Search Results - Blakeney, Cody

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  1. 1
    Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression

    Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression by Blakeney, Cody, Li, Xiaomin, Yan, Yan, Zong, Ziliang

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  2. 2
    Improving the energy efficiency of relational and NoSQL databases via query optimizations

    Improving the energy efficiency of relational and NoSQL databases via query optimizations by Mahajan, Divya, Blakeney, Cody, Zong, Ziliang

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  3. 3
    Is Pruning Compression?: Investigating Pruning Via Network Layer Similarity

    Is Pruning Compression?: Investigating Pruning Via Network Layer Similarity by Blakeney, Cody, Yan, Yan, Zong, Ziliang

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  4. 4
    Does your data spark joy? Performance gains from domain upsampling at the end of training

    Does your data spark joy? Performance gains from domain upsampling at the end of training by Blakeney, Cody, Mansheej, Paul, Larsen, Brett W, Owen, Sean, Frankle, Jonathan

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  5. 5
    Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models

    Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models by Ankner, Zachary, Blakeney, Cody, Sreenivasan, Kartik, Marion, Max, Leavitt, Matthew L, Mansheej, Paul

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  6. 6
    Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation

    Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation by Blakeney, Cody, Huish, Nathaniel, Yan, Yan, Zong, Ziliang

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  7. 7
    LoRA Learns Less and Forgets Less

    LoRA Learns Less and Forgets Less by Biderman, Dan, Portes, Jacob, Gonzalez Ortiz, Jose Javier, Mansheej, Paul, Greengard, Philip, Jennings, Connor, King, Daniel, Havens, Sam, Chiley, Vitaliy, Frankle, Jonathan, Blakeney, Cody, Cunningham, John P

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  8. 8
    Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation

    Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation by Blakeney, Cody, de, Jessica Zosa, Frankle, Jonathan, Zong, Ziliang, Leavitt, Matthew L

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  9. 9
    Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression

    Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression by Blakeney, Cody, Li, Xiaomin, Yan, Yan, Zong, Ziliang

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  10. 10
    Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks

    Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks by Blakeney, Cody, Atkinson, Gentry, Huish, Nathaniel, Yan, Yan, Metris, Vangelis, Zong, Ziliang

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