571 citations · 861 across the 18 of their papers we have counts for
11 papers · 1 filter
Learning Restricted Boltzmann Machines with greedy quantum search
Liming Zhao, Aman Agrawal, Patrick Rebentrost
Restricted Boltzmann Machines (RBMs) are widely used probabilistic undirected graphical models with visible and latent nodes, playing an important role in statistics and machine le…
Provable learning of quantum states with graphical models
Liming Zhao, Naixu Guo, Ming-Xing Luo +1
The complete learning of an -qubit quantum state requires samples exponentially in . Several works consider subclasses of quantum states that can be learned in polynomial sam…
Quantum algorithm for Markov Random Fields structure learning by information theoretic properties
Liming Zhao, Lin-chun Wan, Ming-Xing Luo
Probabilistic graphical models play a crucial role in machine learning and have wide applications in various fields. One pivotal subset is undirected graphical models, also known a…
Quantum algorithm for structure learning of Markov Random Fields
Liming Zhao, Siyi Yang, Patrick Rebentrost
Markov random fields (MRFs) appear in many problems in machine learning and statistics. From a computational learning theory point of view, a natural problem of learning MRFs arise…
Quantum-classical algorithms for skewed linear systems with optimized Hadamard test
Bujiao Wu, Maharshi Ray, Liming Zhao +2
The solving of linear systems provides a rich area to investigate the use of nearer-term, noisy, intermediate-scale quantum computers. In this work, we discuss hybrid quantum-class…
Compiling basic linear algebra subroutines for quantum computers
Liming Zhao, Zhikuan Zhao, Patrick Rebentrost +1
Efficiently processing basic linear algebra subroutines is of great importance for a wide range of computational problems. In this paper, we consider techniques to implement matrix…
Variational Quantum Circuit Model for Knowledge Graphs Embedding
Yunpu Ma, Volker Tresp, Liming Zhao +1
In this work, we propose the first quantum Ansätze for the statistical relational learning on knowledge graphs using parametric quantum circuits. We introduce two types of variatio…
Measurement-driven quantum computing: Performance of a 3-SAT solver
Simon C. Benjamin, Liming Zhao, Joseph F. Fitzsimons
We investigate the performance of a quantum algorithm for solving classical 3-SAT problems. A cycle of post-selected measurements drives the computer's register monotonically towar…
A measurement driven analog of adiabatic quantum computation for frustration-free Hamiltonians
Liming Zhao, Carlos A. Perez-Delgado, Simon C. Benjamin +1
The adiabatic quantum algorithm has drawn intense interest as a potential approach to accelerating optimization tasks using quantum computation. The algorithm is most naturally rea…
Fast graph operations in quantum computation
Liming Zhao, Carlos A. Pérez-Delgado, Joseph F. Fitzsimons
The connection between certain entangled states and graphs has been heavily studied in the context of measurement-based quantum computation as a tool for understanding entanglement…
Genuine Correlations of Tripartite System
Liming Zhao, Xueyuan Hu, R. -H. Yue +1
We define genuine total, classical and quantum correlations in tripartite systems. The measure we propose is based on the idea that genuine tripartite correlation exists if and onl…