most citedTopology optimization based on moving deformable components: A new computational framework

1.2k citations · 1.2k across the 1 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory

Wenliang Zhong, Haoyu Tang, Qinghai Zheng +3

The rapid evolution of deep learning and large language models has led to an exponential growth in the demand for training data, prompting the development of Dataset Distillation m…

cs.IR2024

Denoising Time Cycle Modeling for Recommendation

Sicong Xie, Qunwei Li, Weidi Xu +3

Recently, modeling temporal patterns of user-item interactions have attracted much attention in recommender systems. We argue that existing methods ignore the variety of temporal p…

cs.IR2023

COUPA: An Industrial Recommender System for Online to Offline Service Platforms

Sicong Xie, Binbin Hu, Fengze Li +4

Aiming at helping users locally discovery retail services (e.g., entertainment and dinning), Online to Offline (O2O) service platforms have become popular in recent years, which gr…

cs.LG202321 cited

Edge-cloud Collaborative Learning with Federated and Centralized Features

Zexi Li, Qunwei Li, Yi Zhou +3

Federated learning (FL) is a popular way of edge computing that doesn't compromise users' privacy. Current FL paradigms assume that data only resides on the edge, while cloud serve…

cs.CE20141.2k cited

Topology optimization based on moving deformable components: A new computational framework

Xu Guo, Weisheng Zhang, Wenliang Zhong

In the present work, a new computational framework for structural topology optimization based on the concept of moving deformable components is proposed. Compared with the traditio…