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Found 9 papers, 2 papers with code
Efficient Learning of Optimal Markov Network Topology with k-Tree Modeling
The seminal work of Chow and Liu (1968) shows that approximation of a finite probabilistic system by Markov trees can achieve the minimum information loss with the topology of a maximum spanning tree.
Stock Prediction: a method based on extraction of news features and recurrent neural networks
After that, we construct the features of news based on the positive polar of their words.
A General SIMD-based Approach to Accelerating Compression Algorithms
Compression algorithms are important for data oriented tasks, especially in the era of Big Data.
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