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Task-Optimal Exploration in Linear Dynamical Systems
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Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs
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Representing Unordered Data Using Multiset Automata and Complex Numbers
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Beyond Finite Layer Neural Networks Bridging Deep Architectures and Numerical Differential Equations
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Spectrally Approximating Large Graphs with Smaller Graphs
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Normalized Flat Minima Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis
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Scalable Exact Inference in Multi-Output Gaussian Processes
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Universal Asymptotic Optimality of Polyak Momentum
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Defense Through Diverse Directions
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Beyond Variance Reduction Understanding the True Impact of Baselines on Policy Optimization
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Predictive Coding for Locally-Linear Control
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Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization
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Transformers are RNNs Fast Autoregressive Transformers with Linear Attention
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Coherence Pursuit Fast, Simple, and Robust Subspace Recovery
CoherencePursuit:Fast,Simple,andRobustSubspaceRecoveryMostafaRahmani1GeorgeAtia1AbstractdimensionalsubspacebysolvingAremarkablysimple,yetpowerful,algorithmminD−UˆUˆTDFsubjecttoUˆTUˆ=I,(1)terme...
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Robust and Scalable Models of Microbiome Dynamics
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Lorentz Group Equivariant Neural Network for Particle Physics
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OmniNet Omnidirectional Representations from Transformers
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Obtaining Adjustable Regularization for Free via Iterate Averaging
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Black-box density function estimation using recursive partitioning
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Black Box FDR
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