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The Randomized Dependence Coefficient
29 April 2013
David Lopez-Paz
Philipp Hennig
Bernhard Schölkopf
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Papers citing
"The Randomized Dependence Coefficient"
50 / 63 papers shown
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Augmenting data-driven models for energy systems through feature engineering: A Python framework for feature engineering
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A survey of some recent developments in measures of association
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Asymmetric predictability in causal discovery: an information theoretic approach
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Certified Data Removal in Sum-Product Networks
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Thomas Liebig
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Outlier Explanation via Sum-Product Networks
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Christian Bartelt
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Differentially Private Maximal Information Coefficients
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A Fair Pricing Model via Adversarial Learning
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Quantifying directed dependence via dimension reduction
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Glue: Adaptively Merging Single Table Cardinality to Estimate Join Query Size
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Tian Zeng
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Improving Conditional Coverage via Orthogonal Quantile Regression
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Stephen Bates
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Measuring Dependence with Matrix-based Entropy Functional
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Francesco Alesiani
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Robert Jenssen
José C. Príncipe
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BayesCard: Revitilizing Bayesian Frameworks for Cardinality Estimation
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Amir Shaikhha
Rong Zhu
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Are We Ready For Learned Cardinality Estimation?
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Weiyuan Wu
Jiannan Wang
Qingqing Zhou
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FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation
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FSPN: A New Class of Probabilistic Graphical Model
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Learning Unbiased Representations via Rényi Minimization
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Oualid El Hajouji
Sylvain Lamprier
Marcin Detyniecki
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General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models
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Gunnar Konig
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Fairness-Aware Neural Réyni Minimization for Continuous Features
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Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform
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Conditional Independence Testing using Generative Adversarial Networks
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On Sampling Random Features From Empirical Leverage Scores: Implementation and Theoretical Guarantees
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Monte Carlo Dependency Estimation
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Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional
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L. S. Giraldo
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Automatic Bayesian Density Analysis
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On the Effect of Suboptimal Estimation of Mutual Information in Feature Selection and Classification
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Sum-Product Networks for Hybrid Domains
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Nicola Di Mauro
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Multivariate Dependency Measure based on Copula and Gaussian Kernel
Angshuman Roy
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Stochastic Configuration Networks Ensemble for Large-Scale Data Analytics
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Copula Index for Detecting Dependence and Monotonicity between Stochastic Signals
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Approximate Kernel-based Conditional Independence Tests for Fast Non-Parametric Causal Discovery
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A Copula Statistic for Measuring Nonlinear Multivariate Dependence
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Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes
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Exploring and measuring non-linear correlations: Copulas, Lightspeed Transportation and Clustering
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An Adaptive Test of Independence with Analytic Kernel Embeddings
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From Dependence to Causation
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Large-Scale Kernel Methods for Independence Testing
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Network Maximal Correlation
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Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions
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On Column Selection in Approximate Kernel Canonical Correlation Analysis
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