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Locally Private Causal Inference for Randomized Experiments
Published in JMLR (2026)Subjects: “…Computer Science & IT…”
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Estimating Network-Mediated Causal Effects via Principal Components Network Regression
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Selective Inference with Distributed Data
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Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
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An Axiomatic Definition of Hierarchical Clustering
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Test-Time Training on Video Streams
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Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
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A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
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Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents
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Enhancing Graph Representation Learning with Localized Topological Features
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Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
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DisC2o-HD: Distributed causal inference with covariates shift for analyzing real-world high-dimensional data
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Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes
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Efficiently Escaping Saddle Points in Bilevel Optimization
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Towards Understanding Gradient Flow Dynamics of Homogeneous Neural Networks Beyond the Origin
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Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity
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Towards Unified Native Spaces in Kernel Methods
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TorchCP: A Python Library for Conformal Prediction
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Hopfield-Fenchel-Young Networks: A Unified Framework for Associative Memory Retrieval
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Identifiability of Causal Graphs under Non-Additive Conditionally Parametric Causal Models
Published in JMLR (2026)Subjects: “…Computer Science & IT…”
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