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Ying Chen

Publications and source records attributed to Ying Chen.

At least 217 records · Page 12Linked to original sources

Optimal Contract Design for End-of-Life Care Payments

A large fraction of total healthcare expenditure occurs due to end-of-life (EOL) care, which means it is important to study the problem of more carefully incentivizing necessary versus unnecessary EOL care because this has the potential to reduce overall healthcare spending. This paper introduces a principal-agent model that integrates a mixed payment system of fee-for-service and pay-for-performance in order to analyze whether it is possible to better align healthcare provider incentives with patient outcomes and cost-efficiency in EOL care. The primary contributions are to derive optimal contracts for EOL care payments using a principal-agent framework under three separate models for the healthcare provider, where each model considers a different level of risk tolerance for the provider. We derive these optimal contracts by converting the underlying principal-agent models from a bilevel optimization problem into a single-level optimization problem that can be analytically solved. Our results are demonstrated using a simulation where an optimal contract is used to price intracranial pressure monitoring for traumatic brain injuries.

math.OC↗

Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference

In the context of high usability in single-class anomaly detection models, recent academic research has become concerned about the more complex multi-class anomaly detection. Although several papers have designed unified models for this task, they often overlook the utility of class labels, a potent tool for mitigating inter-class interference. To address this issue, we introduce a Multi-class Implicit Neural representation Transformer for unified Anomaly Detection (MINT-AD), which leverages the fine-grained category information in the training stage. By learning the multi-class distributions, the model generates class-aware query embeddings for the transformer decoder, mitigating inter-class interference within the reconstruction model. Utilizing such an implicit neural representation network, MINT-AD can project category and position information into a feature embedding space, further supervised by classification and prior probability loss functions. Experimental results on multiple datasets demonstrate that MINT-AD outperforms existing unified training models.

cs.CV↗

SoftPatch: Unsupervised Anomaly Detection with Noisy Data

Although mainstream unsupervised anomaly detection (AD) algorithms perform well in academic datasets, their performance is limited in practical application due to the ideal experimental setting of clean training data. Training with noisy data is an inevitable problem in real-world anomaly detection but is seldom discussed. This paper considers label-level noise in image sensory anomaly detection for the first time. To solve this problem, we proposed a memory-based unsupervised AD method, SoftPatch, which efficiently denoises the data at the patch level. Noise discriminators are utilized to generate outlier scores for patch-level noise elimination before coreset construction. The scores are then stored in the memory bank to soften the anomaly detection boundary. Compared with existing methods, SoftPatch maintains a strong modeling ability of normal data and alleviates the overconfidence problem in coreset. Comprehensive experiments in various noise scenes demonstrate that SoftPatch outperforms the state-of-the-art AD methods on the MVTecAD and BTAD benchmarks and is comparable to those methods under the setting without noise.

cs.CV↗

Dynamic motion trajectory control with nanoradian accuracy for multi-element X-ray optical systems via laser interferometry

The past decades have witnessed the development of new X-ray beam sources with brightness growing at a rate surpassing Moore's law. Current and upcoming diffraction limited and fully coherent X-ray beam sources, including multi-bend achromat based synchrotron sources and high repetition rate X-ray free electron lasers, puts increasingly stringent requirements on stability and accuracy of X-ray optics systems. Parasitic motion errors at sub-micro radian scale in beam transport and beam conditioning optics can lead to significant loss of coherence and brightness delivered from source to experiment. To address this challenge, we incorporated optical metrology based on interferometry and differential wavefront sensing as part of the X-ray optics motion control system. A prototype X-ray optics system was constructed following the optical layout of a tunable X-ray cavity. On-line interferometric metrology enabled dynamical feedback to a motion control system to track and compensate for motion errors. The system achieved sub-microradian scale performance, as multiple optical elements are synchronously and continuously adjusted. This first proof of principle measurement demonstrated both the potential and necessity of incorporating optical metrology as part of the motion control architecture for large scale X-ray optical systems such as monochromators, delay lines, and in particular, X-ray cavity systems to enable the next generation cavity-based X-ray free electron lasers.

