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Found 7 papers, 5 papers with code
Efficient semidefinite-programming-based inference for binary and multi-class MRFs
Probabilistic inference in pairwise Markov Random Fields (MRFs), i. e. computing the partition function or computing a MAP estimate of the variables, is a foundational problem in probabilistic graphical models.
Community detection using fast low-cardinality semidefinite programming
Modularity maximization has been a fundamental tool for understanding the community structure of a network, but the underlying optimization problem is nonconvex and NP-hard to solve.
Differentiable learning of numerical rules in knowledge graphs
Rules over a knowledge graph (KG) capture interpretable patterns in data and can be used for KG cleaning and completion.
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
We demonstrate that by integrating this solver into end-to-end learning systems, we can learn the logical structure of challenging problems in a minimally supervised fashion.
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Low-rank semidefinite programming for the MAX2SAT problem
This paper proposes a new algorithm for solving MAX2SAT problems based on combining search methods with semidefinite programming approaches.
Realtime query completion via deep language models
Search engine users nowadays heavily depend on query completion and correction to shape their queries.
The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints
In this paper, we propose a low-rank coordinate descent approach to structured semidefinite programming with diagonal constraints.
