Optimal Experiment Design for Causal Effect Identification

Subjects: “…Artificial Intelligence & Machine Learning…”
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Mean Aggregator is More Robust than Robust Aggregators under Label Poisoning Attacks on Distributed Heterogeneous Data

Subjects: “…Artificial Intelligence & Machine Learning…”
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The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond

Subjects: “…Artificial Intelligence & Machine Learning…”
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depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers

Subjects: “…Artificial Intelligence & Machine Learning…”
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The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise

Subjects: “…Artificial Intelligence & Machine Learning…”
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Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick

Subjects: “…Artificial Intelligence & Machine Learning…”
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Directed Cyclic Graphs for Simultaneous Discovery of Time-Lagged and Instantaneous Causality from Longitudinal Data Using Instrumental Variables

Subjects: “…Artificial Intelligence & Machine Learning…”
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Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions

Subjects: “…Artificial Intelligence & Machine Learning…”
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Regularizing Hard Examples Improves Adversarial Robustness

Subjects: “…Artificial Intelligence & Machine Learning…”
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Random ReLU Neural Networks as Non-Gaussian Processes

Subjects: “…Artificial Intelligence & Machine Learning…”
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Riemannian Bilevel Optimization

Subjects: “…Artificial Intelligence & Machine Learning…”
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Supervised Learning with Evolving Tasks and Performance Guarantees

Subjects: “…Artificial Intelligence & Machine Learning…”
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Error estimation and adaptive tuning for unregularized robust M-estimator

Subjects: “…Artificial Intelligence & Machine Learning…”
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From Sparse to Dense Functional Data in High Dimensions: Revisiting Phase Transitions from a Non-Asymptotic Perspective

Subjects: “…Artificial Intelligence & Machine Learning…”
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Locally Private Causal Inference for Randomized Experiments

Subjects: “…Artificial Intelligence & Machine Learning…”
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Estimating Network-Mediated Causal Effects via Principal Components Network Regression

Subjects: “…Artificial Intelligence & Machine Learning…”
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Selective Inference with Distributed Data

Subjects: “…Artificial Intelligence & Machine Learning…”
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Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization

Subjects: “…Artificial Intelligence & Machine Learning…”
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An Axiomatic Definition of Hierarchical Clustering

Subjects: “…Artificial Intelligence & Machine Learning…”
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Test-Time Training on Video Streams

Subjects: “…Artificial Intelligence & Machine Learning…”
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