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1. A Bit More Than a Bit Is More Than a Bit Better

   https://doi.org/10.2478/popets-2019-0061  

   Hafiz, Syed Mahbub; Henry, Ryan (October 2019, Proceedings on Privacy Enhancing Technologies)

   Abstract We study both the practical and theoretical efficiency of private information retrieval (PIR) protocols in a model wherein several untrusted servers work to obliviously service remote clients’ requests for data and yet no pair of servers colludes in a bid to violate said obliviousness. In exchange for such a strong security assumption, we obtain new PIR protocols exhibiting remarkable efficiency with respect to every cost metric—download, upload, computation, and round complexity—typically considered in the PIR literature. The new constructions extend a multiserver PIR protocol of Shah, Rashmi, and Ramchandran (ISIT 2014), which exhibits a remarkable property of its own: to fetch a b -bit record from a collection of r such records, the client need only download b + 1 bits total. We find that allowing “a bit more” download (and optionally introducing computational assumptions) yields a family of protocols offering very attractive trade-offs. In addition to Shah et al.’s protocol, this family includes as special cases (2-server instances of) the seminal protocol of Chor, Goldreich, Kushilevitz, and Sudan (FOCS 1995) and the recent DPF-based protocol of Boyle, Gilboa, and Ishai (CCS 2016). An implicit “folklore” axiom that dogmatically permeates the research literature on multiserver PIR posits that the latter protocols are the “most efficient” protocols possible in the perfectly and computationally private settings, respectively. Yet our findings soundly refute this supposed axiom: These special cases are (by far) the least performant representatives of our family, with essentially all other parameter settings yielding instances that are significantly faster. 

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2. Bit-by-Bit: Investigating the Vulnerabilities of Binary Neural Networks to Adversarial Bit Flipping

   Kundu, S; Das, S; Karmakar, S; Raha, A; Kundu, S; Makris, Y; Basu, K (June 2024, Transactions on machine learning research)
3. Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network

   https://doi.org/10.1109/ISCA.2018.00069  

   Sharma, Hardik; Park, Jongse; Suda, Naveen; Lai, Liangzhen; Chau, Benson; Chandra, Vikas; Esmaeilzadeh, Hadi (June 2018, ISCA)
4. One-bit digital radar

   https://doi.org/10.1109/ACSSC.2017.8335529  

   Ren, Jiaying; Li, Jian (October 2017, Signals, Systems, and Computers, 2017 51st Asilomar Conference on)

   This paper introduces a one-bit digital radar involving direct one-bit sampling with unknown dithering of the received radio frequency (RF) signal. Due to avoiding the analog mixer and the down-conversion of the RF signal, the digital radar can be energy-efficient and low-priced. The use of unknown dithering allows for the one-bit samples to be processed efficiently using conventional algorithms. A computationally efficient range-Doppler estimation method based on fractional Fourier transform (FRFT) and fast Fourier transform (FFT) is used for linear frequency modulated continuous wave (LFMCW) transmissions, and the CLEAN algorithm is used for target parameter estimation. 

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5. Bit-Stream Processing with No Bit-Stream: Efficient Software Simulation of Stochastic Vision Machines

   https://doi.org/10.1145/3583781.3590217  

   Aygun, Sercan; Najafi, M. Hassan; Imani, Mohsen; Gunes, Ece Olcay (June 2023, Proceedings of the Great Lakes Symposium on VLSI)