47 citations · 195 across the 39 of their papers we have counts for
28 papers · 1 filter
Drawback of Enforcing Equivariance and its Compensation via the Lens of Expressive Power
Yuzhu Chen, Tian Qin, Xinmei Tian +2
Equivariant neural networks encode the intrinsic symmetry of data as an inductive bias, which has achieved impressive performance in wide domains. However, the understanding to the…
DICE: Data Influence Cascade in Decentralized Learning
Tongtian Zhu, Wenhao Li, Can Wang +1
Decentralized learning offers a promising approach to crowdsource data consumptions and computational workloads across geographically distributed compute interconnected through pee…
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing
Zhihao Hu, Yiran Xu, Mengnan Du +3
With the increasing penetration of machine learning applications in critical decision-making areas, calls for algorithmic fairness are more prominent. Although there have been vari…
Heterogeneous Multi-Task Gaussian Cox Processes
Feng Zhou, Quyu Kong, Zhijie Deng +3
This paper presents a novel extension of multi-task Gaussian Cox processes for modeling multiple heterogeneous correlated tasks jointly, e.g., classification and regression, via mu…
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
Tongtian Zhu, Fengxiang He, Kaixuan Chen +2
Decentralized stochastic gradient descent (D-SGD) allows collaborative learning on massive devices simultaneously without the control of a central server. However, existing theorie…
Improving Heterogeneous Model Reuse by Density Estimation
Anke Tang, Yong Luo, Han Hu +5
This paper studies multiparty learning, aiming to learn a model using the private data of different participants. Model reuse is a promising solution for multiparty learning, assum…