Zobrazeno 1 - 10
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pro vyhledávání: '"Shafik, A"'
The increasing demand for processing large volumes of data for machine learning models has pushed data bandwidth requirements beyond the capability of traditional von Neumann architecture. In-memory computing (IMC) has recently emerged as a promising
Externí odkaz:
http://arxiv.org/abs/2412.05327
Autor:
Ghazal, Omar, Lan, Tian, Ojukwu, Shalman, Krishnamurthy, Komal, Yakovlev, Alex, Shafik, Rishad
The modern implementation of machine learning architectures faces significant challenges due to frequent data transfer between memory and processing units. In-memory computing, primarily through memristor-based analog computing, offers a promising so
Externí odkaz:
http://arxiv.org/abs/2408.09456
The Tsetlin Machine (TM) has gained significant attention in Machine Learning (ML). By employing logical fundamentals, it facilitates pattern learning and representation, offering an alternative approach for developing comprehensible Artificial Intel
Externí odkaz:
http://arxiv.org/abs/2407.09162
Notorious for its 70-80% recurrence rate, Non-muscle-invasive Bladder Cancer (NMIBC) imposes a significant human burden and is one of the costliest cancers to manage. Current tools for predicting NMIBC recurrence rely on scoring systems that often ov
Externí odkaz:
http://arxiv.org/abs/2403.10586
System-on-Chip Field-Programmable Gate Arrays (SoC-FPGAs) offer significant throughput gains for machine learning (ML) edge inference applications via the design of co-processor accelerator systems. However, the design effort for training and transla
Externí odkaz:
http://arxiv.org/abs/2403.10538
Autor:
Bhattarai, Bimal, Granmo, Ole-Christoffer, Jiao, Lei, Andersen, Per-Arne, Tunheim, Svein Anders, Shafik, Rishad, Yakovlev, Alex
In this paper, we introduce a sparse Tsetlin Machine (TM) with absorbing Tsetlin Automata (TA) states. In brief, the TA of each clause literal has both an absorbing Exclude- and an absorbing Include state, making the learning scheme absorbing instead
Externí odkaz:
http://arxiv.org/abs/2310.11481
Autor:
Hai Tao, Mohammed Suleman Aldlemy, Raad Z. Homod, Mustafa K. A. Mohammed, Abdul Rahman Mallah, Omer A. Alawi, Shafik S. Shafik, Hussein Togun, Blanka Klimova, Hassan Alzahrani, Zaher Mundher Yaseen
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 18, Iss 1 (2024)
1D and 2D carbon nanomaterials such as multi-walled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) were investigated numerically. The thermophysical properties of water and nanofluids using MWCNTs in different outer diameters (ODs) and G
Externí odkaz:
https://doaj.org/article/a12c2e4f262a431fb74afc3588110a07
The $q$-state Potts chain with ferromagnetic couplings, $J=1$, in the presence of a transverse field, $\Gamma$, has a quantum phase transition at $\Gamma/q=1$, which is continuous for $q \le 4$ and of first order for $q>4$. Here we introduce a $q$-pe
Externí odkaz:
http://arxiv.org/abs/2306.09127
Autor:
Prescott, Samuel, Wheeldon, Adrian, Shafik, Rishad, Rahman, Tousif, Yakovlev, Alex, Granmo, Ole-Christoffer
There is a need for machine learning models to evolve in unsupervised circumstances. New classifications may be introduced, unexpected faults may occur, or the initial dataset may be small compared to the data-points presented to the system during no
Externí odkaz:
http://arxiv.org/abs/2306.01027
Autor:
Ghazal, Omar, Singh, Simranjeet, Rahman, Tousif, Yu, Shengqi, Zheng, Yujin, Balsamo, Domenico, Patkar, Sachin, Merchant, Farhad, Xia, Fei, Yakovlev, Alex, Shafik, Rishad
In-memory computing for Machine Learning (ML) applications remedies the von Neumann bottlenecks by organizing computation to exploit parallelism and locality. Non-volatile memory devices such as Resistive RAM (ReRAM) offer integrated switching and st
Externí odkaz:
http://arxiv.org/abs/2305.12914