Archive

DGIF 2016

Understanding Deep Learning and Neural Semantics

Abstract : Deep learning has achieved great success in computer vision. Many people believe that the success is due to employing a huge number of parameters to fit big training data. In this talk, I will show that neuron responses of […]

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Antiferromagnetic spintronics for low-power neuromorphic computing

Abstract : The mammalian brain is far superior to today’s electronic circuits in intelligence and efficiency. Its functions are realized by the network of neurons connected via synapses. Much effort has been extended in finding satisfactory electronic neural networks that act […]

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ReRAM-based analog synapse devices for neuromorphic system

Abstract : To overcome the intrinsic limitations of von Neumann computing system with information bottleneck between memory and CPU, we need to develop neuromorphic computing system based on hardware artificial neural network (ANN). Hardware ANN system with high density synapse and […]

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Brain-Inspired Computing with Magnetic Nanodevices

Abstract : Today, neural networks are everywhere: they are the virtual assistants in our smartphones, they are powering our search engines and they are the key to big data classification. They can even beat humans at image recognition or at strategy […]

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Spin as State Variable for Computation: Prospects and Perspectives

Abstract : Recent experiments on spin devices like magnetic tunnel junctions (MTJ’s), domain wall motion (DWM) in magnetic strips and spin valves have led to the possibility of having very high density on-chip memories and logic. While the possibility of having […]

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Three Principles for Data Science: Predictability, Stability and Computability

Abstract : In this talk, I’d like to discuss the intertwining importance and connections of three principles of data science in the title in data-driven decisions. The ultimate importance of prediction lies in the fact that future holds the unique and […]

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Brain Plasticity from Synapse to Cognition

Abstract : The cognitive functions of the brain, such as learning and memory, depend on the ability of neural circuits to undergo use-dependent changes in their signal processing properties. Depending on the pattern of neuronal activities, repetitive synaptic transmission could cause […]

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Single-molecule studies of DNA mismatch repair

Abstract : DNA mismatch repair (MMR) is a catalytic reaction of a strand-specific degradation and resynthesis dependent on the mismatch by coordination of sequential signaling pathways. Mutation of MutS homolog (MSH) and MutL homolog (MLH/PMS) of MMR components results in elevate […]

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