50 citations · 84 across the 7 of their papers we have counts for
7 papers
Nonparametric Teaching for Multiple Learners
Chen Zhang, Xiaofeng Cao, Weiyang Liu +2
We study the problem of teaching multiple learners simultaneously in the nonparametric iterative teaching setting, where the teacher iteratively provides examples to the learner fo…
Pairwise Similarity Learning is SimPLE
Yandong Wen, Weiyang Liu, Yao Feng +5
In this paper, we focus on a general yet important learning problem, pairwise similarity learning (PSL). PSL subsumes a wide range of important applications, such as open-set face…
Nonparametric Iterative Machine Teaching
Chen Zhang, Xiaofeng Cao, Weiyang Liu +2
In this paper, we consider the problem of Iterative Machine Teaching (IMT), where the teacher provides examples to the learner iteratively such that the learner can achieve fast co…
Performing SU() operations and rudimentary algorithms in a superconducting transmon qudit for and
Pei Liu, Ruixia Wang, Jing-Ning Zhang +11
Quantum computation architecture based on -level systems, or qudits, has attracted considerable attention recently due to their enlarged Hilbert space. Extensive theoretical and…
MeshDiffusion: Score-based Generative 3D Mesh Modeling
Zhen Liu, Yao Feng, Michael J. Black +3
We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other…
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap
Weiyang Liu, Longhui Yu, Adrian Weller +1
The neural collapse (NC) phenomenon describes an underlying geometric symmetry for deep neural networks, where both deeply learned features and classifiers converge to a simplex eq…