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Kyle Daruwalla

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Journal Articles

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2024
[j3]
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  - journals/ficn/DaruwallaL24
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  - https://dblp.org/rec/journals/ficn/DaruwallaL24
Kyle Daruwalla, Mikko H. Lipasti:
Information bottleneck-based Hebbian learning rule naturally ties working memory and synaptic updates. Frontiers Comput. Neurosci. 18 (2024)
2023
[j2]
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  - journals/cal/KhoramDL23
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Soroosh Khoram, Kyle Daruwalla, Mikko H. Lipasti:
Energy-Efficient Bayesian Inference Using Bitstream Computing. IEEE Comput. Archit. Lett. 22(1): 37-40 (2023)
2020
[j1]
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  - journals/taco/DaruwallaZSL20
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Kyle Daruwalla, Heng Zhuo, Rohit Shukla, Mikko H. Lipasti:
BitSAD v2: Compiler Optimization and Analysis for Bitstream Computing. ACM Trans. Archit. Code Optim. 16(4): 43:1-43:25 (2020)

Conference and Workshop Papers

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2019
[c1]
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Kyle Daruwalla, Heng Zhuo, Carly Schulz, Mikko H. Lipasti:
BitBench: a benchmark for bitstream computing. LCTES 2019: 177-187

Informal and Other Publications

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2021
[i2]
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  - journals/corr/abs-2111-12621
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Ravi S. Raju, Kyle Daruwalla, Mikko H. Lipasti:
Accelerating Deep Learning with Dynamic Data Pruning. CoRR abs/2111.12621 (2021)
[i1]
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  - journals/corr/abs-2111-13187
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Kyle Daruwalla, Mikko H. Lipasti:
Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates. CoRR abs/2111.13187 (2021)

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