Emergence of Crystalline Few-body Correlations in Mass-imbalanced Fermi Polarons

Kavli Affiliate: Cheng Peng | First 5 Authors: Ruijin Liu, Cheng Peng, Xiaoling Cui, , | Summary: Identifying few-body correlations is an efficient tool to solve complex many-body problems. Polarons, interpolating between few- and many-body systems, serve as an ideal platform to achieve the goal. In this work, we reveal the emergence of various crystalline […]


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On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error

Kavli Affiliate: Yi Zhou | First 5 Authors: Quang Minh Nguyen, Hoang H. Nguyen, Yi Zhou, Lam M. Nguyen, | Summary: We study the Unbalanced Optimal Transport (UOT) between two measures of possibly different masses with at most $n$ components, where marginal constraints of the standard Optimal Transport (OT) are relaxed via Kullback-Leibler divergence with […]


Continue.. On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error

On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error

Kavli Affiliate: Yi Zhou | First 5 Authors: Quang Minh Nguyen, Hoang H. Nguyen, Yi Zhou, Lam M. Nguyen, | Summary: We study the Unbalanced Optimal Transport (UOT) between two measures of possibly different masses with at most $n$ components, where the marginal constraints of standard Optimal Transport (OT) are relaxed via Kullback-Leibler divergence with […]


Continue.. On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error

Crafting Better Contrastive Views for Siamese Representation Learning

Kavli Affiliate: Zheng Zhu | First 5 Authors: Xiangyu Peng, Kai Wang, Zheng Zhu, Mang Wang, Yang You | Summary: Recent self-supervised contrastive learning methods greatly benefit from the Siamese structure that aims at minimizing distances between positive pairs. For high performance Siamese representation learning, one of the keys is to design good contrastive pairs. […]


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Unsupervised Long-Term Person Re-Identification with Clothes Change

Kavli Affiliate: Cheng Peng | First 5 Authors: Mingkun Li, Shupeng Cheng, Peng Xu, Xiatian Zhu, Chun-Guang Li | Summary: We investigate unsupervised person re-identification (Re-ID) with clothes change, a new challenging problem with more practical usability and scalability to real-world deployment. Most existing re-id methods artificially assume the clothes of every single person to […]


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Universal tetramer and pentamer in two-dimensional fermionic mixtures

Kavli Affiliate: Cheng Peng | First 5 Authors: Ruijin Liu, Cheng Peng, Xiaoling Cui, , | Summary: We study the emergence of universal tetramer and pentamer bound states in the two-dimensional $(N+1)$ system, which consists $N$ identical heavy fermions interacting with a light atom. We show that the critical heavy-light mass ratio to support a […]


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Ferromagnetic resonance modulation in $d$-wave superconductor/ferromagnetic insulator bilayer systems

Kavli Affiliate: Mamoru Matsuo | First 5 Authors: Yuya Ominato, Ai Yamakage, Takeo Kato, Mamoru Matsuo, | Summary: We investigate ferromagnetic resonance (FMR) modulation in $d$-wave superconductor (SC)/ferromagnetic insulator (FI) bilayer systems theoretically. The modulation of the Gilbert damping in these systems reflects the existence of nodes in the $d$-wave SC and shows power-law decay […]


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BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Kavli Affiliate: Zheng Zhu | First 5 Authors: Junjie Huang, Guan Huang, Zheng Zhu, Yun Ye, Dalong Du | Summary: Autonomous driving perceives its surroundings for decision making, which is one of the most complex scenarios in visual perception. The success of paradigm innovation in solving the 2D object detection task inspires us to seek […]


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Accelerated Proximal Alternating Gradient-Descent-Ascent for Nonconvex Minimax Machine Learning

Kavli Affiliate: Yi Zhou | First 5 Authors: Ziyi Chen, Shaocong Ma, Yi Zhou, , | Summary: Alternating gradient-descent-ascent (AltGDA) is an optimization algorithm that has been widely used for model training in various machine learning applications, which aims to solve a nonconvex minimax optimization problem. However, the existing studies show that it suffers from […]


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