🔄 In a Training Loop

Abdullah Mujeeb Khawaja

amkkk

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https://navigatingnoise.substack.com/

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updated a Space about 1 hour ago

amkkk/gpts-regret-bounds-repro

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ICML-2026-agent-repro/challenge:20 spaces per day publishing limit lift it

published a bucket about 13 hours ago

amkkk/repro-minimum-distance-summaries-for-robust-neural-posterior-estimation-artifacts

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amkkk 's Spaces 63

Repro - On Regret Bounds of Thompson Sampling for Bayesian Optimization

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Reproduction: Revisiting ML Training under Fully Homomorphic Encryption: Convergence Guarantees, Differential Privacy, and Efficient Algorithms

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Reproduction: Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks

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Repro - Softmax as Linear Attention in the Large-Prompt Regime

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Reproduction: Cost-aware Stopping for Bayesian Optimization

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Reproduction: To Grok Grokking: Provable Grokking in Ridge Regression

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Reproduction: Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs

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Reproduction: CAffNet: Hard Constraint-Affine Neural Networks

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Reproduction audit: Non-Uniform Noise-to-Signal Ratio in the REINFORCE Policy-Gradient Estimator

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Reproduction: Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models

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Reproduction: Fair Decisions from Calibrated Scores: Achieving Optimal Classification While Satisfying Sufficiency

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Reproduction: Success-Conditioning as Policy Improvement: The Optimization Problem Solved by Imitating Success

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

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Reproduction: Gaussian Mean Field Variational Inference can Overestimate Predictive Variance

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Reproduction: Ski Rental with Distributional Predictions of Unknown Quality

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Reproduction: Learning in Structured Stackelberg Games

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Repro - Sharp Inequalities between TV and Hellinger for Gaussian Mixtures

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Repro - Positive Distribution Shift as a Framework for Tractable Learning

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

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Repro - On the Coordination of Value-Maximizing Bidders

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Repro - On the Accuracy of Newton Step and Influence Function Data Attributions

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Repro - Theoretical Challenges in Learning for Branch-and-Cut

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Repro - Chebyshev Policies and the Mountain Car Problem

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Repro - Tighter Regret Lower Bound for GP Bandits with SE Kernel

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