references/{annexes,references}.bib : Fixed warnings

2025-06-25 16:34:15 +02:00
parent dbc3f60254
commit 15e0fec150
2 changed files with 71 additions and 68 deletions
--- a/references/annexes.bib
+++ b/references/annexes.bib
@ -40,7 +40,7 @@
 }
@online{wimmics_website,
  author = {Wimmics},
-  title  = {Wimmics – Bridging social semantics and formal semantics on the web},
+  title  = {Wimmics - Bridging social semantics and formal semantics on the web},
  url    = {https://team.inria.fr/wimmics}
 }
@online{tyrex_website,
@ -193,13 +193,13 @@
  url    = {https://www.i3s.unice.fr}
 }
@online{rdf2rdf_website,
-  title = {RDF2RDF’s official website},
+  title = {RDF2RDF's official website},
  url   = {http://www.l3s.de/~minack/rdf2rdf}
 }
@online{team_github,
  author = {Damien Graux and Pierre Saunders},
  year   = {2021},
-  title  = {Team’s GitHub},
+  title  = {Team's GitHub},
  url    = {https://github.com/SemanticWebBenchmarker}
 }
@manual{unix_standard,
@ -207,20 +207,20 @@
  url   = {https://www.opengroup.org/membership/forums/platform/unix}
 }
@online{virtuoso_website,
-  title = {Virtuoso’s official website},
+  title = {Virtuoso's official website},
  url   = {https://virtuoso.openlinksw.com}
 }
@online{dbpedia_website,
-  title = {Dbpedia’s official website},
+  title = {Dbpedia's official website},
  url   = {https://www.dbpedia.org}
 }
@online{lod-cloud_website,
-  title = {The Linked Open Data Cloud’s official website},
+  title = {The Linked Open Data Cloud's official website},
  url   = {https://www.lod-cloud.net}
 }
@online{fuseki_website,
  author = {Apache},
-  title  = {Apache Jena Fueski’s official website},
+  title  = {Apache Jena Fueski's official website},
  url    = {https://jena.apache.org/documentation/fuseki2}
 }
@manual{sparql_standard,
@ -229,11 +229,11 @@
 }
@online{tdb2_website,
  author = {Apache},
-  title  = {TDB2’s official website},
+  title  = {TDB2's official website},
  url    = {https://jena.apache.org/documentation/tdb2}
 }
@online{watdiv_website,
-  title = {WatDiv’s official website},
+  title = {WatDiv's official website},
  url   = {https://dsg.uwaterloo.ca/watdiv}
 }
@online{sp2bench_website,
@ -282,7 +282,7 @@
  url   = {https://github.com/SemanticWebBenchmarker/4store}
 }
@online{wikipedia_cayley_dickson,
-  title = {Cayley–Dickson construction},
+  title = {Cayley-Dickson construction},
  url   = {https://en.wikipedia.org/wiki/Cayley-Dickson\_construction}
 }
@online{wikipedia_complex_number,
--- a/references/references.bib
+++ b/references/references.bib
@ -7,7 +7,7 @@
  address   = {Red Hook, NY, USA},
  abstract  = {Generative Adversarial Networks (GANs) are powerful generative models, but suffer from training instability. The recently proposed Wasserstein GAN (WGAN) makes progress toward stable training of GANs, but sometimes can still generate only poor samples or fail to converge. We find that these problems are often due to the use of weight clipping in WGAN to enforce a Lipschitz constraint on the critic, which can lead to undesired behavior. We propose an alternative to clipping weights: penalize the norm of gradient of the critic with respect to its input. Our proposed method performs better than standard WGAN and enables stable training of a wide variety of GAN architectures with almost no hyperparameter tuning, including 101-layer ResNets and language models with continuous generators. We also achieve high quality generations on CIFAR-10 and LSUN bedrooms.},
  booktitle = {Proceedings of the 31st International Conference on Neural Information Processing Systems},
-  pages     = {5769–5779},
+  pages     = {5769-5779},
  numpages  = {11},
  location  = {Long Beach, California, USA},
  series    = {NIPS'17},
@ -33,7 +33,8 @@
  year      = {1983},
  volume    = {269},
  pages     = {543-547},
