Hong Seong Pyo

SabaPivot

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Reproduction: Certificate-Guided Pruning for Stochastic Lipschitz Optimization

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Reproduction: A theory of learning data statistics in diffusion models, from easy to hard

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Reproduction: Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions

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Reproduction: On the Provable Suboptimality of Momentum SGD in Nonstationary Stochastic Optimization

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Reproduction: High-Probability Convergence Guarantees of Decentralized SGD

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Reproduction: Convergence of Two-Timescale Markovian Stochastic Approximations with Applications in Reinforcement Learning

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Reproduction: Approximation Theory for Lipschitz Continuous Transformers

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Reproduction: Persuasive Privacy

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Reproduction: Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm

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Reproduction: High-Dimensional Learning Dynamics of Quantized Models with Straight-Through Estimator

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Reproduction: Operator Splitting with Hamilton-Jacobi-based Proximals

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Reproduction: MiniMax Learning of Interpretable Factored Stochastic Policies from Conjoint Data, with Uncertainty Quantification

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Reproduction: Rotation-Invariant Spherical Watermarking via Third-Order SO(3) Representation Coupling

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Reproduction: Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis

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Reproduction: Context-free Recognition with Transformers

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Reproduction: Steady-State Behavior of Constant-Stepsize Stochastic Approximation: Gaussian Approximation and Tail Bounds

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Reproduction: Any-dimensional invariant universality

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Reproduction: Unifying Low Dimensional Spectra in Deep Learning

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Reproduction: Convergence Rate of the Last Iterate of Stochastic Proximal Algorithms

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Reproduction: Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets

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Reproduction: Near-Optimal Regret for KL-Regularized Multi-Armed Bandits

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Reproduction: Magnitude Distance: A Geometric Measure of Dataset Similarity

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Reproduction: Causal Modeling of Selection in Evolution

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Reproduction: Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints

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