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Closing the Gap Between Short and Long XORs for Model Counting
Shengjia Zhao, Sorathan Chaturapruek, Ashish Sabharwal +1
Many recent algorithms for approximate model counting are based on a reduction to combinatorial searches over random subsets of the space defined by parity or XOR constraints. Long…
Tight Variational Bounds via Random Projections and I-Projections
Lun-Kai Hsu, Tudor Achim, Stefano Ermon
Information projections are the key building block of variational inference algorithms and are used to approximate a target probabilistic model by projecting it onto a family of tr…
Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping
Michael Xie, Neal Jean, Marshall Burke +2
The lack of reliable data in developing countries is a major obstacle to sustainable development, food security, and disaster relief. Poverty data, for example, is typically scarce…
Variable Elimination in the Fourier Domain
Yexiang Xue, Stefano Ermon, Ronan Le Bras +2
The ability to represent complex high dimensional probability distributions in a compact form is one of the key insights in the field of graphical models. Factored representations…