Approximate inference in continuous determinantal processes, Adv. NIPS, 2013. ,
Learning the parameters of determinantal point process kernels, Proc. ICML, 2014. ,
Mining text data, 2012. ,
Topic Significance Ranking of LDA Generative Models, Proc. ECML, 2009. ,
DOI : 10.1145/1150402.1150450
Spherical Harmonics and Approximations on the Unit Sphere: an Introduction, 2012. ,
DOI : 10.1007/978-3-642-25983-8
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n), Adv. NIPS, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00831977
Inference for determinantal point processes without spectral knowledge, Adv. NIPS, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01245315
Diverse M-Best Solutions in Markov Random Fields, Proc. ECCV, 2012. ,
DOI : 10.1007/978-3-642-33715-4_1
Topic-based vector space model, Proc. ICBIS, 2003. ,
Natural language processing with Python, 2009. ,
Pattern Recognition and Machine Learning, 2006. ,
Dynamic topic models, Proceedings of the 23rd international conference on Machine learning , ICML '06, 2006. ,
DOI : 10.1145/1143844.1143859
A correlated topic model of Science. The Annals of Applied Statistics, pp.17-35, 2007. ,
Latent Dirichlet allocation, Journal of Machine Learning Research, vol.3, pp.993-1022, 2003. ,
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies, Journal of the ACM, vol.57, issue.2, p.7, 2010. ,
DOI : 10.1145/1667053.1667056
Question answering with subgraph embeddings . arXiv preprint, 2014. ,
DOI : 10.3115/v1/d14-1067
URL : http://arxiv.org/pdf/1406.3676
Eynard???Mehta Theorem, Schur Process, and their Pfaffian Analogs, Journal of Statistical Physics, vol.46, issue.3, pp.291-317, 2005. ,
DOI : 10.5802/aif.1526
URL : http://arxiv.org/pdf/math-ph/0409059v2.pdf
Online learning and stochastic approximations. On-line learning in neural networks, 1998. ,
Class-based n-gram models of natural language, Computational linguistics, vol.18, issue.4, pp.467-479, 1992. ,
Maximum likelihood estimation of determinantal point processes, 2017. ,
Discrete principal component analysis, Proc. of the Subspace, Latent Structure and Feature Selection Techniques: Statistical and Optimisation perspectives Workshop, 2005. ,
On-line expectation-maximization algorithm for latent data models, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.11, issue.3, pp.593-613, 2009. ,
DOI : 10.1007/978-1-4684-0192-9
Statistical Inference., Biometrics, vol.49, issue.1, 2002. ,
DOI : 10.2307/2532634
Explaining the Gibbs sampler. The American Statistician, pp.167-174, 1992. ,
Reading tea leaves: How humans interpret topic models, 2009. ,
Decentralized topic modelling with latent Dirichlet allocation . arXiv preprint, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01383111
Indexing by latent semantic analysis, Journal of the American Society for Information Science, vol.41, issue.6, 1990. ,
DOI : 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9
URL : http://www.cs.bham.ac.uk/~pxt/IDA/lsa_ind.pdf
Convergence of a stochastic approximation version of the EM algorithm. The Annals of Statistics, pp.94-128, 1999. ,
Maximum likelihood from incomplete data via the EM algorithm, Journal of the royal statistical society. Series B (methodological ), vol.39, issue.1, pp.1-38, 1977. ,
Predicting Multiple Structured Visual Interpretations, 2015 IEEE International Conference on Computer Vision (ICCV), pp.2947-2955, 2015. ,
DOI : 10.1109/ICCV.2015.337
Generalized nonnegative matrix approximations with Bregman divergences, Adv. NIPS, 2005. ,
Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS), Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '14, 2014. ,
DOI : 10.1145/2623330.2623758
From MAP to marginals: Variational inference in Bayesian submodular models, Adv. NIPS, 2014. ,
