5 papers
Adaptive multi-gradient methods for quasiconvex vector optimization and applications to multi-task learning
Nguyen Anh Minh, Le Dung Muu, Tran Ngoc Thang
We present an adaptive step-size method, which does not include line-search techniques, for solving a wide class of nonconvex multiobjective programming problems on an unbounded co…
A Hyper-Transformer model for Controllable Pareto Front Learning with Split Feasibility Constraints
Tran Anh Tuan, Nguyen Viet Dung, Tran Ngoc Thang
Controllable Pareto front learning (CPFL) approximates the Pareto solution set and then locates a Pareto optimal solution with respect to a given reference vector. However, decisio…
A Novel Approach in Solving Stochastic Generalized Linear Regression via Nonconvex Programming
Vu Duc Anh, Tran Anh Tuan, Tran Ngoc Thang +1
Generalized linear regressions, such as logistic regressions or Poisson regressions, are long-studied regression analysis approaches, and their applications are widely employed in…
Building Footprint Extraction in Dense Areas using Super Resolution and Frame Field Learning
Vuong Nguyen, Anh Ho, Duc-Anh Vu +2
Despite notable results on standard aerial datasets, current state-of-the-arts fail to produce accurate building footprints in dense areas due to challenging properties posed by th…
A neurodynamic approach for a class of pseudoconvex semivectorial bilevel optimization problems
Tran Ngoc Thang, Dao Minh Hoang, Nguyen Viet Dung
The article proposes an exact approach to find the global solution of a nonconvex semivectorial bilevel optimization problem, where the objective functions at each level are pseudo…