129 citations · 302 across the 20 of their papers we have counts for
4 papers · 1 filter
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks
Dennis Wei, Tian Gao, Yue Yu
This paper re-examines a continuous optimization framework dubbed NOTEARS for learning Bayesian networks. We first generalize existing algebraic characterizations of acyclicity to…
MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning
Lu Zhang, Mo Yu, Tian Gao +1
Multi-hop reasoning approaches over knowledge graphs infer a missing relationship between entities with a multi-hop rule, which corresponds to a chain of relationships. We extend e…
Proportional-Integral Projected Gradient Method for Model Predictive Control
Yue Yu, Purnanand Elango, Behçet Açikmeşe
Recently there has been an increasing interest in primal-dual methods for model predictive control (MPC), which require minimizing the (augmented) Lagrangian at each iteration. We…
RC Circuits based Distributed Conditional Gradient Method
Yue Yu, Behçet Açıkmeşe
We consider distributed optimization on undirected connected graphs. We propose a novel distributed conditional gradient method with (O(1/\sqrt{k})) convergence. Compared with exis…