Variational inference in mixed probabilistic submodular models, Adv. NIPS, 2016. ,
Latent semantic indexing (LSI), The Second Text REtrieval Conference, 1994. ,
The approximation of one matrix by another of lower rank, Psychometrika, vol.1, issue.3, pp.211-218, 1936. ,
DOI : 10.1007/BF02288367
The generalized A* architecture, Journal of Artificial Intelligence Research, vol.29, pp.153-190, 2007. ,
Latent topic networks: A versatile probabilistic programming framework for topic models, Proc. ICML, 2015. ,
Streaming Gibbs sampling for LDA model, 2016. ,
Low-rank factorization of determinantal point processes for recommendation, 2016. ,
Discovering diverse and salient threads in document collections, Proc. EMNLP, 2012. ,
Near-optimal MAP inference for determinantal point processes, Adv. NIPS, 2012. ,
Expectation-maximization for learning determinantal point processes, Adv. NIPS, 2014. ,
A probabilistic approach to semantic representation, Proc. CogSci, 2002. ,
Finding scientific topics, Proceedings of the National Academy of Sciences, vol.88, issue.11, pp.5228-5235, 2004. ,
DOI : 10.1073/pnas.88.11.4874
URL : http://www.pnas.org/content/101/suppl_1/5228.full.pdf
Structured low-rank matrix factorization: Optimality, algorithm, and applications to image processing, Proc. ICML, 2014. ,
Monte Carlo sampling methods using Markov chains and their applications, Biometrika, vol.57, issue.1, pp.97-109, 1970. ,
DOI : 10.1093/biomet/57.1.97
A probabilistic justification for using tf???idf term weighting in information retrieval, International Journal on Digital Libraries, vol.3, issue.2, pp.131-139, 2000. ,
DOI : 10.1007/s007999900025
Structured stochastic variational inference, Proc. AISTATS, 2015. ,
Online learning for latent Dirichlet allocation, 2010. ,
Stochastic variational inference, Journal of Machine Learning Research, vol.14, issue.1, pp.1303-1347, 2013. ,
Probabilistic latent semantic analysis, Proc. UAI, 1999. ,
Probabilistic latent semantic indexing, Proc. ACM SIGIR, 1999. ,
DOI : 10.1145/3130348.3130370
URL : http://www-connex.lip6.fr/~amini/././RelatedWorks/Hof99.pdf
Supervised word mover's distance, Adv. NIPS, 2016. ,
Independent component analysis, 2004. ,
Interpolated estimation of Markov source parameters from sparse data, Proc. Workshop on Pattern Recognition in Practice, 1980. ,
Aspect and sentiment unification model for online review analysis, Proceedings of the fourth ACM international conference on Web search and data mining, WSDM '11, 2011. ,
DOI : 10.1145/1935826.1935932
URL : http://uilab.kaist.ac.kr/research/WSDM11/wsdm400-jo.pdf
Fast determinantal point process sampling with application to clustering, Adv. NIPS, 2013. ,
On Particle Methods for Parameter Estimation in State-Space Models, Statistical Science, vol.30, issue.3, pp.328-351, 2015. ,
DOI : 10.1214/14-STS511
Estimation of probabilities from sparse data for the language model component of a speech recognizer, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.35, issue.3, pp.400-401, 1987. ,
DOI : 10.1109/TASSP.1987.1165125
Inferring M-Best Diverse Labelings in a Single One, 2015 IEEE International Conference on Computer Vision (ICCV), 2015. ,
DOI : 10.1109/ICCV.2015.211
Improved backing-off for M-gram language modeling, 1995 International Conference on Acoustics, Speech, and Signal Processing, 1995. ,
DOI : 10.1109/ICASSP.1995.479394
Probabilistic graphical models: principles and techniques, 2009. ,
Matrix Factorization Techniques for Recommender Systems, Computer, vol.42, issue.8, pp.30-37, 2009. ,
DOI : 10.1109/MC.2009.263
URL : http://research.yahoo.com/files/ieeecomputer.pdf
Submodular function maximization. Tractability: Practical Approaches to Hard Problems, p.8, 2012. ,
