Uncertainty relation is one of the fundamental building blocks of quantum theory. Nevertheless, the traditional uncertainty relations do not fully ca…

This short paper reports the algorithms we used and the evaluation performances for ISIC Challenge 2018. Our team participates in all the tasks in th…

Neural networks are among the state-of-the-art techniques for language modeling. Existing neural language models typically map discrete words to dist…

As the core component of Natural Language Processing (NLP) system, Language Model (LM) can provide word representation and probability indication of …

In this paper, we develop a new deflation method for refining or verifying the isolated singular zeros of polynomial systems. Given a polynomial system F⊂C[x] with an isolated singular zero p, by computing the derivatives of the input polynomials di…

In this paper, we develop a new deflation technique for refining or verifying the isolated singular zeros of polynomial systems. Starting from a poly…

Traditional manifold learning algorithms often bear an assumption that the local neighborhood of any point on embedded manifold is roughly equal to t…

The large-scale power deficit in the cosmic microwave background fluctuations might be relevant with the physics of pre-inflation, a bounce, or a sup…

In this paper the next-to-leading order (NLO) corrections to $B_c$ meson exclusive decays to S-wave charmonia and light pseudoscalar or vector mesons…

Object detection has been a building block in computer vision. Though considerable progress has been made, there still exist challenges for objects w…

Deep convolutional networks based methods have brought great breakthrough in images classification, which provides an end-to-end solution for handwri…

We study the influence of external electric, $E$, and magnetic, $B$, fields parallel to each other, and of a chiral chemical potential, $\mu_5$, on t…

In geometry processing, symmetry is the universal high level structural information of the 3d models and benefits many geometry processing tasks incl…

The current advances in object detection depend on large-scale datasets to get good performance. However, there may not always be sufficient samples …

Modern CNN-based object detectors assign anchors for ground-truth objects under the restriction of object-anchor Intersection-over-Unit (IoU). In thi…

Classification and localization are two pillars of visual object detectors. However, in CNN-based detectors, these two modules are usually optimized …

Deep Convolution Neural Networks (DCNNs) are capable of learning unprecedentedly effective image representations. However, their ability in handling …

Data augmentation is usually adopted to increase the amount of training data, prevent overfitting and improve the performance of deep models. However…

We calculate the next-to-leading order (NLO) quantum chromodynamics (QCD) corrections to double charmonium production processes $e^+e^-\to\gamma^*\to…

The quartic self-coupling of the Standard Model Higgs boson can only be measured by observing the triple-Higgs production process, but it is challeng…

In this part, we obtain the pointwise convergence with rationally independent rotation on the torus of the multiple ergodic averages.

In this paper, for a discontinuous skew-product transformation with the integrable observation function, we obtain uniform ergodic theorem and semi-u…

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