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Related publications (32)

Further results on latent discourse models and word embeddings

Youssef Allouah

We discuss some properties of generative models for word embeddings. Namely, (Arora et al., 2016) proposed a latent discourse model implying the concentration of the partition function of the word vectors. This concentration phenomenon led to an asymptotic ...

Microtome Publishing2021

Generalization Error Bounds Via Rényi-, f-Divergences and Maximal Leakage

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

In this work, the probability of an event under some joint distribution is bounded by measuring it with the product of the marginals instead (which is typically easier to analyze) together with a measure of the dependence between the two random variables. ...

2021

Large data scattering for NLKG on waveguide R-d x T

Luigi Forcella

We consider the pure-power defocusing nonlinear Klein-Gordon equation, in the H-1-subcritical case, posed on the product space R-d X T, where T is the one-dimensional flat torus. In this framework, we prove that scattering holds for any initial data belong ...

WORLD SCIENTIFIC PUBL CO PTE LTD2020

Metal-organic framework derived copper catalysts for CO2 to ethylene conversion

Jun Li

The electrochemical reduction of CO2 to ethylene provides a carbon-neutral avenue for the conversion of CO2 to value-added fuels and feedstocks, so contributing to the storage of intermittent renewable electricity. The exploration of efficient electrocatal ...

Royal Society of Chemistry2020

ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning

Irem Boybat Kara, Abu Sebastian

Deep neural networks (DNNs) have surpassed human-level accuracy in a variety of cognitive tasks but at the cost of significant memory/time requirements in DNN training. This limits their deployment in energy and memory limited applications that require rea ...

IEEE2020

Product assortment and space allocation strategies to attract loyal and non-loyal customers

Ralf Seifert, Anna Timonina-Farkas, Argyro Katsifou

Assortment planning deserves much attention from practitioners and academics due to its direct impact on retailers' commercial success. In this paper we focus on the increasingly popular retail practice to use combined product assortments with both "standa ...

2020

Copper-Catalyzed Oxyvinylation of Diazo Compounds

Jérôme Waser, Guillaume Dominique Pisella, Alec Gagnebin

A copper(I)-catalyzed vinylation of diazo compounds with vinylbenziodoxolone reagents (VBX) as partners is reported. The transformation tolerates diverse functionalities on both reagents delivering polyfunctionalized vinylated products. The strategy was su ...

2020

Extended Integrated Force Method for the analysis of prestress-stable statically and kinematically indeterminate structures

Gennaro Senatore, Yafeng Wang

This paper presents a new force method to predict the structural response of statically and kinematically indeterminate systems that can be stabilized through prestress, i.e. prestress-stable structures. This new force method, here named Extended Integrate ...

2020

Reactions of pyrrole, imidazole, and pyrazole with ozone: kinetics and mechanisms

Urs von Gunten, Peter Rudolf Tentscher, Sung Eun Lim

Five-membered nitrogen-containing heterocyclic compounds (azoles) belong to potential moieties in complex structures where transformations during ozonation can occur. This study focused on the azole-ozone chemistry of pyrrole, imidazole, and pyrazole as mo ...

ROYAL SOC CHEMISTRY2020

Sub-Matrix Factorization for Real-Time Vote Prediction

Patrick Thiran, Matthias Grossglauser, Victor Kristof

We address the problem of predicting aggregate vote outcomes (e.g., national) from partial outcomes (e.g., regional) that are revealed sequentially. We combine matrix factorization techniques and generalized linear models (GLMs) to obtain a flexible, effic ...

2020

Learning with tensors: a framework based on convex optimization and spectral regularization

Quoc Tran Dinh

We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a uni ...

Springer2014

Robust, High-Speed Interest Point Matching for Real-Time Applications

Michael Calonder

A typical Computer Vision system needs to process vast amounts of data as captured by one or more cameras, constantly testing the capabilities of today's hardware. Yet such systems face an ever-growing computational load caused by the more and more demandi ...

EPFL2010