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Lifelong generative modeling [PDF]
Neurocomputing, 2020 Lifelong learning is the problem of learning multiple consecutive tasks in a sequential manner, where knowledge gained from previous tasks is retained and used to aid future learning over the lifetime of the learner. It is essential towards the development of intelligent machines that can adapt to their surroundings. In this work we focus on a lifelong
Jason Ramapuram +2 more
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Generalized Thirring Models [PDF]
Annals of Physics, 1996 LaTex 55 pages, 2 figures, extended version of our previous work (hep-th/9308067)
Sachs, I., Wipf, A.
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Generalized Additive Models [PDF]
Statistical Science, 1984 The classical linear regression model expresses the response vector Y as a function of the predictor variables \(X_ i\) through the model \(Y=\sum_{i}X_ i\beta_ i+e\), where the \(X_ i\) are observed, the \(\beta_ i\) are estimated by least squares or some other technique, e is the vector of errors.
Hastie, Trevor, Tibshirani, Robert
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IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models [PDF]
, 2017 This paper provides a unified account of two schools of thinking in information retrieval modelling: the generative retrieval focusing on predicting relevant documents given a query, and the discriminative retrieval focusing on predicting relevancy given
Gong, Yu +7 more
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Economic Theory, 2018 We extend the Luce model of discrete choice theory to satisfactorily handle zero-probability choices. The Luce model (or the Logit model) is the most widely applied and used model in stochastic choice, but it struggles to explain choices that are never made.
Echenique, Federico, Saito, Kota
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Generalized generalized spin models (four-weight spin models) [PDF]
Pacific Journal of Mathematics, 1995 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bannai, Eiichi, Bannai, Etsuko
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PHom-GeM: Persistent Homology for Generative Models [PDF]
, 2019 Generative neural network models, including Generative Adversarial Network (GAN) and Auto-Encoders (AE), are among the most popular neural network models to generate adversarial data.
Charlier, Jeremy +2 more
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Generalized dielectric breakdown model [PDF]
Physical Review B, 1999 Submitted to ...
R Cafiero +4 more
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Journal of the Royal Statistical Society. Series A (General), 1972 The technique of iterative weighted linear regression can be used to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation.
Nelder, J. A., Wedderburn, R. W. M.
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