38 citations · 80 across the 36 of their papers we have counts for
4 papers · 1 filter
Safeguarded Accelerated Adaptive Search under Unreliable Gradient Oracles
Shunzhi Zhang, Shichen Liao, Congying Han +1
From the probabilistic-model viewpoint, stochastic adaptive search can require any fraction of the predicted model reduction for acceptance. Classical backtracking with…
Relating Checkpoint Update Probabilities to Momentum Parameters in Single-Loop Variance Reduction Methods
Hai Liu, Tiande Guo, Congying Han
We propose a single-loop variance-reduced acceleration framework, which relates checkpoint update probabilities to momentum parameters, for solving the composite general convex pro…
Generating Linear programming Instances with Controllable Rank and Condition Number
Anqi Li, Congying Han, Tiande Guo
Instances generation is crucial for linear programming algorithms, which is necessary either to find the optimal pivot rules by training learning method or to evaluate and verify c…
On the optimal pivot path of simplex method for linear programming based on reinforcement learning
Anqi Li, Tiande Guo, Congying Han +2
Based on the existing pivot rules, the simplex method for linear programming is not polynomial in the worst case. Therefore the optimal pivot of the simplex method is crucial. This…