Algorithme de Grover

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Informatique théorique
Theory of computation
Informatique quantique

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Publications associées (30)

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Quantum compilation is the task of translating a quantum algorithm implemented in a high-level quantum programming language into a technology-dependent instructions flow for a physical quantum computer. To tackle the large gap between the quantum program a ...

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A Catalyst Framework for Minimax Optimization

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We introduce a generic two-loop scheme for smooth minimax optimization with strongly-convex-concave objectives. Our approach applies the accelerated proximal point framework (or Catalyst) to the associated dual problem and takes full advantage of existing ...

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Scalable and Efficient Comparison-based Search without Features

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We consider the problem of finding a target object t using pairwise comparisons, by asking an oracle questions of the form “Which object from the pair (i, j) is more similar to t?”. Objects live in a space of latent features, from which the oracle generate ...

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Enabling Accuracy-Aware Quantum Compilers using Symbolic Resource Estimation

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Approximation errors must be taken into account when compiling quantum programs into a low-level gate set. We present a methodology that tracks such errors automatically and then optimizes accuracy parameters to guarantee a specified overall accuracy while ...

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Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

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The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the esti ...

2021

Sensitivity analysis of fractal dimensions of crack maps on concrete and masonry walls

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Assessing building damage after earthquakes requires a visual inspection of the damage, indicated by maps of the cracking pattern on walls, which could be standardized via automated algorithms. To quantitate this damage, fractal dimensions of these crack m ...

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The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Updates

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We analyze (stochastic) gradient descent (SGD) with delayed updates on smooth quasi-convex and non-convex functions and derive concise, non-asymptotic, convergence rates. We show that the rate of convergence in all cases consists of two terms: (i) a stocha ...

Microtome Publishing2020

Scalable Semidefinite Programming

Volkan Cevher, Alp Yurtsever

Semidefinite programming (SDP) is a powerful framework from convex optimization that has striking potential for data science applications. This paper develops a provably correct algorithm for solving large SDP problems by economizing on both the storage an ...

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ROS : Resource Constrained Oracle Synthesis for Quantum Computers

Giovanni De Micheli, Mathias Soeken, Giulia Meuli

We present a complete automatic synthesis framework for oracle functions—a central part in many quantum algorithms. The proposed framework for resource-constrained oracle synthesis (ROS) is an LUT-based hierarchical method where every step is specifically ...

2019

Efficient Quantum Algorithms for GHZ and W States, and Implementation on the IBM Quantum Computer

Nicolas Macris, Clément Christian Javerzac-Galy, Marc-André Dupertuis, Kenichi Komagata, Chun Lam Chan, Fabien Gremion, Jarla Thiesbrummel, Romain Fournier

Efficient deterministic algorithms are proposed with logarithmic step complexities for the generation of entangled GHZ(N) and W-N states useful for quantum networks, and an implementation on the IBM quantum computer up to N = 16 is demonstrated. Improved q ...

WILEY2019

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