arXiv subjects

Yuting Yang

Publications and source records attributed to Yuting Yang.

63 records · Page 4Linked to original sources

arXiv2021

ε-weakened Robustness of Deep Neural Networks

This paper introduces a notation of $\varepsilon$-weakened robustness for analyzing the reliability and stability of deep neural networks (DNNs). Unlike the conventional robustness, which focuses on the "perfect" safe region in the absence of adversarial examples, $\varepsilon$-weakened robustness focuses on the region where the proportion of adversarial examples is bounded by user-specified $\varepsilon$. Smaller $\varepsilon$ means a smaller chance of failure. Under such robustness definition, we can give conclusive results for the regions where conventional robustness ignores. We prove that the $\varepsilon$-weakened robustness decision problem is PP-complete and give a statistical decision algorithm with user-controllable error bound. Furthermore, we derive an algorithm to find the maximum $\varepsilon$-weakened robustness radius. The time complexity of our algorithms is polynomial in the dimension and size of the network. So, they are scalable to large real-world networks. Besides, We also show its potential application in analyzing quality issues.

cs.LG↗

arXiv2021

Deep Transfer Learning for Identifications of Slope Surface Cracks

Geohazards such as landslides have caused great losses to the safety of people's lives and property, which is often accompanied with surface cracks. If such surface cracks could be identified in time, it is of great significance for the monitoring and early warning of geohazards. Currently, the most common method for crack identification is manual detection, which is with low efficiency and accuracy. In this paper, a deep transfer learning framework is proposed to effectively and efficiently identify slope surface cracks for the sake of fast monitoring and early warning of geohazards such as landslides. The essential idea is to employ transfer learning by training (a) the large sample dataset of concrete cracks and (b) the small sample dataset of soil and rock masses cracks. In the proposed framework, (1) pretrained cracks identification models are constructed based on the large sample dataset of concrete cracks; (2) refined cracks identification models are further constructed based on the small sample dataset of soil and rock masses cracks. The proposed framework could be applied to conduct UAV surveys on high-steep slopes to realize the monitoring and early warning of landslides to ensure the safety of people's lives and property.

cs.CV↗

arXiv2021

How to Write High-quality News on Social Network? Predicting News Quality by Mining Writing Style

Rapid development of Internet technologies promotes traditional newspapers to report news on social networks. However, people on social networks may have different needs which naturally arises the question: whether can we analyze the influence of writing style on news quality automatically and assist writers in improving news quality? It's challenging due to writing style and 'quality' are hard to measure. First, we use 'popularity' as the measure of 'quality'. It is natural on social networks but brings new problems: popularity are also influenced by event and publisher. So we design two methods to alleviate their influence. Then, we proposed eight types of linguistic features (53 features in all) according eight writing guidelines and analyze their relationship with news quality. The experimental results show these linguistic features influence greatly on news quality. Based on it, we design a news quality assessment model on social network (SNQAM). SNQAM performs excellently on predicting quality, presenting interpretable quality score and giving accessible suggestions on how to improve it according to writing guidelines we referred to.

cs.CL↗

arXiv2020

Observation of Antichiral Edge States in a Circuit Lattice

We constructed an electrical circuit to realize a modified Haldane lattice exhibiting the unusual phenomenon of antichiral edge states. The circuit consists of a network of inductors and capacitors with interconnections reproducing the effects of a magnetic vector potential. The next nearest neighbor hoppings are configured differently from the standard Haldane model, and as predicted by earlier theoretical studies, this gives rise to antichiral edge states that propagate in the same direction on opposite edges and co-exist with bulk states at the same frequency. Using pickup coils to measure the voltage distributions in the circuit, we experimentally verify the key features of the modified Haldane lattice, including the group velocities of the antichiral edge states.

