Taifeng Wang

Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction

2017 · Proceedings of the AAAI Conference on Artificial Intelligence

Regularized empirical risk minimization (R-ERM) is an important branch of machine learning, since it constrains the capacity of the hypothesis space and guarantees the generalization ability of the learning algorithm. Two classic proximal optimization algorithms, …

Incremental Event Detection via Knowledge Consolidation Networks

2020

Conventional approaches to event detection usually require a fixed set of pre-defined event types. Such a requirement is often challenged in real-world applications, as new events continually occur. Due to huge computation cost and storage …