5,453 research outputs found
Information Losses in Neural Classifiers from Sampling
This paper considers the subject of information losses arising from the
finite datasets used in the training of neural classifiers. It proves a
relationship between such losses as the product of the expected total variation
of the estimated neural model with the information about the feature space
contained in the hidden representation of that model. It then bounds this
expected total variation as a function of the size of randomly sampled datasets
in a fairly general setting, and without bringing in any additional dependence
on model complexity. It ultimately obtains bounds on information losses that
are less sensitive to input compression and in general much smaller than
existing bounds. The paper then uses these bounds to explain some recent
experimental findings of information compression in neural networks which
cannot be explained by previous work. Finally, the paper shows that not only
are these bounds much smaller than existing ones, but that they also correspond
well with experiments.Comment: To be published in IEEE TNNL
INNOVATIVE EXPLORATION AND APPLICATION OF IDEOLOGICAL AND POLITICAL EDUCATION MODEL IN COLLEGES AND UNIVERSITIES FROM THE PERSPECTIVE OF EDUCATIONAL PSYCHOLOGY
INNOVATIVE EXPLORATION AND APPLICATION OF IDEOLOGICAL AND POLITICAL EDUCATION MODEL IN COLLEGES AND UNIVERSITIES FROM THE PERSPECTIVE OF EDUCATIONAL PSYCHOLOGY
Analytical treatment for the development of electromagnetic cascades in intense magnetic fields
In a strong magnetic field, a high-energy photon can be absorbed and then
produce an electron-positron pair. The produced electron/positron will in turn
radiate a high-energy photon via synchrotron radiation, which then initiates a
cascade. We built a one-dimensional Monte-Carlo code to study the development
of the cascade especially after it reaches the saturated status, when almost
all the energy of the primary particles transfers to the photons. The photon
spectrum in this status has a cut-off due to the absorption by magnetic fields,
which is much sharper than the exponential one. Below the cut-off, the spectral
energy distribution (SED) manifest itself as a broken power-law with a spectral
index of and , respectively, below and above the broken energy.
The SED can be fitted by a simple analytical function, which is solely
determined by the product of the cascade scale and the magnetic field
perpendicular to the motion of the particle B_{\perp}, with an accuracy better
than 96\%. The similarity of the spectrum to that from the cascade in an
isotropic black-body photon field is also studied.Comment: 7 pages, 7 figures, minor changes. Version to appear in PR
Recent advances in femtosecond laser-assisted cataract surgery
Perfect vision and fewer complications is our goal in cataract surgery, femtosecond laser-assisted cataract surgery hold the promise. Applications of femtosecond laser technology for capsulotomy, nuclear fragmentation and corneal incision in cataract surgery bring a new level of accuracy, reproducibility and predictability over the current cataract surgery. The femtosecond laser produces capsulotomies that are more precise, accurate, reproducible, and stronger than those created with the conventional manual technique, and further helps maintain proper positioning of the IOL. Femtosecond laser in nuclear fragmentation lead to a lower effective phacoemulsification time, and the corneal incision is more stable. But currently there are some complications and a clear learning curve associated with the use of femtosecond lasers for cataract surgery. The long-term safety and visual outcomes still need further investigation
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