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Hybrid semiconductor/molecular (" CMOL ") circuits may be used for hardware implementation of artificial neural network. Our studies show that such networks (" CrossNets ") may eventually exceed the mammal brain in areal density, at much higher speed and acceptable power consumption. In this report, we demonstrate that CrossNets based on simple(More)
SUMMARY This paper reviews recent important results in the development of neuromorphic network architectures ('CrossNets') for future hybrid semiconductor=nanodevice-integrated circuits. In particular, we have shown that despite the hardware-imposed limitations, a simple weight import procedure allows the CrossNets using simple two-terminal nanodevices to(More)
Hybrid " CMOL " integrated circuits, combining CMOS subsystem with nanowire crossbars and simple two-terminal nanodevices, promise to extend the exponential Moore-Law development of microelectronics into the sub-10-nm range. We are developing neuromorphic network (" CrossNet ") architectures for this future technology, in which neural cell bodies are(More)
In this letter, we have found a more general formulation of the REward Increment = Nonnegative Factor x Offset Reinforcement x Characteristic Eligibility (REINFORCE) learning principle first suggested by Williams. The new formulation has enabled us to apply the principle to global reinforcement learning in networks with various sources of randomness, and to(More)
Esophageal squamous cell carcinoma (ESCC) is one of the most lethal malignancies with a 5-year survival rate less than 15%. Understanding of the molecular mechanisms involved in the pathogenesis of ESCC becomes critical to develop more effective treatments. Mcl-1 expression was measured by reverse transcription (RT)-PCR and Western blotting. Human Mcl-1(More)
Resource allocation mechanism plays a critical role towards the success of cloud computing. Existing allocation mechanisms in public cloud is unsuitable to private IaaS cloud because they either cannot maximize the sum of users value, or provide no service guarantee. For overcome these shortcomings, we propose a novel online, model-free mechanism that makes(More)
Our group is developing artificial neural networks that may be implemented using hybrid semiconductor/molecular (" CMOL ") circuits. Estimates show that such networks (" CrossNets ") may eventually exceed the mammal brain in areal density, at much higher speed and acceptable power consumption. In this report, we demonstrate that CrossNets based on simple(More)
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochastic cells (" Boltzmann machines "). This formulation has enabled us to apply the principle to global reinforcement learning in networks with deterministic neural cells but stochastic(More)