-  booktitle = {Doklady ANSSSR (translated as Soviet.Math.Docl.)}
+  booktitle = {Doklady ANSSSR (translated as Soviet.Math.Docl.)},
+  journal   = {Dokl Akad Nauk SSSR}
 }
@article{adagrad_paper,
  author  = {John Duchi and Elad Hazan and Yoram Singer},
@ -117,7 +118,7 @@ we aim to support the design and implementation of more diverse benchmarks. Appl
 developers can use our result to analyze their data and queries and choose a data
 management system.},
  booktitle = {The World Wide Web Conference},
-  pages     = {1623–1633},
+  pages     = {1623-1633},
  numpages  = {11},
  location  = {San Francisco, CA, USA},
  series    = {WWW '19}
@ -160,7 +161,7 @@ benchmark queries that include pattern matching and long join paths in the under
 data graphs.},
  journal    = {Proc. VLDB Endow.},
  month      = aug,
-  pages      = {647–659},
+  pages      = {647-659},
  numpages   = {13}
 }
@article{lubm_article,
@ -252,7 +253,7 @@ the desired benchmark datasets. To our knowledge, this is the first methodologic
 study of RDF benchmarks, as well as the first attempt on generating RDF benchmarks
 in a principled way.},
  booktitle = {Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data},
-  pages     = {145–156},
+  pages     = {145-156},
  numpages  = {12},
  keywords  = {RDF, benchmark},
  location  = {Athens, Greece},
@ -298,33 +299,34 @@ in a principled way.},
  bibsource  = {dblp computer science bibliography, https://dblp.org}
 }
@article{transfer_learning_survey,
-  author    = {Fuzhen Zhuang and
-               Zhiyuan Qi and
-               Keyu Duan and
-               Dongbo Xi and
-               Yongchun Zhu and
-               Hengshu Zhu and
-               Hui Xiong and
-               Qing He},
-  title     = {A Comprehensive Survey on Transfer Learning},
-  journal   = {CoRR},
-  volume    = {abs/1911.02685},
-  year      = {2019},
-  url       = {http://arxiv.org/abs/1911.02685},
+  author     = {Fuzhen Zhuang and
+                Zhiyuan Qi and
+                Keyu Duan and
+                Dongbo Xi and
+                Yongchun Zhu and
+                Hengshu Zhu and
+                Hui Xiong and
+                Qing He},
+  title      = {A Comprehensive Survey on Transfer Learning},
+  journal    = {CoRR},
+  volume     = {abs/1911.02685},
+  year       = {2019},
+  url        = {http://arxiv.org/abs/1911.02685},
  eprinttype = {arXiv},
-  eprint    = {1911.02685},
-  timestamp = {Sat, 29 Aug 2020 18:19:14 +0200},
-  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-02685.bib},
-  bibsource = {dblp computer science bibliography, https://dblp.org}
+  eprint     = {1911.02685},
+  timestamp  = {Sat, 29 Aug 2020 18:19:14 +0200},
+  biburl     = {https://dblp.org/rec/journals/corr/abs-1911-02685.bib},
+  bibsource  = {dblp computer science bibliography, https://dblp.org}
 }
@article{generative_adversarial_nets,
-  doi = {10.48550/ARXIV.1406.2661},
-  url = {https://arxiv.org/abs/1406.2661},
-  author = {Goodfellow, Ian J. and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
-  keywords = {Machine Learning (stat.ML), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
-  title = {Generative Adversarial Networks},
+  doi       = {10.48550/ARXIV.1406.2661},
+  url       = {https://arxiv.org/abs/1406.2661},
+  author    = {Goodfellow, Ian J. and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
+  keywords  = {Machine Learning (stat.ML), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  title     = {Generative Adversarial Networks},
  publisher = {arXiv},
-  year = {2014},
+  journal   = {arXiv},
+  year      = {2014},
  copyright = {arXiv.org perpetual, non-exclusive license}
 }
@article{vae_paper,
@ -338,22 +340,22 @@ in a principled way.},
  copyright = {arXiv.org perpetual, non-exclusive license}
