Bag of Tricks for Efficient Text Classification. CoRR abs\/1607.01759","author":"Joulin Armand","year":"2016","unstructured":"Armand Joulin , Edouard Grave , Piotr Bojanowski , and Tomas Mikolov . 2016. Bag of Tricks for Efficient Text Classification. CoRR abs\/1607.01759 ( 2016 ). arXiv:1607.01759 Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2016. Bag of Tricks for Efficient Text Classification. CoRR abs\/1607.01759 (2016). arXiv:1607.01759"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-45886-1_15"},{"key":"e_1_3_2_1_15_1","volume-title":"International Conference on Machine Learning. 1188--1196","author":"Le Quoc","year":"2014","unstructured":"Quoc Le and Tomas Mikolov . 2014 . Distributed representations of sentences and documents . In International Conference on Machine Learning. 1188--1196 . Quoc Le and Tomas Mikolov. 2014. Distributed representations of sentences and documents. In International Conference on Machine Learning. 1188--1196."},{"key":"e_1_3_2_1_16_1","volume-title":"Proceedings of the NAACL-HLT 2012 Workshop: Will We Ever Really Replace the N-gram Model? On the Future of Language Modeling for HLT. Association for Computational Linguistics, 1--10","author":"Son Hai Le","year":"2012","unstructured":"Hai Le Son , Alexandre Allauzen , and Fran\u00e7ois Yvon . 2012 . Measuring the influence of long range dependencies with neural network language models . In Proceedings of the NAACL-HLT 2012 Workshop: Will We Ever Really Replace the N-gram Model? On the Future of Language Modeling for HLT. Association for Computational Linguistics, 1--10 . Hai Le Son, Alexandre Allauzen, and Fran\u00e7ois Yvon. 2012. Measuring the influence of long range dependencies with neural network language models. In Proceedings of the NAACL-HLT 2012 Workshop: Will We Ever Really Replace the N-gram Model? On the Future of Language Modeling for HLT. Association for Computational Linguistics, 1--10."},{"key":"e_1_3_2_1_17_1","first-page":"448","article-title":"Learning with positive and unlabeled examples using weighted logistic regression","volume":"3","author":"Lee Wee Sun","year":"2003","unstructured":"Wee Sun Lee and Bing Liu . 2003 . Learning with positive and unlabeled examples using weighted logistic regression . In ICML , Vol. 3. 448 -- 455 . Wee Sun Lee and Bing Liu. 2003. Learning with positive and unlabeled examples using weighted logistic regression. In ICML, Vol. 3. 448--455.","journal-title":"ICML"},{"key":"e_1_3_2_1_18_1","first-page":"587","article-title":"Learning to classify texts using positive and unlabeled data","volume":"3","author":"Li Xiaoli","year":"2003","unstructured":"Xiaoli Li and Bing Liu . 2003 . Learning to classify texts using positive and unlabeled data . In IJCAI , Vol. 3. 587 -- 592 . Xiaoli Li and Bing Liu. 2003. Learning to classify texts using positive and unlabeled data. In IJCAI, Vol. 3. 587--592.","journal-title":"IJCAI"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/11564096_24"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883090"},{"key":"e_1_3_2_1_21_1","volume-title":"ICML","volume":"2","author":"Liu Bing","year":"2002","unstructured":"Bing Liu , Wee Sun Lee , Philip S Yu , and Xiaoli Li . 2002 . Partially supervised classification of text documents . In ICML , Vol. 2 . Citeseer, 387--394. Bing Liu, Wee Sun Lee, Philip S Yu, and Xiaoli Li. 2002. Partially supervised classification of text documents. In ICML, Vol. 2. Citeseer, 387--394."},{"key":"e_1_3_2_1_22_1","volume-title":"Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781","author":"Mikolov Tomas","year":"2013","unstructured":"Tomas Mikolov , Kai Chen , Greg Corrado , and Jeffrey Dean . 2013. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 ( 2013 ). Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)."},{"key":"e_1_3_2_1_23_1","unstructured":"Tomas Mikolov Ilya Sutskever Kai Chen Greg S Corrado and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems. 3111--3119.   Tomas Mikolov Ilya Sutskever Kai Chen Greg S Corrado and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems . 3111--3119."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Tomas Mikolov and Geoffrey Zweig. 2012. Context dependent recurrent neural network language model. (2012).  Tomas Mikolov and Geoffrey Zweig. 2012. Context dependent recurrent neural network language model. (2012).","DOI":"10.1109\/SLT.2012.6424228"},{"key":"e_1_3_2_1_25_1","volume-title":"A fast and simple algorithm for training neural probabilistic language models. arXiv preprint arXiv:1206.6426","author":"Mnih Andriy","year":"2012","unstructured":"Andriy Mnih and Yee Whye Teh . 2012. A fast and simple algorithm for training neural probabilistic language models. arXiv preprint arXiv:1206.6426 ( 2012 ). Andriy Mnih and Yee Whye Teh. 2012. A fast and simple algorithm for training neural probabilistic language models. arXiv preprint arXiv:1206.6426 (2012)."