Publications related to Effective Enrichment of Gene Expression Data Sets

On the Double Descent of Random Features Models Trained with SGD

We study generalization properties of random features (RF) regression in high dimensions optimized by stochastic gradient descent (SGD) in under-/overparameterized regime. In this work, we derive precise non-asymptotic error bounds of RF regression under b ...

2022

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021

Collaborative Sampling in Generative Adversarial Networks

Alexandre Massoud Alahi, Yuejiang Liu, Parth Ashit Kothari

The standard practice in Generative Adversarial Networks (GANs) discards the discriminator during sampling. However, this sampling method loses valuable information learned by the discriminator regarding the data distribution. In this work, we propose a co ...

2020

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

Michaël Unser, Quy Ha Nguyen

In our recent work, the sampling and reconstruction of non-decaying signals, modeled as members of weighted-L-p spaces, were shown to be stable with an appropriate choice of the generating kernel for the shift-invariant reconstruction space. In this paper, ...

2019

Retroactive Packet Sampling for Traffic Receipts

Pavlos Nikolopoulos, Adrian Perrig, Christos Pappas

Is it possible to design a packet-sampling algorithm that prevents the network node that performs the sampling from treating the sampled packets preferentially? We study this problem in the context of designing a "network transparency" system. In this syst ...

ACM2019

Distributed sampling for rational approximation of the acoustic scattering of an airfoil

Francesca Bonizzoni, Davide Pradovera

In this paper we compute a reduced order model for a time‐harmonic external acoustic scattering problem with parametric frequency. The employed technique is minimal rational interpolation, an explicit moment‐matching method for Hilbert space‐valued meromor ...

2019

Safe Adaptive Importance Sampling

Martin Jaggi, Sebastian Urban Stich, Anant Raj

Importance sampling has become an indispensable strategy to speed up optimization algorithms for large-scale applications. Improved adaptive variants - using importance values defined by the complete gradient information which changes during optimization - ...

2017

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

Sampling at unknown locations, with an application in surface retrieval

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Michalina Wanda Pacholska

We consider the problem of sampling at unknown locations. We prove that, in this setting, if we take arbitrarily many samples of a polynomial or real bandlimited signal, it is possible to find another function in the same class, arbitrarily far away from t ...

2017

Quasi-random numbers for copula models

Mathieu Jacques David Cambou

The present work addresses the question how sampling algorithms for commonly applied copula models can be adapted to account for quasi-random numbers. Besides sampling methods such as the conditional distribution method (based on a one-to-one transformatio ...

Springer2017

Effective Enrichment of Gene Expression Data Sets

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On the Double Descent of Random Features Models Trained with SGD

Uncertain Sampling with Certain Priors

Collaborative Sampling in Generative Adversarial Networks

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

Retroactive Packet Sampling for Traffic Receipts

Distributed sampling for rational approximation of the acoustic scattering of an airfoil

Safe Adaptive Importance Sampling

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Sampling at unknown locations, with an application in surface retrieval

Quasi-random numbers for copula models

Uncertain Sampling with Certain Priors

Safe Adaptive Importance Sampling

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

On the Double Descent of Random Features Models Trained with SGD

Distributed sampling for rational approximation of the acoustic scattering of an airfoil

Quasi-random numbers for copula models

Retroactive Packet Sampling for Traffic Receipts

Sampling at unknown locations, with an application in surface retrieval

Collaborative Sampling in Generative Adversarial Networks