87 citations · 467 across the 21 of their papers we have counts for
21 papers
Exploring the mass and redshift dependence of the cluster pressure profile with stacks on thermal SZ maps
Denis Tramonte, Yin-Zhe Ma, Ziang Yan +11
We provide novel constraints on the parameters defining the universal pressure profile (UPP) within clusters of galaxies, and explore their dependence on the cluster mass and redsh…
An End-to-End Framework for Marketing Effectiveness Optimization under Budget Constraint
Ziang Yan, Shusen Wang, Guorui Zhou +2
Online platforms often incentivize consumers to improve user engagement and platform revenue. Since different consumers might respond differently to incentives, individual-level bu…
On constraining Cosmology and the Halo Mass Function with Weak Gravitational Lensing
Shiming Gu, Marc-Antoine Dor, Ludovic van Waerbeke +4
The discrepancy between the weak lensing (WL) and the {\it Planck} measurements of has been a subject of several studies. These studies tend to show that a suppression of the…
KiDS-1000: cross-correlation with Planck cosmic microwave background lensing and intrinsic alignment removal with self-calibration
Ji Yao, Huanyuan Shan, Pengjie Zhang +11
Galaxy shear - cosmic microwave background (CMB) lensing convergence cross-correlations contain additional information on cosmology to auto-correlations. While being immune to cert…
Dynamical cluster masses from photometric surveys
Omar Contigiani, Henk Hoekstra, Margot M. Brouwer +5
The masses of galaxy clusters can be measured using data obtained exclusively from wide photometric surveys in one of two ways: directly from the amplitude of the weak lensing sign…
Cosmic star formation history with tomographic cosmic infrared background-galaxy cross-correlation
Ziang Yan, Ludovic van Waerbeke, Angus H. Wright +5
In this work, we probe the star formation history of the Universe using tomographic cross-correlation between the cosmic infrared background (CIB) and galaxy samples. The galaxy sa…
Joint constraints on cosmology and the impact of baryon feedback: combining KiDS-1000 lensing with the thermal Sunyaev-Zeldovich effect from Planck and ACT
Tilman Tröster, Alexander J. Mead, Catherine Heymans +13
We conduct a pseudo- analysis of the tomographic cross-correlation between 1000 deg of weak lensing data from the Kilo-Degree Survey (KiDS-1000) and the thermal Sunyaev…
Probing galaxy bias and intergalactic gas pressure with KiDS Galaxies-tSZ-CMB lensing cross-correlations
Ziang Yan, Ludovic van Waerbeke, Tilman Tröster +14
We constrain the redshift dependence of gas pressure bias (bias-weighted average electron pressure), which characterises the thermo…
Sill-Net: Feature Augmentation with Separated Illumination Representation
Haipeng Zhang, Zhong Cao, Ziang Yan +1
For visual object recognition tasks, the illumination variations can cause distinct changes in object appearance and thus confuse the deep neural network based recognition models.…
Learning Fast Approximations of Sparse Nonlinear Regression
Yuhai Song, Zhong Cao, Kailun Wu +2
The idea of unfolding iterative algorithms as deep neural networks has been widely applied in solving sparse coding problems, providing both solid theoretical analysis in convergen…
FMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention
Yiwen Sun, Yulu Wang, Kun Fu +4
Estimated time of arrival (ETA) is one of the most important services in intelligent transportation systems and becomes a challenging spatial-temporal (ST) data mining task in rece…
Adversarial Margin Maximization Networks
Ziang Yan, Yiwen Guo, Changshui Zhang
The tremendous recent success of deep neural networks (DNNs) has sparked a surge of interest in understanding their predictive ability. Unlike the human visual system which is able…
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
Ziang Yan, Yiwen Guo, Changshui Zhang
Unlike the white-box counterparts that are widely studied and readily accessible, adversarial examples in black-box settings are generally more Herculean on account of the difficul…
The Cosmology Large Angular Scale Surveyor Receiver Design
Jeffrey Iuliano, Joseph Eimer, Lucas Parker +42
The Cosmology Large Angular Scale Surveyor consists of four instruments performing a CMB polarization survey. Currently, the 40 GHz and first 90 GHz instruments are deployed and ob…
Design and characterization of the Cosmology Large Angular Scale Surveyor (CLASS) 93 GHz focal plane
Sumit Dahal, Aamir Ali, John W. Appel +44
The Cosmology Large Angular Scale Surveyor (CLASS) aims to detect and characterize the primordial B-mode signal and make a sample-variance-limited measurement of the optical depth…
Variable-delay Polarization Modulators for the CLASS Telescopes
Kathleen Harrington, Joseph Eimer, David T. Chuss +43
The search for inflationary primordial gravitational waves and the measurement of the optical depth to reionization, both through their imprint on the large angular scale correlati…
Deep Defense: Training DNNs with Improved Adversarial Robustness
Ziang Yan, Yiwen Guo, Changshui Zhang
Despite the efficacy on a variety of computer vision tasks, deep neural networks (DNNs) are vulnerable to adversarial attacks, limiting their applications in security-critical syst…
Zero-Shot Learning by Generating Pseudo Feature Representations
Jiang Lu, Jin Li, Ziang Yan +1
Zero-shot learning (ZSL) is a challenging task aiming at recognizing novel classes without any training instances. In this paper we present a simple but high-performance ZSL approa…
Weakly- and Semi-Supervised Object Detection with Expectation-Maximization Algorithm
Ziang Yan, Jian Liang, Weishen Pan +2
Object detection when provided image-level labels instead of instance-level labels (i.e., bounding boxes) during training is an important problem in computer vision, since large sc…
Neural Network Architecture Optimization through Submodularity and Supermodularity
Junqi Jin, Ziang Yan, Kun Fu +2
Deep learning models' architectures, including depth and width, are key factors influencing models' performance, such as test accuracy and computation time. This paper solves two p…
Optimizing Recurrent Neural Networks Architectures under Time Constraints
Junqi Jin, Ziang Yan, Kun Fu +2
Recurrent neural network (RNN)'s architecture is a key factor influencing its performance. We propose algorithms to optimize hidden sizes under running time constraint. We convert…