5 citations · 9 across the 4 of their papers we have counts for
4 papers
The Inductive Bias of Flatness Regularization for Deep Matrix Factorization
Khashayar Gatmiry, Zhiyuan Li, Ching-Yao Chuang +3
Recent works on over-parameterized neural networks have shown that the stochasticity in optimizers has the implicit regularization effect of minimizing the sharpness of the loss fu…
Learning Empirical Bregman Divergence for Uncertain Distance Representation
Zhiyuan Li, Ziru Liu, Anna Zou +1
Deep metric learning techniques have been used for visual representation in various supervised and unsupervised learning tasks through learning embeddings of samples with deep netw…
Learning Generalized Hybrid Proximity Representation for Image Recognition
Zhiyuan Li, Anca Ralescu
Recently, deep metric learning techniques received attention, as the learned distance representations are useful to capture the similarity relationship among samples and further im…
Implicit Regularization and Convergence for Weight Normalization
Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren +5
Normalization methods such as batch [Ioffe and Szegedy, 2015], weight [Salimansand Kingma, 2016], instance [Ulyanov et al., 2016], and layer normalization [Baet al., 2016] have bee…