Works matching IS 15324435 AND DT 2022 AND VI 23
Results: 351
Learning Green's functions associated with time-dependent partial differential equations.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Network Regression with Graph Laplacians.
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ReservoirComputing.jl: An Effcient and Modular Library for Reservoir Computing Models.
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Information-Theoretic Characterization of the Generalization Error for Iterative Semi-Supervised Learning.
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Self-Healing Robust Neural Networks via Closed-Loop Control.
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Approximate Bayesian Computation via Classification.
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Metrics of Calibration for Probabilistic Predictions.
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Smooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee.
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Integral Autoencoder Network for Discretization-Invariant Learning.
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Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth.
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Deepchecks: A Library for Testing and Validating Machine Learning Models and Data.
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On the Convergence Rates of Policy Gradient Methods.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks.
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OMLT: Optimization & Machine Learning Toolkit.
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Nonparametric adaptive control and prediction: theory and randomized algorithms.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Scalable Gaussian-process regression and variable selection using Vecchia approximations.
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De-Sequentialized Monte Carlo: a parallel-in-time particle smoother.
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Exact Partitioning of High-order Models with a Novel Convex Tensor Cone Relaxation.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Nonparametric Neighborhood Selection in Graphical Models.
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d3rlpy: An Offline Deep Reinforcement Learning Library.
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WarpDrive: Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Convergence Guarantees for the Good-Turing Estimator.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Learning Operators with Coupled Attention.
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Minimax optimal approaches to the label shift problem in non-parametric settings.
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Oracle Complexity in Nonsmooth Nonconvex Optimization.
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When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint.
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Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features.
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Intrinsic Dimension Estimation Using Wasserstein Distance.
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Nyström Regularization for Time Series Forecasting.
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The Weighted Generalised Covariance Measure.
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Inherent Tradeoffs in Learning Fair Representations.
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Constraint Reasoning Embedded Structured Prediction.
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Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons.
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Jump Gaussian Process Model for Estimating Piecewise Continuous Regression Functions.
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Nonstochastic Bandits with Composite Anonymous Feedback.
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Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.
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Policy Gradient and Actor--Critic Learning in Continuous Time and Space: Theory and Algorithms.
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CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms.
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Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements.
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Vector-Valued Least-Squares Regression under Output Regularity Assumptions.
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On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC).
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Power Iteration for Tensor PCA.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Effcient Inference for Dynamic Flexible Interactions of Neural Populations.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Topologically penalized regression on manifolds.
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Communication-Constrained Distributed Quantile Regression with Optimal Statistical Guarantees.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Fast Stagewise Sparse Factor Regression.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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Toward Understanding Convolutional Neural Networks from Volterra Convolution Perspective.
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- Journal of Machine Learning Research, 2022, v. 23, p. 1
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A Unified Statistical Learning Model for Rankings and Scores with Application to Grant Panel Review.
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