cond-mat.mes-hall↗

arXiv2020

On-shelf Utility Mining of Sequence Data

Utility mining has emerged as an important and interesting topic owing to its wide application and considerable popularity. However, conventional utility mining methods have a bias toward items that have longer on-shelf time as they have a greater chance to generate a high utility. To eliminate the bias, the problem of on-shelf utility mining (OSUM) is introduced. In this paper, we focus on the task of OSUM of sequence data, where the sequential database is divided into several partitions according to time periods and items are associated with utilities and several on-shelf time periods. To address the problem, we propose two methods, OSUM of sequence data (OSUMS) and OSUMS+, to extract on-shelf high-utility sequential patterns. For further efficiency, we also designed several strategies to reduce the search space and avoid redundant calculation with two upper bounds time prefix extension utility (TPEU) and time reduced sequence utility (TRSU). In addition, two novel data structures were developed for facilitating the calculation of upper bounds and utilities. Substantial experimental results on certain real and synthetic datasets show that the two methods outperform the state-of-the-art algorithm. In conclusion, OSUMS may consume a large amount of memory and is unsuitable for cases with limited memory, while OSUMS+ has wider real-life applications owing to its high efficiency.

cs.DB↗

arXiv2020

A high repetition rate picosecond LiNbO3 THz parametric amplifier and the parametric gain study

A high repetition rate, picosecond THz parametric amplifier (TPA) with a LiNbO3 (LN) crystal has been demonstrated in this work. At 10 kHz repetition rate, a peak power of 200 W and an average power of 12 μW have been obtained over a wide range around 2 THz; at 100 kHz repetition rate, a maximum peak power of 18 W and average power of 10.8 μW have been obtained. The parametric gain of the LN crystal was also investigated and a modified Schwarz-Maier model was introduced to interpret the experimental results.

physics.optics↗

arXiv2019

Gapped Topological Kink States and Topological Corner States in Graphene

Based on the tight-binding model calculations and photonic experimental visualization on graphene, we report the domain-wall-induced gapped topological kink states and topological corner states. In graphene, domain walls with gapless topological kink states could be induced either by sublattice symmetry breaking or by lattice deformation. We find that the coexistence of these two mechanisms will induce domain walls with gapped topological kink states. Significantly, the intersection of these two types of domain wall gives rise to topological corner state localized at the crossing point. Through the manipulation of domain walls, we show graphene not only a versatile platform supporting multiple topological corner modes in a controlled manner, but also possessing promising applications such as fabricating topological quantum dots composed of gapped topological kink states and topological corner states.

cond-mat.mes-hall↗

arXiv2017

Approximate Program Smoothing Using Mean-Variance Statistics, with Application to Procedural Shader Bandlimiting

This paper introduces a general method to approximate the convolution of an arbitrary program with a Gaussian kernel. This process has the effect of smoothing out a program. Our compiler framework models intermediate values in the program as random variables, by using mean and variance statistics. Our approach breaks the input program into parts and relates the statistics of the different parts, under the smoothing process. We give several approximations that can be used for the different parts of the program. These include the approximation of Dorn et al., a novel adaptive Gaussian approximation, Monte Carlo sampling, and compactly supported kernels. Our adaptive Gaussian approximation is accurate up to the second order in the standard deviation of the smoothing kernel, and mathematically smooth. We show how to construct a compiler that applies chosen approximations to given parts of the input program. Because each expression can have multiple approximation choices, we use a genetic search to automatically select the best approximations. We apply this framework to the problem of automatically bandlimiting procedural shader programs. We evaluate our method on a variety of complex shaders, including shaders with parallax mapping, animation, and spatially varying statistics. The resulting smoothed shader programs outperform previous approaches both numerically, and aesthetically, due to the smoothing properties of our approximations.

cs.GR↗

arXiv2016

Visualization of unidirectional optical waveguide using topological photonic crystals made of dielectric material

The introduction of topology unravels a new chapter of physics. Topological systems provide unique edge/interfacial quantum states which are expected to contribute to the development of novel spintronics and open the door to robust quantum computation. Optical systems can also benefit from topology. Engineering locally in real space a honeycomb photonic crystal with double Dirac cone in its photonic dispersion, topology transition in photonic band structure is induced and a pseudospin unidirectional optical channel is created and demonstrated by the backscattering immune electromagnetic transportation. The topological photonic crystal made of dielectric material can pave the road towards steering light propagations and contribute to novel communication technology.

physics.optics↗