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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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algorise 's Spaces 204

Reproduction: Distributionally Robust Markov Games with Average Reward

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Reproduction: High-Probability Convergence Guarantees of Decentralized SGD

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Reproduction: On the Epistemic Uncertainty of Overparametrized Neural Networks

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Reproduction: Step-Size Stability in Stochastic Optimization: A Theoretical Perspective

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Reproduction: Stationary MMD Points

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Reproduction: On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothness: An SDE Approach

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Reproduction: Forward-KL Convergence of Time-Inhomogeneous Langevin Diffusions

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Reproduction: Optimal Transport Group Counterfactual Explanations

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Reproduction: Towards Understanding Adam Convergence on Highly Degenerate Polynomials

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Reproduction: A Direct Second-Order Method for Solving Two-Player Zero-Sum Games

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Reproduction: Reusing Trajectories in Policy Gradients Enables Fast Convergence

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Reproduction: Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning

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Reproduction: Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer

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Reproduction: Near-Universal Multiplicative Updates for Nonnegative Einsum Factorization

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Reproduction: Asymptotic Universal Alignment: A New Alignment Framework via Test-Time Scaling

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Reproduction: Universal Representation of Generalized Convex Functions and their Gradients

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Reproduction: Full-Batch Gradient Descent Outperforms One-Pass SGD: Sample Complexity Separation in Single-Index Learning

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Reproduction: Refined Analysis of Entropy-Regularized Actor-Critic

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Reproduction: Asymptotically Optimal Sequential Testing with Markovian Data

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Reproduction: Learning in Structured Stackelberg Games

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Reproduction: Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels

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Reproduction: Dynamic Regret via Discounted-to-Dynamic Reduction with Applications to Curved Losses and Adam Optimizer

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Reproduction: Gradient Descent as a Perceptron Algorithm: Understanding Dynamics and Implicit Acceleration

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Reproduction: Federated Bilevel Performative Prediction

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