18 citations · 22 across the 6 of their papers we have counts for
10 papers
Towards Practical Explainability with Cluster Descriptors
Xiaoyuan Liu, Ilya Tyagin, Hayato Ushijima-Mwesigwa +2
With the rapid development of machine learning, improving its explainability has become a crucial research goal. We study the problem of making the clusters more explainable by inv…
Constructing Optimal Contraction Trees for Tensor Network Quantum Circuit Simulation
Cameron Ibrahim, Danylo Lykov, Zichang He +2
One of the key problems in tensor network based quantum circuit simulation is the construction of a contraction tree which minimizes the cost of the simulation, where the cost can…
BEINIT: Avoiding Barren Plateaus in Variational Quantum Algorithms
Ankit Kulshrestha, Ilya Safro
Barren plateaus are a notorious problem in the optimization of variational quantum algorithms and pose a critical obstacle in the quest for more efficient quantum machine learning…
Partitioning Dense Graphs with Hardware Accelerators
Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Indradeep Ghosh +1
Graph partitioning is a fundamental combinatorial optimization problem that attracts a lot of attention from theoreticians and practitioners due to its broad applications. From mul…
Proactive Query Expansion for Streaming Data Using External Source
Farah Alshanik, Amy Apon, Yuheng Du +2
Query expansion is the process of reformulating the original query by adding relevant words. Choosing which terms to add in order to improve the performance of the query expansion…
Transferability of optimal QAOA parameters between random graphs
Alexey Galda, Xiaoyuan Liu, Danylo Lykov +2
The Quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization. I…