5 citations · 24 across the 8 of their papers we have counts for
5 papers · 1 filter
On Performance Estimation in Automatic Algorithm Configuration
Shengcai Liu, Ke Tang, Yunwen Lei +1
Over the last decade, research on automated parameter tuning, often referred to as automatic algorithm configuration (AAC), has made significant progress. Although the usefulness o…
Parallel Exploration via Negatively Correlated Search
Peng Yang, Qi Yang, Ke Tang +1
Effective exploration is a key to successful search. The recently proposed Negatively Correlated Search (NCS) tries to achieve this by parallel exploration, where a set of search p…
Competitive Coevolution as an Adversarial Approach to Dynamic Optimization
Xiaofen Lu, Ke Tang, Stefan Menzel +1
Dynamic optimization, for which the objective functions change over time, has attracted intensive investigations due to the inherent uncertainty associated with many real-world pro…
Running Time Analysis of the (1+1)-EA for Robust Linear Optimization
Chao Bian, Chao Qian, Ke Tang +1
Evolutionary algorithms (EAs) have found many successful real-world applications, where the optimization problems are often subject to a wide range of uncertainties. To understand…
Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions
Yunwen Lei, Ting Hu, Guiying Li +1
Stochastic gradient descent (SGD) is a popular and efficient method with wide applications in training deep neural nets and other nonconvex models. While the behavior of SGD is wel…