KL divergence
Tight Parallel Repetition Theorems for Public-Coin Arguments using KL-divergence
... probability ϵ). Thus, if the allowed number of samples M is sufficiently larger than 1/ϵ, then by the Markov inequality, P ∗ can successfully convince V k with probability “almost” 1, even if we restrict P ∗ to use at most ...
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Software Integrity Attestation for SaaS Cloud Systems Using KL Divergence
... using KL Divergence. KL divergence The KL-divergence is the robust technique with respect to quantitative similarities identified in the output results of other genuine ...
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Research Hotspots Evolving Action Detection based on Time Sequence Journal Topic Model
... Abstract. Since the research hotspot development in academic fields is mainly reflected through academic journal contents, how to analyze the evolving action of academic journal related topics is a huge factor for ...
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Non-Gaussian statistics in global atmospheric dynamics: a study with a 10 240-member ensemble Kalman filter using an intermediate atmospheric general circulation model
... Spatial distributions of (a) analysis absolute error, (b) analysis ensemble spread, (c) background skewness, (d) back- ground kurtosis, and (e) background KL divergence for temperature a[r] ...
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Variational Autoencoder with Implicit Optimal Priors
... However, KL divergence with the aggregated posterior cannot be calculated in a closed form, which prevents us from using this optimal ...this KL divergence without modeling the aggregated ...
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Graph Based Lexicon Expansion with Sparsity Inducing Penalties
... metric KL-divergence used to bring the distributions at labeled vertices close to the corresponding ob- served distributions, as well as replacing the KL- based graph smoothness term with the ...
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Measuring Language Divergence by Intra Lexical Comparison
... A further difficulty lies in the fact that many lan- guages are not represented by the full 200 mean- ings. Consequently, in comparing lexical metrics from two data sets, we frequently need to restrict the metrics to ...
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Probability Product Kernels
... the KL-divergence between complicated distributions (mixtures, hidden Markov models, Bayesian networks, linear dynamical systems and intractable graphical models) is intractable and must be approximated ...
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A Survey of Text Document Clustering by using Clustering Techniques
... the KL divergence is used to calculate the similarity and as per experiment on both algorithm final output is to improve time consumption and the improve time consumption of improved k-means algorithm is ...
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Clustering Multi Attribute Uncertain Data using Probability Distribution
... between KL- Divergence and JS-Divergence against the number of ...of KL-Divergence is shown by red line in graph and for JS–Divergence it is shown by green line in ...for ...
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Estimating Class Priors in Domain Adaptation for Word Sense Disambiguation
... To gauge how well the sense priors are estimated, we measure the KL divergence between the true sense priors and the sense priors estimated by using the predictions of uncalibrated multi[r] ...
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Conditional Word Embedding and Hypothesis Testing via Bayes by Backprop
... Impact of Covariates To demonstrate how doc- ument covariates influence conditional word em- beddings, we compare the vector for “currency” against “sterling” and “pound” according to the KL divergence in ...
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Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions
... composition for both the RBM and HBM to study the total errors of each model from the trade-off between bias and variance. For our study, we use Contrastive Divergence (CD) as the inferencing technique for the ...
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Online Sentence Novelty Scoring for Topical Document Streams
... only KL divergence features, TransCount to a system using only nonlinear transformation of unseen word count features, RelPos to a system using only relative position features, Word2Vec to a system using ...
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Investigating the influence of PFC transection and nicotine on dynamics of AMPA and NMDA receptors of VTA dopaminergic neurons
... and KL divergence to better understand the dynamics of AMPA and NMDA signals since they took into consideration the whole current response rather than just the peak ...
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The Quality of the Covariance Selection through Detection Problem and AUC Bounds
... Log-scale of the possible feasible region and its asymptotic behavior (linear line) for the AUC and the KL divergence pair for all possible detectors or equivalently all possible ROC cur[r] ...
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Guaranteed Bounds on Information-Theoretic Measures of Univariate Mixtures Using Piecewise Log-Sum-Exp Inequalities
... the KL divergence within an additive factor of log k + log k 0 ...on KL divergence [15] to other information theoretical measures such as the differential entropy and ...
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Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation
... (KL) divergence between the posterior and ...of KL collapsing to zero. One has to implement various heuristics such as KL weight anneal- ing and word dropout in a carefully engineered manner ...
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Dimensional Reduction of Statistical Structural of a Paper by Information Geometry
... information divergence is generally more relevant to statistical discrimination performance than Euclidean ...information divergence between the distributions of the data over each class. The KL ...
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Cross Document Coreference on a Large Scale Corpus
... The KL divergence approach, on the other hand, showed a modest increase of 3% to 77%, equaling the agglomerative ...because KL divergence relies more on the global property of the corpus and ...
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