1 citations · 1 across the 4 of their papers we have counts for
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Accelerated Algorithm for Sparse Regularized Partial Optimal Transport
Khoa Nguyen, Dung T. Nguyen, Thong Huynh +4
Partial Optimal Transport (POT) extends the classical optimal transport problem by relaxing the strict mass conservation constraint, enabling its use in a wide range of real-world…
Neural Autoregressive Flows for Markov Boundary Learning
Khoa Nguyen, Bao Duong, Viet Huynh +1
Recovering Markov boundary -- the minimal set of variables that maximizes predictive performance for a response variable -- is crucial in many applications. While recent advances i…
SGFusion: Stochastic Geographic Gradient Fusion in Federated Learning
Khoa Nguyen, Khang Tran, NhatHai Phan +3
This paper proposes Stochastic Geographic Gradient Fusion (SGFusion), a novel training algorithm to leverage the geographic information of mobile users in Federated Learning (FL).…
Sparse Partial Optimal Transport via Quadratic Regularization
Khang Tran, Khoa Nguyen, Anh Nguyen +7
Partial Optimal Transport (POT) has recently emerged as a central tool in various Machine Learning (ML) applications. It lifts the stringent assumption of the conventional Optimal…
Clustering-based Meta Bayesian Optimization with Theoretical Guarantee
Khoa Nguyen, Viet Huynh, Binh Tran +3
Bayesian Optimization (BO) is a well-established method for addressing black-box optimization problems. In many real-world scenarios, optimization often involves multiple functions…