physics.optics↗

Decays of $1^{-+}$ Charmoniumlike Hybrid

By extracting the transition amplitudes, we give the first lattice QCD prediction of the two-body decay partial widths of the $1^{-+}$ charmoniumlike hybrid $η_{c1}$. Given the calculated mass value $m_{η_{c1}}=4.329(36)$ GeV, the $η_{c1}$ decay is dominated by the open charm modes $D_1\bar{D}$, $D^*\bar{D}$ and $D^*\bar{D}^*$ with partial widths of $258(133)$ MeV, $88(18)$ MeV and $150(118)$ MeV, respectively. The coupling of $η_{c1}$ to $χ_{c1}$ plus a flavor singlet pseudoscalar is not small, but $χ_{c1}η$ decay is suppressed by the small $η-η'$ mixing angle. The partial width of $η_{c1}\to η_cη'$ is estimated to be around 1 MeV. We suggest experiments to search for $η_{c1}$ in the $P$-wave $D^*\bar{D}$ and $D^*\bar{D}^*$ systems. Especially, the polarization of $D^*\bar{D}^*$ can be used to distinguish the $1^{-+}$ product (total spin $S=1$) from $1^{--}$ products ($S=0$).

hep-lat↗

Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domain

Existing quality enhancement methods for compressed images focus on aligning the enhancement domain with the raw domain to yield realistic images. However, these methods exhibit a pervasive enhancement bias towards the compression domain, inadvertently regarding it as more realistic than the raw domain. This bias makes enhanced images closely resemble their compressed counterparts, thus degrading their perceptual quality. In this paper, we propose a simple yet effective method to mitigate this bias and enhance the quality of compressed images. Our method employs a conditional discriminator with the compressed image as a key condition, and then incorporates a domain-divergence regularization to actively distance the enhancement domain from the compression domain. Through this dual strategy, our method enables the discrimination against the compression domain, and brings the enhancement domain closer to the raw domain. Comprehensive quality evaluations confirm the superiority of our method over other state-of-the-art methods without incurring inference overheads.

cs.CV↗

HCPM: Hierarchical Candidates Pruning for Efficient Detector-Free Matching

Deep learning-based image matching methods play a crucial role in computer vision, yet they often suffer from substantial computational demands. To tackle this challenge, we present HCPM, an efficient and detector-free local feature-matching method that employs hierarchical pruning to optimize the matching pipeline. In contrast to recent detector-free methods that depend on an exhaustive set of coarse-level candidates for matching, HCPM selectively concentrates on a concise subset of informative candidates, resulting in fewer computational candidates and enhanced matching efficiency. The method comprises a self-pruning stage for selecting reliable candidates and an interactive-pruning stage that identifies correlated patches at the coarse level. Our results reveal that HCPM significantly surpasses existing methods in terms of speed while maintaining high accuracy. The source code will be made available upon publication.

cs.CV↗

Tuning-Free Image Customization with Image and Text Guidance

Despite significant advancements in image customization with diffusion models, current methods still have several limitations: 1) unintended changes in non-target areas when regenerating the entire image; 2) guidance solely by a reference image or text descriptions; and 3) time-consuming fine-tuning, which limits their practical application. In response, we introduce a tuning-free framework for simultaneous text-image-guided image customization, enabling precise editing of specific image regions within seconds. Our approach preserves the semantic features of the reference image subject while allowing modification of detailed attributes based on text descriptions. To achieve this, we propose an innovative attention blending strategy that blends self-attention features in the UNet decoder during the denoising process. To our knowledge, this is the first tuning-free method that concurrently utilizes text and image guidance for image customization in specific regions. Our approach outperforms previous methods in both human and quantitative evaluations, providing an efficient solution for various practical applications, such as image synthesis, design, and creative photography.

