🔄 In a Training Loop

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ProCreations

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https://ssh.codes

AI & ML interests

i make stuff

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Reproduction - High-Dimensional Learning Dynamics of Quantized Models with STE

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Reproduction - Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies

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Reproduction - Complexity of Decentralized Optimization with Mixed Affine Constraints

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Reproduction - When More Data Doesn't Help: Limits of Adaptation in Multitask Learning

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Reproduction - On the Sharp Input-Output Analysis of Nonlinear Systems under Adversarial Attacks

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

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Reproduction - Anytime Detection of Strategic Deviations in Multi-Agent Systems

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Reproduction - Calibrating Decision Robustness via Inverse Conformal Risk Control

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Reproduction - Exploration-free Multi-group Mean Estimation

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Reproduction - Asymptotic Universal Alignment

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Reproduction - Online Newton Inference

Six-claim audit of accelerated online Newton inference

Reproduction: Convergence Analysis of the Lion Optimizer

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Reproduction: Success Conditioning as Policy Improvement

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Reproduction - No-Swap-Regret Auction Revenue

Exact auction certificates and polynomial rates

Reproduction - On Densest k-Subgraph Mining and Diagonal Loading

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Reproduction - REINFORCE Noise-to-Signal Ratio

Exact unstable-horizon, polynomial, and neural audits

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

Log and share experiment results in a web‑based research notebook

Reproduction - SAQNN Universal Approximation

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Reproduction: Autoregressive Language Models are Secretly Energy-Based Models

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Reproduction: A Short and Unified Convergence Analysis of the SAG, SAGA, and IAG Algorithms

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Reproduction: Minimum Distance Summaries for Robust Neural Posterior Estimation

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Reproduction: The Relative Instability of Model Comparison with Cross-validation

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Reproduction: Revisiting the Bertrand Paradox via Equilibrium Analysis of No-regret Learners

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Reproduction: The Optimal Sample Complexity of Linear Contracts

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