activity
20162022
most citedPhase transition of the q-state clock model: duality and tensor renormalization

44 citations · 88 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG20223 cited

Low-Interception Waveform: To Prevent the Recognition of Spectrum Waveform Modulation via Adversarial Examples

Haidong Xie, Jia Tan, Xiaoying Zhang +5

Deep learning is applied to many complex tasks in the field of wireless communication, such as modulation recognition of spectrum waveforms, because of its convenience and efficien…

cs.CV202126 cited

Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches

Nan Ji, YanFei Feng, Haidong Xie +2

The security of object detection systems has attracted increasing attention, especially when facing adversarial patch attacks. Since patch attacks change the pixels in a restricted…

cs.LG20202 cited

Blind Adversarial Training: Balance Accuracy and Robustness

Haidong Xie, Xueshuang Xiang, Naijin Liu +1

Adversarial training (AT) aims to improve the robustness of deep learning models by mixing clean data and adversarial examples (AEs). Most existing AT approaches can be grouped int…

math.ST2018

Statistical inference and feasibility determination: a nonasymptotic approach

Ying Zhu

We develop non-asymptotically justified methods for hypothesis testing about the dimensional coefficients in (possibly nonlinear) regression models. Given a function $h…

cond-mat.str-el201712 cited

Analytic continuation with Padé decomposition

Xing-Jie Han, Hai-Jun Liao, Hai-Dong Xie +3

The ill-posed analytic continuation problem for Green's functions or self-energies can be done using the Padé rational polynomial approximation. However, to extract accurate result…

cond-mat.stat-mech201744 cited

Phase transition of the q-state clock model: duality and tensor renormalization

Jing Chen, Hai-Jun Liao, Hai-Dong Xie +6

We investigate the critical behavior and the duality property of the ferromagnetic -state clock model on the square lattice based on the tensor-network formalism. From the entan…