},{"key":"e_1_3_2_1_26_1","volume-title":"subgraph2vec: Learning distributed representations of rooted sub-graphs from large graphs. arXiv preprint arXiv:1606.08928","author":"Narayanan Annamalai","year":"2016","unstructured":"Annamalai Narayanan , Mahinthan Chandramohan , Lihui Chen , Yang Liu , and Santhoshkumar Saminathan . 2016. subgraph2vec: Learning distributed representations of rooted sub-graphs from large graphs. arXiv preprint arXiv:1606.08928 ( 2016 ). Annamalai Narayanan, Mahinthan Chandramohan, Lihui Chen, Yang Liu, and Santhoshkumar Saminathan. 2016. subgraph2vec: Learning distributed representations of rooted sub-graphs from large graphs. arXiv preprint arXiv:1606.08928 (2016)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2488388.2488475"},{"key":"e_1_3_2_1_28_1","volume-title":"Manning","author":"Pennington Jeffrey","year":"2014","unstructured":"Jeffrey Pennington , Richard Socher , and Christopher D . Manning . 2014 . GloVe: Global Vectors for Word Representation. In Empirical Methods in Natural Language Processing (EMNLP) . 1532--1543. http:\/\/www.aclweb.org\/anthology\/D14-1162 Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. GloVe: Global Vectors for Word Representation. In Empirical Methods in Natural Language Processing (EMNLP). 1532--1543. http:\/\/www.aclweb.org\/anthology\/D14-1162"},{"key":"e_1_3_2_1_29_1","unstructured":"Yafeng Ren Donghong Ji and Hongbin Zhang. 2014. Positive Unlabeled Learning for Deceptive Reviews Detection. In EMNLP. 488--498.  Yafeng Ren Donghong Ji and Hongbin Zhang. 2014. Positive Unlabeled Learning for Deceptive Reviews Detection. In EMNLP . 488--498."},{"key":"e_1_3_2_1_30_1","volume-title":"Int. Conf. on Machine Learning.","author":"Roy N","year":"2001","unstructured":"N Roy and A McCallum . 2001 . Toward optimal active learning through sampling estimation of error reduction . Int. Conf. on Machine Learning. N Roy and A McCallum. 2001. Toward optimal active learning through sampling estimation of error reduction. Int. Conf. on Machine Learning."},{"key":"e_1_3_2_1_31_1","volume-title":"Swivel: Improving embeddings by noticing what's missing. arXiv preprint arXiv:1602.02215","author":"Shazeer Noam","year":"2016","unstructured":"Noam Shazeer , Ryan Doherty , Colin Evans , and Chris Waterson . 2016 . Swivel: Improving embeddings by noticing what's missing. arXiv preprint arXiv:1602.02215 (2016). Noam Shazeer, Ryan Doherty, Colin Evans, and Chris Waterson. 2016. Swivel: Improving embeddings by noticing what's missing. arXiv preprint arXiv:1602.02215 (2016)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1162\/153244302760185243"},{"key":"e_1_3_2_1_33_1","volume-title":"Learning longer-term dependencies in rnns with auxiliary losses. arXiv preprint arXiv:1803.00144","author":"Trinh Trieu H","year":"2018","unstructured":"Trieu H Trinh , Andrew M Dai , Minh-Thang Luong , and Quoc V Le. 2018. Learning longer-term dependencies in rnns with auxiliary losses. arXiv preprint arXiv:1803.00144 ( 2018 ). Trieu H Trinh, Andrew M Dai, Minh-Thang Luong, and Quoc V Le. 2018. Learning longer-term dependencies in rnns with auxiliary losses. arXiv preprint arXiv:1803.00144 (2018)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959160"},{"key":"e_1_3_2_1_35_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008.   Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems . 5998--6008."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.06.004"},{"key":"e_1_3_2_1_37_1","volume-title":"Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. In International Conference on Learning Representations (ICLR).","author":"Yang Zhilin","year":"2018","unstructured":"Zhilin Yang , Zihang Dai , Ruslan Salakhutdinov , and William W Cohen . 2018 . Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. In International Conference on Learning Representations (ICLR). Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, and William W Cohen. 2018. Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143980"}],"event":{"name":"RecSys '19: Thirteenth ACM Conference on Recommender Systems","acronym":"RecSys '19","location":"Copenhagen Denmark"},"container-title":["Proceedings of the 13th ACM Conference on Recommender Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3298689.3347034","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3298689.3347034","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:12:55Z","timestamp":1750201975000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3298689.3347034"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,10]]},"references-count":38,"alternative-id":["10.1145\/3298689.3347034","10.1145\/3298689"],"URL":"https:\/\/doi.org\/10.1145\/3298689.3347034","relation":{},"subject":[],"published":{"date-parts":[[2019,9,10]]},"assertion":[{"value":"2019-09-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}