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algorise

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algorise/repro-sinkhorn-normalization-of-diffusion-kernels

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algorise/repro-sinkhorn-normalization-of-diffusion-kernels

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algorise/repro-linear-regression-with-unknown-truncation-beyond-gaussian-features

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Reproduction: Sample Complexity Bounds for Robust Mean Estimation with Mean-Shift Contamination

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Reproduction: Nash Equilibria in Games with Playerwise Concave Coupling Constraints: Existence and Computation

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Reproduction: Joint Model and Data Sparsification via the Marginal Likelihood

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Reproduction: One-step Latent-free Image Generation with Pixel Mean Flows

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Reproduction: Agora: Toward Autonomous Bug Detection in Production-Level Consensus Protocols with LLM Agents

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Reproduction: Tracing the Dynamics of Refusal: Exploiting Latent Refusal Trajectories for Robust Jailbreak Detection

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Reproduction: Even Faster Kernel Matrix Linear Algebra via Density Estimation

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Reproduction: Robust Bayesian Optimisation with Unbounded Corruptions

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

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Reproduction: Flatland: The Adventures of Gradient Descent with Large Step Sizes

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Reproduction: Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity

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Reproduction: Lower Complexity Bounds for Nonconvex-Strongly-Convex Bilevel Optimization with First-Order Oracles

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Reproduction: The Implicit Bias of Steepest Descent with Mini-batch Stochastic Gradient

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Reproduction: MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-regularized Optimization

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Reproduction: Tracking Drift: Variation-Aware Entropy Scheduling for Non-Stationary Reinforcement Learning

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Reproduction: Improved Algorithms for Nash Welfare in Linear Bandits

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Reproduction: Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?

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Reproduction: Accuracy and Normalized Accuracy under Length Bias: Analysis, Guidelines, and a Bayesian Alternative

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Reproduction: Online Learning with Recency: Algorithms for Sliding-window Streaming Multi-armed Bandits

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Reproduction: High-Accuracy Sampling for Diffusion Models and Log-Concave Distributions

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Reproduction: Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation

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Reproduction: DDSVM: A Differentiable Framework for Deep Support Vector Machines with Iterative Geometry-Aware Optimization

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Reproduction: Can Adaptive Gradient Methods Converge under Heavy-Tailed Noise? A Case Study of AdaGrad

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Reproduction: Taming Stochastic Gradient Descent: Almost Sure Convergence and Saddle-Point Avoidance under (L0,L1)-Smoothness

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