cs.CV↗

Form factor for Dalitz decays from $J/ψ$ to light pseudoscalars

We calculate the form factor $M(q^2)$ for the Dalitz decay $J/ψ\to γ^*(q^2)η_{(N_f=1)}$ with $η_{(N_f)}$ being the SU($N_f$) flavor singlet pseudoscalar meson. The difference among the partial widths $Γ(J/ψ\to γη_{(N_f)})$ at different $N_f$ can be attributed in part to the $\mathbf{U}_A(1)$ anomaly that induces a $N_f$ scaling. $M(q^2)$'s in $N_f=1,2$ are both well described by the single pole model $M(q^2)=M(0)/(1-q^2/Λ^2)$. Combined with the known experimental results of the Dalitz decays $J/ψ\to Pe^+e^-$, the pseudoscalar mass $m_P$ dependence of the pole parameter $Λ$ is approximated by $Λ(m_P^2)=Λ_1(1-m_P^2/Λ_2^2)$ with $Λ_1=2.64(4)~\mathrm{GeV}$ and $Λ_2=2.97(33)~\mathrm{GeV}$. These results provide inputs for future theoretical and experimental studies on the Dalitz decays $J/ψ\to Pe^+e^-$.

hep-lat↗

Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses

Matrix sensing problems exhibit pervasive non-convexity, plaguing optimization with a proliferation of suboptimal spurious solutions. Avoiding convergence to these critical points poses a major challenge. This work provides new theoretical insights that help demystify the intricacies of the non-convex landscape. In this work, we prove that under certain conditions, critical points sufficiently distant from the ground truth matrix exhibit favorable geometry by being strict saddle points rather than troublesome local minima. Moreover, we introduce the notion of higher-order losses for the matrix sensing problem and show that the incorporation of such losses into the objective function amplifies the negative curvature around those distant critical points. This implies that increasing the complexity of the objective function via high-order losses accelerates the escape from such critical points and acts as a desirable alternative to increasing the complexity of the optimization problem via over-parametrization. By elucidating key characteristics of the non-convex optimization landscape, this work makes progress towards a comprehensive framework for tackling broader machine learning objectives plagued by non-convexity.

math.OC↗

Manin triples associated to $n$-Lie bialgebras

In this paper, we study the Manin triples associated to $n$-Lie bialgebras. We introduce the concept of operad matrices for $n$-Lie bialgebras. In particular, by studying a special case of operad matrices, it leads to the notion of local cocycle $n$-Lie bialgebras. Furthermore, we establish a one-to-one correspondence between the double of $n$-Lie bialgebras and Manin triples of $n$-Lie algebras.

math.RA↗

Tackling the Non-IID Issue in Heterogeneous Federated Learning by Gradient Harmonization

Federated learning (FL) is a privacy-preserving paradigm for collaboratively training a global model from decentralized clients. However, the performance of FL is hindered by non-independent and identically distributed (non-IID) data and device heterogeneity. In this work, we revisit this key challenge through the lens of gradient conflicts on the server side. Specifically, we first investigate the gradient conflict phenomenon among multiple clients and reveal that stronger heterogeneity leads to more severe gradient conflicts. To tackle this issue, we propose FedGH, a simple yet effective method that mitigates local drifts through Gradient Harmonization. This technique projects one gradient vector onto the orthogonal plane of the other within conflicting client pairs. Extensive experiments demonstrate that FedGH consistently enhances multiple state-of-the-art FL baselines across diverse benchmarks and non-IID scenarios. Notably, FedGH yields more significant improvements in scenarios with stronger heterogeneity. As a plug-and-play module, FedGH can be seamlessly integrated into any FL framework without requiring hyperparameter tuning.

