1k citations · 1.6k across the 54 of their papers we have counts for
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Leave Zero Out: Towards a No-Cross-Validation Approach for Model Selection
Weikai Li, Chuanxing Geng, Songcan Chen
As the main workhorse for model selection, Cross Validation (CV) has achieved an empirical success due to its simplicity and intuitiveness. However, despite its ubiquitous role, CV…
With False Friends Like These, Who Can Notice Mistakes?
Lue Tao, Lei Feng, Jinfeng Yi +1
Adversarial examples crafted by an explicit adversary have attracted significant attention in machine learning. However, the security risk posed by a potential false friend has bee…
Convex Subspace Clustering by Adaptive Block Diagonal Representation
Yunxia Lin, Songcan Chen
Subspace clustering is a class of extensively studied clustering methods where the spectral-type approaches are its important subclass. Its key first step is to desire learning a r…
Unsupervised Domain Adaptation with Progressive Adaptation of Subspaces
Weikai Li, Songcan Chen
Unsupervised Domain Adaptation (UDA) aims to classify unlabeled target domain by transferring knowledge from labeled source domain with domain shift. Most of the existing UDA metho…
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization
Feihu Huang, Songcan Chen, Heng Huang
In this paper, we propose a faster stochastic alternating direction method of multipliers (ADMM) for nonconvex optimization by using a new stochastic path-integrated differential e…
Accelerated Stochastic Gradient-free and Projection-free Methods
Feihu Huang, Lue Tao, Songcan Chen
In the paper, we propose a class of accelerated stochastic gradient-free and projection-free (a.k.a., zeroth-order Frank-Wolfe) methods to solve the constrained stochastic and fini…
A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label Learning
Xiang Li, Songcan Chen
In reality, learning from multi-view multi-label data inevitably confronts three challenges: missing labels, incomplete views, and non-aligned views. Existing methods mainly concer…
A Centroid Auto-Fused Hierarchical Fuzzy c-Means Clustering
Yunxia Lin, Songcan Chen
Like k-means and Gaussian Mixture Model (GMM), fuzzy c-means (FCM) with soft partition has also become a popular clustering algorithm and still is extensively studied. However, the…
Expand Globally, Shrink Locally: Discriminant Multi-label Learning with Missing Labels
Zhongchen Ma, Songcan Chen
In multi-label learning, the issue of missing labels brings a major challenge. Many methods attempt to recovery missing labels by exploiting low-rank structure of label matrix. How…
Unsupervised Domain Adaptation Through Transferring both the Source-Knowledge and Target-Relatedness Simultaneously
Qing Tian, Yanan Zhu, Chuang Ma +1
Unsupervised domain adaptation (UDA) is an emerging research topic in the field of machine learning and pattern recognition, which aims to help the learning of unlabeled target dom…
A Multi-view Perspective of Self-supervised Learning
Chuanxing Geng, Zhenghao Tan, Songcan Chen
As a newly emerging unsupervised learning paradigm, self-supervised learning (SSL) recently gained widespread attention, which usually introduces a pretext task without manual anno…