Approximate Inference via Weighted Rademacher Complexity

This repository contains code used for experiments described in:

Approximate Inference via Weighted Rademacher Complexity
Jonathan Kuck, Ashish Sabharwal, Stefano Ermon
AAAI Conference on Artificial Intelligence (AAAI), 2018.
Paper: https://arxiv.org/abs/1801.09028
Blog post: https://ermongroup.github.io/blog/rademacher/

To reproduce Ising model experiments, see refactored_multi_model/ising_model.py.
To reproduce # SAT experiments, see refactored_multi_model/sat_model.py.

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
SAT_problems		SAT_problems
plots		plots
refactored_multi_model		refactored_multi_model
test_bias_plots		test_bias_plots
.DS_Store		.DS_Store
._.DS_Store		._.DS_Store
._test_Delta_ub.py		._test_Delta_ub.py
._test_barvinok_bias_weighted.py		._test_barvinok_bias_weighted.py
README.md		README.md
exact_partition.py		exact_partition.py
ising_model.py		ising_model.py
mrf_model.py		mrf_model.py
mrf_single_joint_factor.py		mrf_single_joint_factor.py
permanent_bound_comparison_simple_clean.py		permanent_bound_comparison_simple_clean.py
test_Delta_ub.py		test_Delta_ub.py
test_barvinok_bias.py		test_barvinok_bias.py
test_barvinok_bias_weighted.py		test_barvinok_bias_weighted.py
test_independent_c_vecs.py		test_independent_c_vecs.py

ermongroup/weighted-rademacher

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Approximate Inference via Weighted Rademacher Complexity

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