Concept

Irreducible representation

Related publications (238)

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Three-Dimensional Cubic Barcodes

Martin Vetterli, Adam James Scholefield, Golnooshsadat Elhami

We consider three-dimensional cubic barcodes, consisting of smaller cubes, each built from one of two possible materials and carry one bit of information. To retrieve the information stored in the barcode, we measure a 2-D projection of the barcode using a ...

2021

Learning computationally efficient static word and sentence representations

Prakhar Gupta

Most of the Natural Language Processing (NLP) algorithms involve use of distributed vector representations of linguistic units (primarily words and sentences) also known as embeddings in one way or another. These embeddings come in two flavours namely, sta ...

EPFL2021

A quantum algorithm for the direct estimation of the steady state of open quantum systems

Vincenzo Savona, Nathan Ramusat

Simulating the dynamics and the non-equilibrium steady state of an open quantum system are hard computational tasks on conventional computers. For the simulation of the time evolution, several efficient quantum algorithms have recently been developed. Howe ...

VEREIN FORDERUNG OPEN ACCESS PUBLIZIERENS QUANTENWISSENSCHAF2021

Contextual semantic interpretability

Devis Tuia, Sylvain Lobry, Nicolas Courty

Convolutional neural networks (CNN) are known to learn an image representation that captures concepts relevant to the task, but do so in an implicit way that hampers model interpretability. However, one could argue that such a representation is hidden in t ...

LNCS2020

Generalized Mullineux Involution And Perverse Equivalences

Thomas Gerber

We define a generalization of the Mullineux involution on multipartitions using the theory of crystals for higher-level Fock spaces. Our generalized Mullineux involution turns up in representation theory via two important derived functors on cyclotomic Che ...

2020

Principal Component Analysis By Optimization Of Symmetric Functions Has No Spurious Local Optima

Armin Eftekhari

Principal component analysis (PCA) finds the best linear representation of data and is an indispensable tool in many learning and inference tasks. Classically, principal components of a dataset are interpreted as the directions that preserve most of its "e ...

SIAM PUBLICATIONS2020

Enhancing discrete choice models with representation learning

Alexandre Massoud Alahi, Virginie Janine Camille Lurkin

In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...

2020

OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation

Petr Motlicek

The preparation of parallel corpora is a challenging task, particularly for languages that suffer from under-representation in the digital world. In a multi-lingual country like India, the need for such parallel corpora is stringent for several low-resourc ...

European Language Resources Association (ELRA)2020

Graph Embeddings for One-pass Processing of Heterogeneous Queries

Karl Aberer, Quoc Viet Hung Nguyen, Chi Thang Duong

Effective information retrieval (IR) relies on the ability to comprehensively capture a user's information needs. Traditional IR systems are limited to homogeneous queries that define the information to retrieve by a single modality. Support for heterogene ...

IEEE COMPUTER SOC2020

Asymptotic freedom, Haldane gap and edge states of SU(N) spin chains

Samuel Gozel

In this thesis we study various one-dimensional quantum spin systems with SU(2) and SU(N) symmetry. We investigate the short-distance behavior of the SU(2) Heisenberg model in the limit of large spin and show that there exists an extended regime where pert ...

EPFL2020