19 citations · 24 across the 16 of their papers we have counts for
20 papers
A Deterministic -Approximation for Non-monotone Submodular Maximization under Matroid Constraints
Shengminjie Chen, Kaifeng Lin, Xiaoming Sun +1
Submodular maximization arises in a wide range of combinatorial optimization problems and has been extensively studied from the perspective of approximation algorithms. For maximiz…
Quantum Submodular Maximization
Yonggang Jiang, Xiaoming Sun, Penghui Yao +3
We study the quantum query complexity of maximizing a non-negative submodular function, considering both the unconstrained setting and, for monotone functions, a cardinality constr…
Deterministic Algorithm for Non-monotone Submodular Maximization under Matroid and Knapsack Constraints
Shengminjie Chen, Yiwei Gao, Kaifeng Lin +2
Submodular maximization constitutes a prominent research topic in combinatorial optimization and theoretical computer science, with extensive applications across diverse domains. W…
SAQNN: Spectral Adaptive Quantum Neural Network as a Universal Approximator
Jialiang Tang, Jialin Zhang, Xiaoming Sun
Quantum machine learning (QML), as an interdisciplinary field bridging quantum computing and machine learning, has garnered significant attention in recent years. Currently, the fi…
Scalable Multi-QPU Circuit Design for Dicke State Preparation: Optimizing Communication Complexity and Local Circuit Costs
Ziheng Chen, Junhong Nie, Xiaoming Sun +2
Preparing large-qubit Dicke states is of broad interest in quantum computing and quantum metrology. However, the number of qubits available on a single quantum processing unit (QPU…
A Lyapunov Framework for Quantum Algorithm Design in Combinatorial Optimization with Approximation Ratio Guarantees
Shengminjie Chen, Ziyang Li, Hongyi Zhou +3
In this work, we develop a framework aiming at designing quantum algorithms for combinatorial optimization problems while providing theoretical guarantees on their approximation ra…
A Unified Complexity-Algorithm Account of Constant-Round QAOA Expectation Computation
Jingheng Wang, Shengminjie Chen, Xiaoming Sun +1
The Quantum Approximate Optimization Algorithm (QAOA) is widely studied for combinatorial optimization and has achieved significant advances both in theoretical guarantees and prac…
Communication Complexity of Distributed Unitary Synthesis
Longcheng Li, Xiaoming Sun, Jialin Zhang +1
We study space-bounded communication complexity for unitary implementation in distributed quantum processors, where we restrict the number of qubits per processor to ensure practic…
Quantum circuit synthesis with SQiSW
Jialiang Tang, Jialin Zhang, Xiaoming Sun
The primary objective of quantum circuit synthesis is to efficiently and accurately realize specific quantum algorithms or operations utilizing a predefined set of quantum gates, w…
Efficient Deterministic Algorithms for Maximizing Symmetric Submodular Functions
Zongqi Wan, Jialin Zhang, Xiaoming Sun +1
Symmetric submodular maximization is an important class of combinatorial optimization problems, including MAX-CUT on graphs and hyper-graphs. The state-of-the-art algorithm for the…
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…
Improved Deterministic Streaming Algorithms for Non-monotone Submodular Maximization
Xiaoming Sun, Jialin Zhang, Shuo Zhang
Submodular maximization is one of the central topics in combinatorial optimization. It has found numerous applications in the real world. Streaming algorithms for submodule maximiz…
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…
Improved Deterministic Algorithms for Non-monotone Submodular Maximization
Xiaoming Sun, Jialin Zhang, Shuo Zhang +1
Submodular maximization is one of the central topics in combinatorial optimization. It has found numerous applications in the real world. In the past decades, a series of algorithm…
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…
Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback
Zhijie Zhang, Wei Chen, Xiaoming Sun +1
We study the online influence maximization (OIM) problem in social networks, where the learner repeatedly chooses seed nodes to generate cascades, observes the cascade feedback, an…
Efficient quantum circuit synthesis for SAT-oracle with limited ancillary qubit
Shuai Yang, Wei Zi, Bujiao Wu +3
How to implement quantum oracle with limited resources raises concerns these days. We design two ancilla-adjustable and efficient algorithms to synthesize SAT-oracle, the key compo…
Simple Deterministic Approximation for Submodular Multiple Knapsack Problem
Xiaoming Sun, Jialin Zhang, Zhijie Zhang
Submodular maximization has been a central topic in theoretical computer science and combinatorial optimization over the last decades. Plenty of well-performed approximation algori…
Optimization of CNOT circuits on limited connectivity architecture
Bujiao Wu, Xiaoyu He, Shuai Yang +4
A CNOT circuit is the key gadget for entangling qubits in quantum computing systems. However, the qubit connectivity of noisy intermediate-scale quantum (NISQ) devices is constrain…