11 citations · 22 across the 5 of their papers we have counts for
5 papers
OmniTabBench: Mapping the Empirical Frontiers of GBDTs, Neural Networks, and Foundation Models for Tabular Data at Scale
Dihong Jiang, Ruoqi Cao, Zhiyuan Dang +8
While traditional tree-based ensemble methods have long dominated tabular tasks, deep neural networks and emerging foundation models have challenged this primacy, yet no consensus…
AI Pangaea: Unifying Intelligence Islands for Adapting Myriad Tasks
Jianlong Chang, Haixin Wang, Zhiyuan Dang +11
The pursuit of artificial general intelligence continuously demands generalization in one model across myriad tasks, even those not seen before. However, current AI models are isol…
Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm
Qingsong Zhang, Bin Gu, Zhiyuan Dang +2
Vertical federated learning (VFL) attracts increasing attention due to the emerging demands of multi-party collaborative modeling and concerns of privacy leakage. A complete list o…
Doubly Contrastive Deep Clustering
Zhiyuan Dang, Cheng Deng, Xu Yang +1
Deep clustering successfully provides more effective features than conventional ones and thus becomes an important technique in current unsupervised learning. However, most deep cl…
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data
Bin Gu, Zhiyuan Dang, Xiang Li +1
In a lot of real-world data mining and machine learning applications, data are provided by multiple providers and each maintains private records of different feature sets about com…