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Proteus: Preserving Model Confidentiality during Graph Optimizations

Proteus: Preserving Model Confidentiality during Graph Optimizations

18 April 2024
Yubo Gao
Maryam Haghifam
Christina Giannoula
Renbo Tu
Gennady Pekhimenko
Nandita Vijaykumar
    AAML
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Papers citing "Proteus: Preserving Model Confidentiality during Graph Optimizations"

2 / 2 papers shown
Title
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
Mufei Li
Viraj Shitole
Eli Chien
Changhai Man
Zhaodong Wang
Srinivas Sridharan
Ying Zhang
Tushar Krishna
P. Li
30
0
0
04 Nov 2024
SparseTIR: Composable Abstractions for Sparse Compilation in Deep
  Learning
SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning
Zihao Ye
Ruihang Lai
Junru Shao
Tianqi Chen
Luis Ceze
76
91
0
11 Jul 2022
1