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Poster
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Tue 18:30
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Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimization
Pan Xu · Jian Ma · Quanquan Gu
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Poster
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Mon 18:30
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Scalable Model Selection for Belief Networks
Zhao Song · Yusuke Muraoka · Ryohei Fujimaki · Lawrence Carin
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Workshop
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Fri 14:15
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Sayantan Dasgupta (Michigan) on Multi-label Learning for Large Text Corpora using Latent Variable Model
Sayantan Dasgupta
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Poster
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Wed 18:30
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An Empirical Bayes Approach to Optimizing Machine Learning Algorithms
James McInerney
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Poster
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Mon 18:30
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Neural Variational Inference and Learning in Undirected Graphical Models
Volodymyr Kuleshov · Stefano Ermon
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Poster
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Wed 18:30
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Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models
Rishit Sheth · Roni Khardon
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Poster
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Mon 18:30
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Neural Expectation Maximization
Klaus Greff · Sjoerd van Steenkiste · Jürgen Schmidhuber
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Poster
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Mon 18:30
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Gaussian process based nonlinear latent structure discovery in multivariate spike train data
Anqi Wu · Nicholas Roy · Stephen Keeley · Jonathan Pillow
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Poster
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Wed 18:30
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Causal Effect Inference with Deep Latent-Variable Models
Christos Louizos · Uri Shalit · Joris Mooij · David Sontag · Richard Zemel · Max Welling
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Poster
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Mon 18:30
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Collapsed variational Bayes for Markov jump processes
Boqian Zhang · Jiangwei Pan · Vinayak Rao
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Poster
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Mon 18:30
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A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks
Qinliang Su · xuejun Liao · Lawrence Carin
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Poster
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Tue 18:30
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Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
Zhenwen Dai · Mauricio Álvarez · Neil Lawrence
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