309 citations · 749 across the 34 of their papers we have counts for
8 papers · 1 filter
Continuation Path Learning for Homotopy Optimization
Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang +1
Homotopy optimization is a traditional method to deal with a complicated optimization problem by solving a sequence of easy-to-hard surrogate subproblems. However, this method can…
Pareto Set Learning for Neural Multi-objective Combinatorial Optimization
Xi Lin, Zhiyuan Yang, Qingfu Zhang
Multiobjective combinatorial optimization (MOCO) problems can be found in many real-world applications. However, exactly solving these problems would be very challenging, particula…
Self-supervised Symmetric Nonnegative Matrix Factorization
Yuheng Jia, Hui Liu, Junhui Hou +2
Symmetric nonnegative matrix factorization (SNMF) has demonstrated to be a powerful method for data clustering. However, SNMF is mathematically formulated as a non-convex optimizat…
Clustering Ensemble Meets Low-rank Tensor Approximation
Yuheng Jia, Hui Liu, Junhui Hou +1
This paper explores the problem of clustering ensemble, which aims to combine multiple base clusterings to produce better performance than that of the individual one. The existing…
Controllable Pareto Multi-Task Learning
Xi Lin, Zhiyuan Yang, Qingfu Zhang +1
A multi-task learning (MTL) system aims at solving multiple related tasks at the same time. With a fixed model capacity, the tasks would be conflicted with each other, and the syst…
Multi-View Spectral Clustering Tailored Tensor Low-Rank Representation
Yuheng Jia, Hui Liu, Junhui Hou +2
This paper explores the problem of multi-view spectral clustering (MVSC) based on tensor low-rank modeling. Unlike the existing methods that all adopt an off-the-shelf tensor low-r…
Pareto Multi-Task Learning
Xi Lin, Hui-Ling Zhen, Zhenhua Li +2
Multi-task learning is a powerful method for solving multiple correlated tasks simultaneously. However, it is often impossible to find one single solution to optimize all the tasks…
Nonlinear Collaborative Scheme for Deep Neural Networks
Hui-Ling Zhen, Xi Lin, Alan Z. Tang +3
Conventional research attributes the improvements of generalization ability of deep neural networks either to powerful optimizers or the new network design. Different from them, in…