Searching for "Probability Product Kernels." – sorted by Relevance.
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Probability product kernels
- are combined with generative modeling using a novel kernel between distributions. In the probability product
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A family of probabilistic kernels based on information divergence
- of the previously proposed probability product kernel. A family of probabilistic kernels, based on information
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Spectral Clustering and Embedding with Hidden Markov Models
- ) ˆμi = � T −1 t=1 � T t=1 γt(i)xt � T t=1 γt(i) 2.2 Probability Product Kernels ˆΣi = �T t=1 γt
- Cited by 1 (0 self) – Add To MetaCart
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Support Cluster Machine
- of the proposed SCM and the probability product kernel is firstly described, and then the proposed SCM
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Bhattacharyya and Expected Likelihood Kernels
- and computing the probability product kernel between these estimates: K (x ; x 0 ) = K (p; p 0 ) = Z p
- Cited by 10 (2 self) – Add To MetaCart
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BIOMEDICAL IMAGE CLASSIFICATION USING JOINT HISTOGRAM AND BHATTACHARYYA KERNEL
- distributions, the Probability Product Kernel. They showed that in special cases, their kernel reduces
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Weighted Decomposition Kernels
- histogram intersection kernels (Odone et al., 2005) and probability product kernels (Jebara et al., 2004
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Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis
- of time series data [10]. This probability product kernel measures the distance between two HMMs each
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Invariances in kernel methods: From samples to objects
- in the space of functions Ks(., x ′ ) and was called the probability product kernel in Kondor and Jebara (2004
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Face recognition using more than one still image: What is more
- proposed probability product kernel function. In [47], Zhou and Chellappa computed the probabilistic
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