Bilinear Models (BL)
A Study of Bilinear Models in Voice Conversion
... The bilinear models represent a factor analysis technique introduced originally in [10] which attempts to model observations as a result of two underlying ...that bilinear models are a viable ...
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Designs of Minimal-Order State Observer and Servo Controller for a Robot Arm Using Piecewise Bilinear Models
... This paper has proposed a servo control system based on a minimal-order state observer for nonlinear systems approximated by piecewise bilinear (PB) models. The design method is capable of designing the ...
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Learning to Negate Adjectives with Bilinear Models
... We learn a mapping that negates adjectives by predicting an adjective’s antonym in an arbitrary word embedding model. We show that both linear models and neural networks improve on this task when they have access ...
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The time-profile of cell growth in fission yeast: model selection criteria favoring bilinear models over exponential ones
... a bilinear pattern might be caused by effects of the cell cycle itself causing a relatively sudden rate-increase at an RCP (or more than one ...A bilinear model seemed most adequate to describe the increase ...
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Feature Rich Networks for Knowledge Base Completion
... When textual relation mentions are added, we observe that our proposed model increases its per- formance score about 3 points in MRR and 4.5 in hits@10 compared to the best model that does not include text. Contrary to ...
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Bilinear identification of a binary distillation column
... This appendix contains the identified models for the experimental column work described in Chapter 8, using the input function shown in Graph 8 .1... 4th order diagonal bilinear models, [r] ...
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Nonlinearity Tests For Bilinear Time Series Data
... for bilinear models do not give an outright decision of rejecting or accepting the null hypothesis of linearity since the percentages of acceptance is not less than ...the bilinear coefficients get ...
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Unsupervised Learning of Sentence Embeddings Using Compositional n Gram Features
... plex models, such as recurrent neural networks (RNNs), LSTMs, attention models and even Neu- ral Turing Machine ...such models much slower to train on larger ...“shallow” models such as matrix ...
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Explicit equilibria in bilinear kinetic models for socio-economic interactions
... of bilinear models of type ...a bilinear kinetic model of Boltzmann type, based on dissipative binary collisions (41) with √ p + √ q = 1 and p, q ∈ (0, ...
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Necessary Conditions for Isolation of Special Classes of Bilinear Autoregressive Moving Average Vector (BARMAV) Models
... Abstract: Bilinear Autoregressive Moving Average Vector (BARMAV) Models are models aggregated with the linear and non-linear vector components of autoregressive and moving average ...BARMAV ...
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Differential Networks for Visual Question Answering
... attention models focusing on fusion can be di- vided into two categories, linear models and bilinear ...linear models are adopted to fuse image and ques- tion feature ...Recently, ...
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Volatility of Internally Generated Revenue and Effects of Its Major Components: A Case of Akwa Ibom State, Nigeria
... and Bilinear models have been adopted in the investigations of volatility of exchange rate of Naira/USD, Naira/BP and Naira/Euro returns, Nigerian Stock Market Returns Volatility, Naira-US dollar and ...
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Self-bilinear Map on Unknown Order Groups from Indistinguishability Obfuscation and Its Applications
... A self-bilinear map is a bilinear map where the domain and target groups are identical. In this paper, we introduce a self-bilinear map with auxiliary information which is a weaker variant of a ...
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FLEXIBLE SHARING IN DHT BASED P2P NETWORKS USING METADATA OF RESOURCE
... the bilinear interpolation algorithm, we can know that the value of each interpolation point is only related to its nearest neighbor four sampling points, and the whole processing has a good data independence and ...
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Bilinear Discriminant Component Analysis
... Bilinear parameter space factorization has been suggested before in context of Fisher LDA (Visani et al., 2005). In this paper we generalize maximum likelihood Logistic Regression to the case of a bilinear ...
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Temporal Bilinear Networks for Video Action Recognition
... Temporal Bilinear (TB) model to capture the tem- poral pairwise feature interactions between adjacent ...quadratic bilinear transformations in the temporal do- main for motion evolution and sequential ...
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Sequential Attention: A Context Aware Alignment Function for Machine Reading
... senting a blank that can be correctly filled in by the answer. With calibrated probabilities Pr(a|d, q), we take the argmax a Pr(a|d, q) where possible a’s are restricted to the subset of anonymized en- tity symbols ...
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Bilinear Fourier integral operator and its boundedness
... In [ 1 ] Beny and Okoudjou proved that a bilinear integral operator with kernel in the modulation space is bounded.. Okoudjou , Bilinear pseudodifferential operators on modulation spaces[r] ...
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Representations of solutions to linear and bilinear difference equations and systems of bilinear difference equations
... close-to-cyclic bilinear systems of difference equations can be also applied to close-to-cyclic bilinear sys- tems of difference equations of fourth ...
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Designing and Interpreting Probes with Control Tasks
... Zhang et al. (2017) defined completely random tasks related to Rademacher complexity (Bartlett and Mendelson, 2001) to understand the capacity of neural networks to overfit, showing that they are expressive enough to fit ...
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