cs.LG↗

Molecular intercalation in the van der Waals antiferromagnets FePS3 and NiPS3

We have performed electrochemical treatment of the van der Waals antiferromagnetic materials FePS$_3$ and NiPS$_3$ with the ionic liquid EMIM-BF$_4$, achieving significant molecular intercalation. Mass analysis of the intercalated compounds, EMIM$_x$-FePS$_3$ and EMIM$_x$-NiPS$_3$, indicated respective intercalation levels, $x$, of approximately 27\% and 37\%, and X-ray diffraction measurements demonstrated a massive (over 50\%) enhancement of the $c$-axis lattice parameters. To investigate the consequences of these changes for the magnetic properties, we performed magnetic susceptibility and $^{31}$P nuclear magnetic resonance (NMR) studies of both systems. For EMIM$_x$-FePS$_3$, intercalation reduces the magnetic ordering temperature from $T_N = 120$~K to 78~K, and we find a spin gap in the antiferromagnetic phase that drops from 45~K to 30~K. For EMIM$_x$-NiPS$_3$, the ordering temperature is almost unaffected (changing from 148~K to 145~K), but a change towards nearly isotropic spin fluctuations suggests an alteration of the magnetic Hamiltonian. Such relatively modest changes, given that the huge extension of the $c$ axes is expected to cause a very strong suppression any interlayer interactions, point unequivocally to the conclusion that the magnetic properties of both parent compounds are determined solely by two-dimensional (2D), intralayer physics. The changes in transition temperatures and low-temperature spin dynamics in both compounds therefore indicate that intercalation also results in a significant modulation of the intralayer magnetic interactions, which we propose is due to charge doping and localization on the P sites. Our study offers chemical intercalation with ionic liquids as an effective method to control not only the interlayer but also the intralayer interactions in quasi-2D magnetic materials.

cond-mat.str-el↗

Prediction of novel ordered phases in U-X (X= Zr, Sc, Ti, V, Cr, Y, Nb, Mo, Hf, Ta, W) binary alloys under high pressure

U-based binary alloys have been widely adopted in fast nuclear reactors, but their stability under extreme conditions of high-pressure is almost unknown, mounting up to latent risk in applications. Here, possible ordered phases in U-Zr system up to 200 GPa are comprehensively investigated by unbiased first-principles structure prediction. Stable U2Zr, metastable U3Zr and U4Zr phases are discovered for the first time, which exhibit strong stability under compression. They all are metallic, with 5f electrons of uranium dominating the electronic density of states near the Fermi level. Prominent ionic interactions between U and Zr atoms, as well as covalent interactions between adjacent uranium atoms, are found. The same strategy is applied to explore the stability of ordered phases in other U-based binary transition metal alloys, U-X (X= Sc, Ti, V, Cr, Y, Nb, Mo, Hf, Ta, W). Stable and metastable ordered phases similar to U-Zr alloy are unveiled, all with similar electronic structures. For these alloys, we find that the structure of U2X (X=Zr, Ti, Hf) hosts a unique hybrid phase transition similar to U2Nb, which is a superposition of a first-order transition and a second-order transition. The prediction of these novel phases not only refutes the stability of the long-believed ordered phase I4/mmm-U2Mo, but also rewrites the phase diagrams of U-X (X= Zr, Sc, Ti, V, Cr, Nb, Mo, Hf, Ta) alloys under high pressure. All of these findings promote our understanding of the high-pressure behavior of the broad category of U-based binary alloys with transition metals.

cond-mat.mtrl-sci↗

Universal Metallic Surface States in Electride

Robust metallic surface states (MSS) of topological insulator (TI) against imperfections and perturbations are important in broad applications such as chemical catalysis and quantum computing. Unfortunately, they are suffered from the narrow band gap that can be accessed. Searching for MSS with large bulk band gap beyond conventional TIs becomes a quest. In this work, inspired by the adiabatic connection principle in real space, we identify that all electrides, a new class of emerging materials, must host robust and universal MSS that resists any disturbances, in spite of the fact that some of them could be classified as trivial in standard topology theory. This counterintuitive property is traced to the specific charge localization-delocalization change intrinsic to electride when approaching the crystalline surface or interface, which is a kind of interstice-centered to atom-centered transition in the real-space topology of the charge density distribution, and is sharply different from the band inversion in the standard topology theory. The new mechanism circumvents the obstacle that limits the band gap of TI. Robust and universal MSS in an electride that conventionally-determined as trivial but with a colossal band gap beyond 6.13 eV are demonstrated. This gap size is about 6-fold larger than the highest record of known "wide-gap" TIs, thus opens up new avenues to universal MSS with gigantic bulk gap.

