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Wide Neural Networks with Bottlenecks are Deep Gaussian Processes.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Trust-Region Variational Inference with Gaussian Mixture Models.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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The Kalai-Smorodinsky solution for many-objective Bayesian optimization.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Scikit-network: Graph Analysis in Python.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Breaking the Curse of Nonregularity with Subagging -- Inference of the Mean Outcome under Optimal Treatment Regimes.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Near-optimal Individualized Treatment Recommendations.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Doubly Distributed Supervised Learning and Inference with High-Dimensional Correlated Outcomes.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Consistency of Semi-Supervised Learning Algorithms on Graphs: Probit and One-Hot Methods.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Asymptotic Consistency of α-Rényi-Approximate Posteriors.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Learning Big Gaussian Bayesian Networks: Partition, Estimation and Fusion.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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- Article
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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- Article
The Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative due to the Implicit Ridge Regularization.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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New Insights and Perspectives on the Natural Gradient Method.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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- Article
Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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- Article
Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and its Statistical Optimality.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Topology of Deep Neural Networks.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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High Dimensional Forecasting via Interpretable Vector Autoregression.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Streamlined Computing for Variational Inference with Higher Level Random Effects.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Robust Reinforcement Learning with Bayesian Optimisation and Quadrature.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Distributionally Ambiguous Optimization for Batch Bayesian Optimization.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Efficient Adjustment Sets for Population Average Causal Treatment Effect Estimation in Graphical Models.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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- Article
Kriging Prediction with Isotropic Matérn Correlations: Robustness and Experimental Designs.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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apricot: Submodular selection for data summarization in Python.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Variational Inference for Computational Imaging Inverse Problems.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Distributed High-dimensional Regression Under a Quantile Loss Function.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Dual Iterative Hard Thresholding.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Optimal Estimation of Sparse Topic Models.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Generating Weighted MAX-2-SAT Instances with Frustrated Loops: an RBM Case Study.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Local Causal Network Learning for Finding Pairs of Total and Direct Effects.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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Complete Dictionary Learning via ℓ<sup>4</sup>-Norm Maximization over the Orthogonal Group.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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- Article
Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise.
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- Journal of Machine Learning Research, 2020, v. 21, n. 146-188, p. 1
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