Maps frozen MobileNetV2 features to Ising spins on quasi-cyclic LDPC graphs, operates a Random-Bond Ising Model at Nishimori temperature, and achieves 98.7% top-1 accuracy on ImageNet-10 and 84.92% on ImageNet-100 with 32-64 dimensional representations.
Stoica et al., ACM SIGCOMM31, 149–160 (2001)
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TensorHub uses Reference-Oriented Storage to enable scalable weight transfer in LLM RL training by referencing replicated GPU weights, achieving up to 19x reduction in cross-datacenter stall time.
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Natural Image Classification via Quasi-Cyclic Graph Ensembles and Random-Bond Ising Models at the Nishimori Temperature
Maps frozen MobileNetV2 features to Ising spins on quasi-cyclic LDPC graphs, operates a Random-Bond Ising Model at Nishimori temperature, and achieves 98.7% top-1 accuracy on ImageNet-10 and 84.92% on ImageNet-100 with 32-64 dimensional representations.
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TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training
TensorHub uses Reference-Oriented Storage to enable scalable weight transfer in LLM RL training by referencing replicated GPU weights, achieving up to 19x reduction in cross-datacenter stall time.