Ticket #993: rmf.bib

File rmf.bib, 6.4 KB (added by zenogantner, 3 years ago)

example bibtex file

Line 
1@inproceedings{koren:icdm08,
2    author = {Yifan Hu and Yehuda Koren and Chris Volinsky},
3    title = {Collaborative Filtering for Implicit Feedback Datasets},
4    booktitle = {IEEE International Conference on Data Mining (ICDM 2008)},
5    year = {2008},
6    pages = {263-272}
7}
8
9@inproceedings{pan:icdm08,
10  author    = {Rong Pan and
11               Yunhong Zhou and
12               Bin Cao and
13               Nathan Nan Liu and
14               Rajan M. Lukose and
15               Martin Scholz and
16               Qiang Yang},
17  title     = {One-Class Collaborative Filtering},
18  booktitle = {IEEE International Conference on Data Mining (ICDM 2008)},
19  year      = {2008},
20  pages     = {502-511}
21}
22
23@article{weimer:ml08,
24    abstract = {Abstract\ \ Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful learning approach to this task and has been recently extended to structured ranking losses. In this paper we discuss a number of extensions to MMMF by introducing offset terms, item dependent regularization and a graph kernel on the recommender graph. We show equivalence between graph kernels and the recent MMMF extensions by Mnih and Salakhutdinov (Advances in Neural Information Processing Systems\ 20, 2008). Experimental evaluation of the introduced extensions show improved performance over the original MMMF formulation.},
25    author = {Markus Weimer and Alexandros Karatzoglou and Alex Smola },
26    citeulike-article-id = {3140972},
27    journal = {Machine Learning},
28    number = {3},
29    pages = {263--276},
30    posted-at = {2008-08-20 17:26:44},
31    priority = {2},
32    title = {Improving maximum margin matrix factorization},
33    volume = {72},
34    year = {2008}
35}
36
37@INPROCEEDINGS{marlin:nips03,
38  author = " Benjamin Marlin",
39  title = " Modeling User Rating Profiles For Collaborative Filtering",
40  booktitle = "Advances in Neural Information Processing Systems 16",
41  editor = "Sebastian Thrun and Lawrence Saul and Bernhard {Sch\"{o}lkopf}",
42  publisher = "MIT Press",
43  address = "Cambridge, MA",
44  year = "2004",
45  keywords = "latent variable models, mixture models, generative models, machine learning, collaborative filtering",
46}
47
48@inproceedings{Huang:nips07,
49 title = {Efficient Inference for Distributions on Permutations},
50 author = {Jonathan Huang and Carlos Guestrin and Leonidas Guibas},
51 booktitle = {Advances in Neural Information Processing Systems 20},
52 editor = {J.C. Platt and D. Koller and Y. Singer and S. Roweis},
53 publisher = {MIT Press},
54 address = {Cambridge, MA},
55 pages = {697--704},
56 year = {2008}
57}
58
59
60@ARTICLE{desphande:is04,
61AUTHOR    = "M. Deshpande and G. Karypis",
62TITLE     = "Item-based top-N recommendation algorithms.",
63JOURNAL   = "ACM Transactions on Information Systems. Springer-Verlag",
64PAGE      = "143--177",
65VOLUME  = "22/1",
66YEAR      = "2004",
67}
68
69@misc{citeulike:1031420,
70    author = {Srebro, N.  and Jaakkola, T. },
71    citeulike-article-id = {1031420},
72    posted-at = {2007-12-18 01:34:48},
73    priority = {2},
74    title = {Weighted low rank approximation},
75    url = {http://citeseer.ist.psu.edu/srebro03weighted.html},
76    year = {2003}
77}
78
79@inproceedings{rennie:icml05,
80 author = {Jasson D. M. Rennie and Nathan Srebro},
81 title = {Fast maximum margin matrix factorization for collaborative prediction},
82 booktitle = {ICML '05: Proceedings of the 22nd international conference on Machine learning},
83 year = {2005},
84 isbn = {1-59593-180-5},
85 pages = {713--719},
86 location = {Bonn, Germany},
87 doi = {http://doi.acm.org/10.1145/1102351.1102441},
88 publisher = {ACM},
89 address = {New York, NY, USA},
90 }
91
92@inproceedings{koren:kdd08,
93 author = {Yehuda Koren},
94 title = {Factorization meets the neighborhood: a multifaceted collaborative filtering model},
95 booktitle = {KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining},
96 year = {2008},
97 isbn = {978-1-60558-193-4},
98 pages = {426--434},
99 location = {Las Vegas, Nevada, USA},
100 doi = {http://doi.acm.org/10.1145/1401890.1401944},
101 publisher = {ACM},
102 address = {New York, NY, USA},
103}
104
105@Inproceedings{rendle:rs08,
106    author = {Steffen Rendle and Lars Schmidt-Thieme},
107    title = {Online-Updating Regularized Kernel Matrix Factorization Models for Large-Scale Recommender Systems},
108    year = {2008},
109    booktitle = {RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems},
110    publisher = {ACM},
111}
112
113
114
115@inproceedings{herschtal:icml04,
116 author = {Alan Herschtal and Bhavani Raskutti},
117 title = {Optimising area under the ROC curve using gradient descent},
118 booktitle = {ICML '04: Proceedings of the twenty-first international conference on Machine learning},
119 year = {2004},
120 isbn = {1-58113-828-5},
121 pages = {49},
122 location = {Banff, Alberta, Canada},
123 doi = {http://doi.acm.org/10.1145/1015330.1015366},
124 publisher = {ACM},
125 address = {New York, NY, USA},
126 }
127
128 
129   @inproceedings{sarwar02incrementalsvd,
130title = {Incremental Singular Value Decomposition Algorithms for Highly Scalable Recommender Systems},
131author = {Badrul Sarwar and George Karypis and Joseph Konstan and John Riedl},
132booktitle = {Proceedings of the 5th International Conference in Computers and Information Technology},
133url = {citeseer.ist.psu.edu/663385.html},
134year = {2002},
135keywords = {incremental recommendation scalability svd }
136}
137
138@article{hofmann04,
139 author = {Thomas Hofmann},
140 title = {Latent semantic models for collaborative filtering},
141 journal = {ACM Trans. Inf. Syst.},
142 volume = {22},
143 number = {1},
144 year = {2004},
145 issn = {1046-8188},
146 pages = {89--115},
147 doi = {http://doi.acm.org/10.1145/963770.963774},
148 publisher = {ACM},
149 address = {New York, NY, USA},
150 }
151
152@InProceedings{KonHowJeb07,
153    author = "Kondor, R. and Howard, A. and Jebara, T.",
154    title = "Multi-object tracking with representations of the symmetric group",
155    Booktitle = {Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, San Juan, Puerto Rico},
156    Month = {March},
157    Year = {2007}
158}
159
160@inproceedings{Burges:2005aa,
161    address = {New York, NY, USA},
162    author = {Burges, Chris   and Shaked, Tal   and Renshaw, Erin   and Lazier, Ari   and Deeds, Matt   and Hamilton, Nicole   and Hullender, Greg  },
163    booktitle = {ICML '05: Proceedings of the 22nd international conference on Machine learning},
164    keywords = {ranknet},
165    pages = {89--96},
166    priority = {0},
167    publisher = {ACM Press},
168    title = {Learning to rank using gradient descent},
169    year = {2005}
170}
171