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4 papers · 2 filters
Hindsight Credit Assignment
Anna Harutyunyan, Will Dabney, Thomas Mesnard +8
We consider the problem of efficient credit assignment in reinforcement learning. In order to efficiently and meaningfully utilize new data, we propose to explicitly assign credit…
Alleviating Label Switching with Optimal Transport
Pierre Monteiller, Sebastian Claici, Edward Chien +3
Label switching is a phenomenon arising in mixture model posterior inference that prevents one from meaningfully assessing posterior statistics using standard Monte Carlo procedure…
Deep Network Classification by Scattering and Homotopy Dictionary Learning
John Zarka, Louis Thiry, Tomás Angles +1
We introduce a sparse scattering deep convolutional neural network, which provides a simple model to analyze properties of deep representation learning for classification. Learning…
Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins
Jérôme Tubiana, Simona Cocco, Rémi Monasson
A Restricted Boltzmann Machine (RBM) is an unsupervised machine-learning bipartite graphical model that jointly learns a probability distribution over data and extracts their relev…