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Publications associées (16)
Multi-layer State Evolution Under Random Convolutional Design
Florent Gérard Krzakala, Lenka Zdeborová
Signal recovery under generative neural network priors has emerged as a promising direction in statistical inference and computational imaging. Theoretical analysis of reconstruction algorithms under generative priors is, however, challenging. For generati ...
2022Fourier Sampling in Signal Processing and Numerical Linear Algebra
This thesis focuses on developing efficient algorithmic tools for processing large datasets. In many modern data analysis tasks, the sheer volume of available datasets far outstrips our abilities to process them. This scenario commonly arises in tasks incl ...
EPFL2020Oblivious Sketching of High-Degree Polynomial Kernels
Mikhail Kapralov, Amir Zandieh
Kernel methods are fundamental tools in machine learning that allow detection of non-linear dependencies between data without explicitly constructing feature vectors in high dimensional spaces. A major disadvantage of kernel methods is their poor scalabili ...
ASSOC COMPUTING MACHINERY2020Unified Theory for Recovery of Sparse Signals in a General Transform Domain
Compressed sensing is provided a data-acquisition paradigm for sparse signals. Remarkably, it has been shown that the practical algorithms provide robust recovery from noisy linear measurements acquired at a near optimal sampling rate. In many real-world a ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018Methods and apparatuses for encoding and decoding digital images or video streams
Pascal Frossard, Giulia Fracastoro
The invention relates to a method and an apparatus for encoding and/or decoding digital images, wherein said encoding apparatus (1100) comprises processing means (1110) configured for determining weights of a graph related to an image by minimizing a cost ...
2018Recompression Of Hadamard Products Of Tensors In Tucker Format
The Hadamard product features prominently in tensor-based algorithms in scientific computing and data analysis. Due to its tendency to significantly increase ranks, the Hadamard product can represent a major computational obstacle in algorithms based on lo ...
Siam Publications2017An experimentalist's guide to the matrix element in angle resolved photoemission
Angle resolved photoemission spectroscopy (ARPES) is commonly known as a powerful probe of the one-electron removal spectral function in ordered solid state. With increasing efficiency of light sources and spectrometers, experiments over a wide range of em ...
Elsevier Science Bv2017Caching Gaussians: Minimizing Total Correlation on the Gray–Wyner Network
Michael Christoph Gastpar, Guillaume Jean Op 't Veld
We study a caching problem that resembles a lossy Gray–Wyner network: A source produces vector samples from a Gaussian distribution, but the user is interested in the samples of only one component. The encoder first sends a cache message without any knowle ...
Ieee2016Modulation, Coding, and Receiver Design for Gigabit mmWave Communication
While wireless communication has become an ubiquitous part of our daily life and the world around us, it has not been able yet to deliver the multi-gigabit throughput required for applications like high-definition video transmission or cellular backhaul co ...
EPFL2016Approximate Message Passing With Consistent Parameter Estimation and Applications to Sparse Learning
Michaël Unser, Ulugbek Kamilov
We consider the estimation of an independent and identically distributed (i.i.d.) (possibly non-Gaussian) vector x is an element of R-n from measurements y is an element of R-m obtained by a general cascade model consisting of a known linear transform foll ...
Ieee-Inst Electrical Electronics Engineers Inc2014