Results 61 to 70 of about 1,885,677 (275)
Weighted Mutual Information for Aggregated Kernel Clustering
Entropy, 2020 Background: A common task in machine learning is clustering data into different groups based on similarities. Clustering methods can be divided in two groups: linear and nonlinear. A commonly used linear clustering method is K-means.
Nezamoddin N. Kachouie, Meshal Shutaywi
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Molecular Oncology, EarlyView.Cytarabine is a key therapy for acute myeloid leukaemia (AML), but its efficacy is limited by the dNTPase SAMHD1, which hydrolyses its active metabolite. Screening nucleotide biosynthesis inhibitors revealed that IMPDH inhibitors selectively sensitise SAMHD1‐proficient AML cells to cytarabine.
Miriam Yagüe‐Capilla +9 more
wiley +1 more source
Space-time generalization of mutual information
Journal of High Energy PhysicsThe mutual information characterizes correlations between spatially separated regions of a system. Yet, in experiments we often measure dynamical correlations, which involve probing operators that are also separated in time.
Paolo Glorioso +2 more
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Machine Learning with Squared-Loss Mutual Information
Entropy, 2012 Mutual information (MI) is useful for detecting statistical independence between random variables, and it has been successfully applied to solving various machine learning problems.
Masashi Sugiyama
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Derivative of BICM mutual information [PDF]
Electronics Letters, 2007 submitted to the IET Electronics Letters.
Fabregas, Albert Guillen I +1 more
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Molecular Oncology, EarlyView.We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric +10 more
wiley +1 more source
Improved Neural Networks Based on Mutual Information via Information Geometry
Algorithms, 2019 This paper presents a new algorithm based on the theory of mutual information and information geometry. This algorithm places emphasis on adaptive mutual information estimation and maximum likelihood estimation.
Meng Wang +5 more
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KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer
Molecular Oncology, EarlyView.Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan +16 more
wiley +1 more source
Advances in Applied Mathematics, 1995 The mutual information of two random variables plays fundamental roles in many areas of applied mathematics. This quantity can be generalized to finite sets of random variables. In contrast to the nonnegativity of the usual mutual information, the triple mutual information can be negative as well as positive and its sign gives us a rough indication of ...
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Hierarchical clustering using mutual information [PDF]
Europhysics Letters (EPL), 2005 We present a method for hierarchical clustering of data called {\it mutual information clustering} (MIC) algorithm. It uses mutual information (MI) as a similarity measure and exploits its grouping property: The MI between three objects $X, Y,$ and $Z$ is equal to the sum of the MI between $X$ and $Y$, plus the MI between $Z$ and the combined object ...
Kraskov, A. +3 more
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