Rohit Yelukati Mahendra PRO

YMRohit

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ICML 2026 reproductions — d3LLM & MemoryBench (Claude)

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YMRohit/icml2026-31042-adagrad-heavytail-logbook

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YMRohit/icml2026-31042-adagrad-heavytail-logbook

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

Icml31042 Adagradheavy

Repro - Improved Analysis of the Accelerated Noisy Power Method with Applications to Decentralized PCA

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Icml27119 Noisypower

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Repro - Fast and Scalable Analytical Diffusion (GoldDiff)

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Icml64125 Golddiff

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Repro - FOAM: Blocked State Folding for Memory-Efficient LLM Training

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Repro - MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems

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Icml64918 Memorybench

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Reproducing Maximum Likelihood Reinforcement Learning (ICML 2026 #65332)

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Repro - Optimal Unconstrained Self-Distillation in Ridge Regression

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Repro - d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation

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Repro - Efficiently Training Time-to-First-Spike SNNs from Scratch

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Icml61269 D3llm

Repro - Combinatorial Sparse PCA Beyond the Spiked Identity Model

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Repro - Scaling Laws for Precision in High-Dimensional Linear Regression

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Repro - Towards Understanding Adam Convergence on Highly Degenerate Polynomials

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Icml22249 Release Artifacts

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Icml20531 Release Artifacts

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Icml20531 Adam Degenerate Metrics

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Repro - To Grok Grokking: Provable Grokking in Ridge Regression

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Icml17708 Grokking Metrics

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