Machine Learning Using Approximate Computing
Journal of Low Power Electronics and ApplicationsApproximate computation has emerged as a promising alternative to accurate computation, particularly for applications that can tolerate some degree of error without significant degradation of the output quality.
Padmanabhan Balasubramanian +2 more
doaj +1 more source
Approximate Computing With Stochastic Transistors’ Voltage Over-Scaling
IEEE Access, 2019 Ubiquitous computing and the ever-rising need for energy efficiency pose challenges in terms of the processing requirements and the corresponding machine complexity.
Ren Li +3 more
doaj +1 more source
Approximate Computing: Concepts, Architectures, Challenges, Applications, and Future Directions
IEEE AccessThe unprecedented progress in computational technologies led to a substantial proliferation of artificial intelligence applications, notably in the era of big data and IoT devices.
Ayad M. Dalloo +3 more
doaj +1 more source
A Low-Power and High-Accuracy Approximate Multiplier With Reconfigurable Truncation
IEEE Access, 2022 Multipliers are among the most critical arithmetic functional units in many applications, and those applications commonly require many multiplications which result in significant power consumption. For applications that have error tolerance, employing an
Fang-Yi Gu, Ing-Chao Lin, Jia-Wei Lin
doaj +1 more source
An Approximate GEMM Unit for Energy-Efficient Object Detection
Sensors, 2021 Edge computing brings artificial intelligence algorithms and graphics processing units closer to data sources, making autonomy and energy-efficient processing vital for their design.
Ratko Pilipović +4 more
doaj +1 more source
Primal Recovery from Consensus-Based Dual Decomposition for Distributed Convex Optimization [PDF]
, 2015 Dual decomposition has been successfully employed in a variety of distributed convex optimization problems solved by a network of computing and communicating nodes.
Jamali-Rad, Hadi, Simonetto, Andrea
core +2 more sources
ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation
Journal of Statistical Software, 2021 ABCpy is a highly modular scientific library for approximate Bayesian computation (ABC) written in Python. The main contribution of this paper is to document a software engineering effort that enables domain scientists to easily apply ABC to their ...
Ritabrata Dutta +7 more
doaj +1 more source
Two-loop QCD Corrections to $b \to c$ Transitions at Zero Recoil: Analytical Results [PDF]
, 1997 We present analytical results for the $O(\alpha _s ^2)$ contributions to the functions $\eta _A$ and $\eta _V$ which parameterize QCD corrections to semileptonic $b \to c$ transitions at zero recoil. Previously obtained approximate results are confirmed.
Andrzej Czarnecki +17 more
core +2 more sources
An effective likelihood-free approximate computing method with statistical inferential guarantees [PDF]
, 2018 Approximate Bayesian computing is a powerful likelihood-free method that has grown increasingly popular since early applications in population genetics.
Li, Wentao +2 more
core +1 more source
Privacy Leakages in Approximate Adders
, 2018 Approximate computing has recently emerged as a promising method to meet the low power requirements of digital designs. The erroneous outputs produced in approximate computing can be partially a function of each chip's process variation. We show that, in
Holcomb, Daniel, Keshavarz, Shahrzad
core +1 more source