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Deep Gated Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) models can extract informative corr...
10/12/2020 ∙ by Ofir Lindenbaum, et al. ∙
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Kernel-based parameter estimation of dynamical systems with unknown observation functions
A low-dimensional dynamical system is observed in an experiment as a hig...
09/09/2020 ∙ by Ofir Lindenbaum, et al. ∙
7
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Let the Data Choose its Features: Differentiable Unsupervised Feature Selection
Scientific observations often consist of a large number of variables (fe...
07/09/2020 ∙ by Ofir Lindenbaum, et al. ∙
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LOCA: LOcal Conformal Autoencoder for standardized data coordinates
We propose a deep-learning based method for obtaining standardized data ...
04/15/2020 ∙ by Erez Peterfreund, et al. ∙
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Randomly Aggregated Least Squares for Support Recovery
We study the problem of exact support recovery: given an (unknown) vecto...
03/16/2020 ∙ by Ofir Lindenbaum, et al. ∙
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The Spectral Underpinning of word2vec
word2vec due to Mikolov et al. (2013) is a word embedding method that is...
02/27/2020 ∙ by Ariel Jaffe, et al. ∙
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Deep supervised feature selection using Stochastic Gates
In this study, we propose a novel non-parametric embedded feature select...
10/09/2018 ∙ by Yutaro Yamada, et al. ∙
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Geometry-Based Data Generation
Many generative models attempt to replicate the density of their input d...
02/14/2018 ∙ by Ofir Lindenbaum, et al. ∙
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Multi-View Kernel Consensus For Data Analysis and Signal Processing
The input data features set for many data driven tasks is high-dimension...
06/28/2016 ∙ by Moshe Salhov, et al. ∙
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MultiView Diffusion Maps
In this study we consider learning a reduced dimensionality representati...
08/23/2015 ∙ by Ofir Lindenbaum, et al. ∙
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