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Low Complexity Scheduling and Coding for Wireless Networks

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Publications associées (33)

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Hybrid ground-state quantum algorithms based on neural Schrödinger forging

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Entanglement forging based variational algorithms leverage the bipartition of quantum systems for addressing ground-state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basis stat ...

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Scalable Quantum Algorithms for Noisy Quantum Computers

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Quantum computing not only holds the potential to solve long-standing problems in quantum physics, but also to offer speed-ups across a broad spectrum of other fields. Access to a computational space that incorporates quantum effects, such as superposition ...

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The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

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Efficient Continual Finite-Sum Minimization

Ioannis Mavrothalassitis, Volkan Cevher, Leello Tadesse Dadi, Efstratios Panteleimon Skoulakis

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

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In this thesis, we give new protocols that offer a quantum advantage for problems in ML, Physics, and Finance. Quantum mechanics gives predictions that are inconsistent with local realism. The experiment proving this fact (Bell, 1964) gives a quantum proto ...

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Multiple tensor-times-matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. We establish communication lower bounds that determine ...

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Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

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Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

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Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

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Planetary-Scale Byzantine Fault Tolerance

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The scale and pervasiveness of the Internet make it a pillar of planetary communication, industry and economy, as well as a fundamental medium for public discourse and democratic engagement. In stark contrast with the Internet's decentralized infrastructur ...

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Due to its high parallelism, belief propagation (BP)decoding is amenable to high-throughput applications and thusrepresents a promising solution for the ultra-high peak datarate required by future communication systems. To bridge theperformance gap compare ...

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