DOI : 10.1017/cbo9781139177801.004
URL : http://www.cs.cmu.edu/%7Edgolovin/papers/submodular_survey12.pdf
k-DPPs: Fixed-size determinantal point processes, Proc. ICML, 2011. ,
Determinantal Point Processes for Machine Learning, Machine Learning, pp.123-286, 2012. ,
DOI : 10.1561/2200000044
Stochastic approximation and recursive algorithms and applications, 2003. ,
From word embeddings to document distances, Proc. ICML, 2015. ,
Machine reading tea leaves: Automatically evaluating topic coherence and topic model quality, EACL, 2014. ,
DOI : 10.3115/v1/e14-1056
Determinantal point process models and statistical inference, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.4, issue.4, pp.853-877, 2015. ,
DOI : 10.1007/978-1-4612-4628-2
URL : https://hal.archives-ouvertes.fr/hal-01241077
Learning the parts of objects by non-negative matrix factorization, Nature, vol.401, issue.6755, pp.788-791, 1999. ,
Theory of point estimation, 1998. ,
SNAP Datasets: Stanford large network dataset collection, 2014. ,
Nonsmooth optimization via quasi-Newton methods, Mathematical Programming, pp.135-163, 2013. ,
DOI : 10.1175/1520-0493(2000)129<4031:UODANO>2.0.CO;2
URL : http://www.cs.nyu.edu/faculty/overton/papers/pdffiles/nsoquasi.pdf
Efficient sampling for k-determinantal point processes, Proc. AISTATS, 2016. ,
Fast DPP sampling for Nystrom with application to kernel methods, Proc. ICML, 2016. ,
Online EM for unsupervised models, Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics on, NAACL '09, 2009. ,
DOI : 10.3115/1620754.1620843
URL : http://www.cs.berkeley.edu/~pliang/papers/online-naacl2009.pdf
UCI machine learning repository, 2013. URL http ,
Joint sentiment/topic model for sentiment analysis, Proceeding of the 18th ACM conference on Information and knowledge management, CIKM '09, 2009. ,
DOI : 10.1145/1645953.1646003
Ratings meet reviews, a combined approach to recommend, Proceedings of the 8th ACM Conference on Recommender systems, RecSys '14, 2014. ,
DOI : 10.1145/2645710.2645728
Fixed-point algorithms for learning determinantal point processes, Proc. ICML, 2015. ,
Kronecker determinantal point processes. arXiv preprint, 2016. ,
Hidden factors and hidden topics, Proceedings of the 7th ACM conference on Recommender systems, RecSys '13, 2013. ,
DOI : 10.1145/2507157.2507163
Supervised topic models, Adv. NIPS, 2008. ,
Topic sentiment mixture, Proceedings of the 16th international conference on World Wide Web , WWW '07, 2007. ,
DOI : 10.1145/1242572.1242596
Equation of State Calculations by Fast Computing Machines, The Journal of Chemical Physics, vol.21, issue.6, pp.1087-1092, 1953. ,
DOI : 10.1063/1.1700747
Efficient estimation of word representations in vector space, 2013. ,
Distributed representations of words and phrases and their compositionality, Adv. NIPS, 2013. ,
Optimizing semantic coherence in topic models, Proc. EMNLP, 2011. ,
Sparse stochastic inference for latent Dirichlet allocation, Proc. ICML, 2012. ,
Estimating a Dirichlet distribution, 2000. ,
The theory of digital handling of non-numerical information and its implications to machine economics, Proc. ACM at Rutgers University, 1950. ,
Machine learning: a probabilistic perspective, 2012. ,
A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants, Learning in graphical models, pp.355-368, 1998. ,
DOI : 10.1007/978-94-011-5014-9_12
Automatic evaluation of topic coherence, NAACL HLT, 2010. ,
Improving topic coherence with regularized topic models, Adv. NIPS, 2011. ,
Using maximum entropy for text classification, IJCAI-99 workshop on machine learning for information filtering, 1999. ,
Text classification from labeled and unlabeled documents using EM, Machine Learning, vol.39, issue.2/3, pp.103-134, 2000. ,
DOI : 10.1023/A:1007692713085
Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values, Environmetrics, vol.18, issue.2, pp.111-126, 1994. ,
DOI : 10.1007/978-3-642-93295-3_112
Nested Hierarchical Dirichlet Processes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.37, issue.2, 2014. ,
DOI : 10.1109/TPAMI.2014.2318728
URL : http://arxiv.org/pdf/1210.6738
Bayesian nonparametrics for sparse dynamic networks, 2016. ,
Stochastic gradient Riemannian Langevin dynamics on the probability simplex, Adv. NIPS, 2013. ,
Factorial LDA: Sparse multi-dimensional text models, Adv. NIPS, 2012. ,
Distributional clustering of English words, Proceedings of the 31st annual meeting on Association for Computational Linguistics -, 1993. ,
DOI : 10.3115/981574.981598
Rethinking LDA: moment matching for discrete ICA, Adv. NIPS, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01225271
Acceleration of Stochastic Approximation by Averaging, SIAM Journal on Control and Optimization, vol.30, issue.4, pp.838-855, 1992. ,
DOI : 10.1137/0330046
Improving multi-class text classification with naive Bayes, 2001. ,
Introduction to Recommender Systems Handbook, 2011. ,
DOI : 10.1007/978-0-387-85820-3_1
Exploring the Space of Topic Coherence Measures, Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, WSDM '15, 2015. ,
DOI : 10.1093/analys/59.4.338
Online maximum-likelihood estimation for latent factor models, 2011 IEEE Statistical Signal Processing Workshop (SSP), 2011. ,
DOI : 10.1109/SSP.2011.5967760
A vector space model for automatic indexing, Communications of the ACM, vol.18, issue.11, pp.613-620, 1975. ,
DOI : 10.1145/361219.361220
URL : http://ecommons.cornell.edu/bitstream/1813/6057/1/74-218.pdf
Deterministic single-pass algorithm for LDA, Adv. NIPS, 2010. ,
Learning with kernels: support vector machines, regularization , optimization, and beyond, 2001. ,
Kernel methods for pattern analysis, 2004. ,
DOI : 10.1017/CBO9780511809682
Hierarchical Dirichlet Processes, Journal of the American Statistical Association, vol.101, issue.476, pp.1566-1581, 2006. ,
DOI : 10.1198/016214506000000302
URL : http://www.cs.princeton.edu/~blei/papers/TehJordanBealBlei2006.pdf
Modeling online reviews with multi-grain topic models, Proceeding of the 17th international conference on World Wide Web , WWW '08, 2008. ,
DOI : 10.1145/1367497.1367513
URL : http://cui.unige.ch/~titov/papers/www08.pdf
Recursive parameter estimation using incomplete data, Journal of the Royal Statistical Society. Series B (Methodological), vol.46, issue.2, pp.257-267, 1984. ,
DOI : 10.21236/ADA116190
Learning determinantal point processes with moments and cycles. arXiv preprint, 2017. ,
Asymptotic Statistics, 2000. ,
Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001. ,
DOI : 10.1109/CVPR.2001.990517
Topic modeling, Proceedings of the 23rd international conference on Machine learning , ICML '06, 2006. ,
DOI : 10.1145/1143844.1143967
Evaluation methods for topic models, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009. ,
DOI : 10.1145/1553374.1553515
URL : http://www.cs.umass.edu/~wallach/publications/wallach09evaluation.pdf
Truncation-free online variational inference for Bayesian nonparametric models, Adv. NIPS, 2012. ,
Continuous time dynamic topic models. arXiv preprint, 2012. ,
A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms, Journal of the American Statistical Association, vol.51, issue.411, pp.699-704, 1990. ,
DOI : 10.1214/aos/1176346060
Parallel inference for latent Dirichlet allocation on graphics processing units, Adv. NIPS, 2009. ,
SAME but Different, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '15, 2014. ,
DOI : 10.1145/2623330.2623756
Bilingual word embeddings for phrase-based machine translation, Proc. EMNLP, 2013. ,