Search Results for author: Minh Do

Found 8 papers, 1 papers with code

Planning for Compilation of a Quantum Algorithm for Graph Coloring

no code implementations23 Feb 2020 Minh Do, Zhihui Wang, Bryan O'Gorman, Davide Venturelli, Eleanor Rieffel, Jeremy Frank

Previous work demonstrated that temporal planning is an attractive approach for part of this compilationtask, specifically, the routing of circuits that implement the Quantum Alternating Operator Ansatz (QAOA) applied to the MaxCut problem on a quantum processor architecture.

STREETS: A Novel Camera Network Dataset for Traffic Flow

1 code implementation NeurIPS 2019 Corey Snyder, Minh Do

In this paper, we introduce STREETS, a novel traffic flow dataset from publicly available web cameras in the suburbs of Chicago, IL.

Comparing and Integrating Constraint Programming and Temporal Planning for Quantum Circuit Compilation

no code implementations19 Mar 2018 Kyle E. C. Booth, Minh Do, J. Christopher Beck, Eleanor Rieffel, Davide Venturelli, Jeremy Frank

Our hybrid methods use solutions found by temporal planning to warm start CP, leveraging the ability of the former to find satisficing solutions to problems with a high degree of task optionality, an area that CP typically struggles with.

Compiling quantum circuits to realistic hardware architectures using temporal planners

no code implementations24 May 2017 Davide Venturelli, Minh Do, Eleanor Rieffel, Jeremy Frank

We investigate the application of temporal planners to the problem of compiling quantum circuits to newly emerging quantum hardware.

Synthesizing Robust Plans under Incomplete Domain Models

no code implementations NeurIPS 2013 Tuan A. Nguyen, Subbarao Kambhampati, Minh Do

In this paper, we first introduce annotations expressing the knowledge of the domain incompleteness and formalize the notion of plan robustness with respect to an incomplete domain model.

Probabilistic Low-Rank Subspace Clustering

no code implementations NeurIPS 2012 S. D. Babacan, Shinichi Nakajima, Minh Do

In this paper, we consider the problem of clustering data points into low-dimensional subspaces in the presence of outliers.

Density Estimation

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