Works matching IS 15324435 AND DT 2019 AND VI 20 AND IP 137-159
Results: 22
Optimal Convergence Rates for Convex Distributed Optimization in Networks.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Characterizing the Sample Complexity of Pure Private Learners.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Bayesian Optimization for Policy Search via Online-Offline Experimentation.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Quantifying Uncertainty in Online Regression Forests.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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GraSPy: Graph Statistics in Python.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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On Asymptotic and Finite-Time Optimality of Bayesian Predictors.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Convergence of Gaussian Belief Propagation Under General Pairwise Factorization: Connecting Gaussian MRF with Pairwise Linear Gaussian Model.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Convergence guarantees for a class of non-convex and non-smooth optimization problems.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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High-dimensional Varying Index Coefficient Models via Stein's Identity.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Learning Optimized Risk Scores.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Collective Matrix Completion.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Minimal Sample Subspace Learning: Theory and Algorithms.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Approximation algorithms for stochastic clustering.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Multiclass Boosting: Margins, Codewords, Losses, and Algorithms.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Generalized maximum entropy estimation.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Nonparametric Bayesian Aggregation for Massive Data.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Decentralized Dictionary Learning Over Time-Varying Digraphs.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Model-free Nonconvex Matrix Completion: Local Minima Analysis and Applications in Memory-efficient Kernel PCA.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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Provably Accurate Double-Sparse Coding.
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- Journal of Machine Learning Research, 2019, v. 20, n. 137-159, p. 1
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