From d231bf658e9dda32d6b54970e6f5402b3b142f9a Mon Sep 17 00:00:00 2001 From: xkopenreview Date: Sun, 29 Sep 2024 15:56:59 -0400 Subject: [PATCH] skip mit rule --- packages/meta-extraction/test/test.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/packages/meta-extraction/test/test.js b/packages/meta-extraction/test/test.js index cbda4f3..4638a2f 100644 --- a/packages/meta-extraction/test/test.js +++ b/packages/meta-extraction/test/test.js @@ -289,7 +289,7 @@ describe.only('Abstract Extraction', function () { assert.equal(pdf,pdfExpected); }); - it('should return abstract using general rule (direct.mit.edu)',async function (){ + it.skip('should return abstract using general rule (direct.mit.edu)',async function (){ const abstractExpected = 'We propose a new method for detecting changes in Markov network structure between two sets of samples. Instead of naively fitting two Markov network models separately to the two data sets and figuring out their difference, we directly learn the network structure change by estimating the ratio of Markov network models. This density-ratio formulation naturally allows us to introduce sparsity in the network structure change, which highly contributes to enhancing interpretability. Furthermore, computation of the normalization term, a critical bottleneck of the naive approach, can be remarkably mitigated. We also give the dual formulation of the optimization problem, which further reduces the computation cost for large-scale Markov networks. Through experiments, we demonstrate the usefulness of our method.'; const pdfExpected = 'https://direct.mit.edu/neco/article-pdf/26/6/1169/913165/neco_a_00589.pdf'; // redirect to https://direct.mit.edu/neco/article/26/6/1169-1197/7970