cond-mat.mtrl-sci↗

NMR evidence of spinon localization in kagome antiferromagnet YCu$_3$(OH)$_6$Br$_2$[Br$_{1-x}$(OH)$_x$]

We performed nuclear magnetic resonance studies on a kagome antiferromagnet YCu$_3$(OH)$_6$Br$_2$[Br$_{1-x}$(OH)$_{x}$]. No significant NMR spectral broadening is found in the Br center peak from 1 K down to 0.05 K, indicating absence of static antiferromagnetic ordering. In contrast to signatures of dominant 2D kagome antiferromagnetic fluctuations at temperature above 30 K, both the Knight shift $K_{\rm{n}}$ and the spin-lattice relaxation rate $1/T_{1}$ increase when the sample is cooled from 30 K to 8 K, which can be attributed to the scattering of spin excitations by strong non-magnetic impurities. Unusually, a hump is observed in $K_{\rm{n}}$ and $1/T_{2}$ close to 2 K (far below the exchange energy), which indicates the existence of excitations with a large density of states close to zero energy. These phenomena are reproduced by a mean-field simulation of Heisenberg model with bond-dependent exchange interactions, where the sign fluctuations in the spinon kinetic terms caused by impurities result in localization of spinons and an almost flat band close to the Fermi energy.

cond-mat.str-el↗

Field-induced phase transitions and quantum criticality in a honeycomb antiferromagnet Na3Co2SbO6

We performed 23Na NMR measurements on a single-domain crystal of the Kitaev material Na3Co2SbO6, with magnetic field applied along the crystalline a axis. A positive Curie-Weiss constant is obtained from the NMR Knight shift, which suggests the existence of ferromagnetic exchange couplings. The antiferromagnetic ordering is found to be suppressed at a field of 1.9 T. Inside the ordered phase, our data reveal two additional phase transitions. At 1.9 T, the spin-lattice relaxation rate 1/23T1 establishes a quantum critical behavior at high temperatures. However, at low temperatures, a gapped behavior is observed at the critical field, which suggests a weakly first-order transition instead and a possible field-induced quantum spin liquid. Our results reveal complex microscopic interactions in the system, which may help to search for possible quantum spin liquids.

cond-mat.str-el↗

Regularized lattice Boltzmann method based maximum principle and energy stability preserving finite-difference scheme for the Allen-Cahn equation

The Allen-Cahn equation (ACE) inherently possesses two crucial properties: the maximum principle and the energy dissipation law. Preserving these two properties at the discrete level is also necessary in the numerical methods for the ACE. In this paper, unlike the traditional top-down macroscopic numerical schemes which discretize the ACE directly, we first propose a novel bottom-up mesoscopic regularized lattice Boltzmann method based macroscopic numerical scheme for d (=1, 2, 3)-dimensional ACE, where the DdQ(2d+1) [(2d+1) discrete velocities in d-dimensional space] lattice structure is adopted. In particular, the proposed macroscopic numerical scheme has a second-order accuracy in space, and can also be viewd as an implicit-explicit finite-difference scheme for the ACE, in which the nonlinear term is discretized semi-implicitly, the temporal derivative and dissipation term of the ACE are discretized by using the explicit Euler method and second-order central difference method, respectively. Then we also demonstrate that the proposed scheme can preserve the maximum bound principle and the original energy dissipation law at the discrete level under some conditions. Finally, some numerical experiments are conducted to validate our theoretical analysis.

math.NA↗