 }
@article{edit_gan_paper,
-  author    = {Huan Ling and
-               Karsten Kreis and
-               Daiqing Li and
-               Seung Wook Kim and
-               Antonio Torralba and
-               Sanja Fidler},
-  title     = {EditGAN: High-Precision Semantic Image Editing},
-  journal   = {CoRR},
-  volume    = {abs/2111.03186},
-  year      = {2021},
-  url       = {https://arxiv.org/abs/2111.03186},
+  author     = {Huan Ling and
+                Karsten Kreis and
+                Daiqing Li and
+                Seung Wook Kim and
+                Antonio Torralba and
+                Sanja Fidler},
+  title      = {EditGAN: High-Precision Semantic Image Editing},
+  journal    = {CoRR},
+  volume     = {abs/2111.03186},
+  year       = {2021},
+  url        = {https://arxiv.org/abs/2111.03186},
  eprinttype = {arXiv},
-  eprint    = {2111.03186},
-  timestamp = {Wed, 10 Nov 2021 16:07:30 +0100},
-  biburl    = {https://dblp.org/rec/journals/corr/abs-2111-03186.bib},
-  bibsource = {dblp computer science bibliography, https://dblp.org}
+  eprint     = {2111.03186},
+  timestamp  = {Wed, 10 Nov 2021 16:07:30 +0100},
+  biburl     = {https://dblp.org/rec/journals/corr/abs-2111-03186.bib},
+  bibsource  = {dblp computer science bibliography, https://dblp.org}
 }
@misc{dall_e_2_paper,
  doi       = {10.48550/ARXIV.2204.06125},
@ -399,26 +401,26 @@ in a principled way.},
  address   = {Cambridge, MA, USA},
  abstract  = {The Bayesian analysis of neural networks is difficult because a simple prior over weights implies a complex prior distribution over functions. In this paper we investigate the use of Gaussian process priors over functions, which permit the predictive Bayesian analysis for fixed values of hyperparameters to be carried out exactly using matrix operations. Two methods, using optimization and averaging (via Hybrid Monte Carlo) over hyperparameters have been tested on a number of challenging problems and have produced excellent results.},
  booktitle = {Proceedings of the 8th International Conference on Neural Information Processing Systems},
-  pages     = {514–520},
+  pages     = {514-520},
  numpages  = {7},
  location  = {Denver, Colorado},
  series    = {NIPS'95}
 }
@article{semi-supervised_learning_with_deep_generative_models,
-  author    = {Diederik P. Kingma and
-               Danilo Jimenez Rezende and
-               Shakir Mohamed and
-               Max Welling},
-  title     = {Semi-Supervised Learning with Deep Generative Models},
-  journal   = {CoRR},
-  volume    = {abs/1406.5298},
-  year      = {2014},
-  url       = {http://arxiv.org/abs/1406.5298},
+  author     = {Diederik P. Kingma and
+                Danilo Jimenez Rezende and
+                Shakir Mohamed and
+                Max Welling},
+  title      = {Semi-Supervised Learning with Deep Generative Models},
+  journal    = {CoRR},
+  volume     = {abs/1406.5298},
+  year       = {2014},
+  url        = {http://arxiv.org/abs/1406.5298},
  eprinttype = {arXiv},
-  eprint    = {1406.5298},
-  timestamp = {Mon, 13 Aug 2018 16:47:38 +0200},
-  biburl    = {https://dblp.org/rec/journals/corr/KingmaRMW14.bib},
-  bibsource = {dblp computer science bibliography, https://dblp.org}
+  eprint     = {1406.5298},
+  timestamp  = {Mon, 13 Aug 2018 16:47:38 +0200},
+  biburl     = {https://dblp.org/rec/journals/corr/KingmaRMW14.bib},
+  bibsource  = {dblp computer science bibliography, https://dblp.org}
 }
@article{every_model_learned_by_gradient_descent_is_approximately_a_kernel_machine,
  author     = {Pedro Domingos},
@ -467,5 +469,6 @@ in a principled way.},
  author    = {Edward Jewitt Wheeler},
  page      = {564},
  volumes   = {49},
-  year      = {1910}
+  year      = {1910},
+  publisher = {New York : Current Literature Pub. Co.}
 }