63 citations · 168 across the 57 of their papers we have counts for
5 papers · 1 filter
Boosting Gradient Ascent for Continuous DR-submodular Maximization
Qixin Zhang, Zongqi Wan, Zengde Deng +4
Projected Gradient Ascent (PGA) is the most commonly used optimization scheme in machine learning and operations research areas. Nevertheless, numerous studies and examples have sh…
Bandit Multi-linear DR-Submodular Maximization and Its Applications on Adversarial Submodular Bandits
Zongqi Wan, Jialin Zhang, Wei Chen +2
We investigate the online bandit learning of the monotone multi-linear DR-submodular functions, designing the algorithm that attains of $(1…
Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regrets
Zongqi Wan, Zhijie Zhang, Tongyang Li +2
Multi-arm bandit (MAB) and stochastic linear bandit (SLB) are important models in reinforcement learning, and it is well-known that classical algorithms for bandits with time horiz…
Bounded Memory Adversarial Bandits with Composite Anonymous Delayed Feedback
Zongqi Wan, Xiaoming Sun, Jialin Zhang
We study the adversarial bandit problem with composite anonymous delayed feedback. In this setting, losses of an action are split into components, spreading over consecutive ro…
Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang +1
We revisit the optimization from samples (OPS) model, which studies the problem of optimizing objective functions directly from the sample data. Previous results showed that we can…