4 papers
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…
Lie Symmetry Net: Preserving Conservation Laws in Modelling Financial Market Dynamics via Differential Equations
Xuelian Jiang, Tongtian Zhu, Yingxiang Xu +3
This paper employs a novel Lie symmetries-based framework to model the intrinsic symmetries within financial market. Specifically, we introduce Lie symmetry net (LSN), which charac…
Topology-aware Generalization of Decentralized SGD
Tongtian Zhu, Fengxiang He, Lan Zhang +3
This paper studies the algorithmic stability and generalizability of decentralized stochastic gradient descent (D-SGD). We prove that the consensus model learned by D-SGD is $\math…