Modurec: Recommender Systems with Feature and Time Modulation

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Active multi gate micro-electro-mechanical device with built-in transistor

Mihai Adrian Ionescu

The present invention exploits the combination of the amplification, provided by the integration of a FET (or any other three terminal active device), with the signal modulation, provided by the MEM resonator, to build a MEM resonator with built-in transis ...

2010

Autoregressive Models of Amplitude Modulations in Audio Compression

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy

We present a scalable medium bit-rate wide-band audio coding technique based on frequency domain linear prediction (FDLP). FDLP is an efficient method for representing the long-term amplitude modulations of speech/audio signals using autoregressive models. ...

2010

Self-Supervision By Prediction For Object Discovery In Videos

Pascal Frossard, Beril Besbinar

Despite their irresistible success, deep learning algorithms still heavily rely on annotated data, and unsupervised settings pose many challenges, such as finding the right inductive bias in diverse scenarios. In this paper, we propose an object-centric mo ...

IEEE2021

Fast Multi-Step Critiquing for VAE-based Recommender Systems

Boi Faltings, Diego Matteo Antognini

Recent studies have shown that providing personalized explanations alongside recommendations increases trust and perceived quality. Furthermore, it gives users an opportunity to refine the recommendations by critiquing parts of the explanations. On one han ...

ASSOC COMPUTING MACHINERY2021

Energy-Efficient Design Techniques for High-Speed Wireline Serial Links

Firat Çelik

The exponential growth in computing power and multimedia services has caused a tremendous increase in data traffic in recent years. This increase in data traffic brings a strong demand for data bandwidth of electrical input/output (I/O) links and pushes th ...

EPFL2021

Time-Varying Components for Enhancing Wireless Transfer of Power and Information

Romain Christophe Rémy Fleury, Mohammad Sajjad Mirmoosa

Temporal modulation of components of electromagnetic systems provides an exceptional opportunity to engineer the response of those systems in a desired fashion, both in the time and frequency domains. For engineering time-modulated systems, one needs to th ...

American Physical Society (APS)2021

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

Context-Aware Learning for Generative Models

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Serafeim Perdikis

This work studies the class of algorithms for learning with side-information that emerges by extending generative models with embedded context-related variables. Using finite mixture models (FMMs) as the prototypical Bayesian network, we show that maximum- ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Benefiting from Multitask Learning to Improve Single Image Super-Resolution

Jean-Philippe Thiran, Claudiu-Cristian Musat, Hazim Kemal Ekenel, Mohammad Saeed Rad

Despite significant progress toward super resolving more realistic images by deeper convolutional neural networks (CNNs), reconstructing fine and natural textures still remains a challenging problem. Recent works on single image super resolution (SISR) are ...

2020

Comprehensive Spectral Analysis of PWM Waveforms With Compensated DC link Oscillations

Drazen Dujic, Stefan Milovanovic

In the available literature, including reference books on the topic, the spectral analysis of voltage waveforms obtained through the use of pulse-width modulation relies on the assumption of an ideally flat voltage across the DC link of a considered switch ...

2020