74 citations · 76 across the 6 of their papers we have counts for
6 papers
Bandit Submodular Maximization under Matroid Constraints: Learning Compressed Exchange Policy
Zongqi Wan, Zhijie Zhang
We study adversarial bandit maximization of monotone submodular functions under a matroid constraint. For a rank- matroid on elements, we give a randomized oracle-polynomial…
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…
Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch
Aojun Zhou, Yukun Ma, Junnan Zhu +5
Sparsity in Deep Neural Networks (DNNs) has been widely studied to compress and accelerate the models on resource-constrained environments. It can be generally categorized into uns…
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…
Cake Cutting on Graphs: A Discrete and Bounded Proportional Protocol
Xiaohui Bei, Xiaoming Sun, Hao Wu +3
The classical cake cutting problem studies how to find fair allocations of a heterogeneous and divisible resource among multiple agents. Two of the most commonly studied fairness c…
A Linear Algorithm for Finding the Sink of Unique Sink Orientations on Grids
Xiaoming Sun, Jialin Zhang, Zhijie Zhang
An orientation of a grid is called unique sink orientation (USO) if each of its nonempty subgrids has a unique sink. Particularly, the original grid itself has a unique global sink…