Zobrazeno 1 - 10
of 6 866
pro vyhledávání: '"Donatelli, A."'
Autor:
Lukin, Stephanie M., Bonial, Claire, Marge, Matthew, Hudson, Taylor, Hayes, Cory J., Pollard, Kimberly A., Baker, Anthony, Foots, Ashley N., Artstein, Ron, Gervits, Felix, Abrams, Mitchell, Henry, Cassidy, Donatelli, Lucia, Leuski, Anton, Hill, Susan G., Traum, David, Voss, Clare R.
Publikováno v:
2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) https://aclanthology.org/2024.lrec-main.1259/
We introduce the Situated Corpus Of Understanding Transactions (SCOUT), a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration. The corpus was constructed from multiple Wizard-of-Oz experiments where human pa
Externí odkaz:
http://arxiv.org/abs/2411.12844
Autor:
Bonial, Claire, Lukin, Stephanie M., Abrams, Mitchell, Baker, Anthony, Donatelli, Lucia, Foots, Ashley, Hayes, Cory J., Henry, Cassidy, Hudson, Taylor, Marge, Matthew, Pollard, Kimberly A., Artstein, Ron, Traum, David, Voss, Clare R.
Publikováno v:
Language Resources and Evaluation 2024
In this paper, we describe the development of symbolic representations annotated on human-robot dialogue data to make dimensions of meaning accessible to autonomous systems participating in collaborative, natural language dialogue, and to enable comm
Externí odkaz:
http://arxiv.org/abs/2411.12829
Autor:
Abbatiello, Anna, Donatelli, Donatella
We study free boundary compressible viscous models that may include nonlinear viscosities. These are compressible/incompressible Navier-Stokes type systems for a non-Newtonian stress tensor. They describe the motion of a possibly non-Newtonian fluid
Externí odkaz:
http://arxiv.org/abs/2410.19691
Variational models for image deblurring problems typically consist of a smooth term and a potentially non-smooth convex term. A common approach to solving these problems is using proximal gradient methods. To accelerate the convergence of these first
Externí odkaz:
http://arxiv.org/abs/2409.13454
Autor:
Donatelli, Marco, Furchì, Davide
The iterated Arnoldi-Tikhonov (iAT) method is a regularization technique particularly suited for solving large-scale ill-posed linear inverse problems. Indeed, it reduces the computational complexity through the projection of the discretized problem
Externí odkaz:
http://arxiv.org/abs/2404.08321
Autor:
Mughal, Muhammad Hamza, Dabral, Rishabh, Habibie, Ikhsanul, Donatelli, Lucia, Habermann, Marc, Theobalt, Christian
Gestures play a key role in human communication. Recent methods for co-speech gesture generation, while managing to generate beat-aligned motions, struggle generating gestures that are semantically aligned with the utterance. Compared to beat gesture
Externí odkaz:
http://arxiv.org/abs/2403.17936
In the past decades, a remarkable amount of research has been carried out regarding fast solvers for large linear systems resulting from various discretizations of fractional differential equations (FDEs). In the current work, we focus on multigrid m
Externí odkaz:
http://arxiv.org/abs/2403.16352
We consider an unsupervised bilevel optimization strategy for learning regularization parameters in the context of imaging inverse problems in the presence of additive white Gaussian noise. Compared to supervised and semi-supervised metrics relying e
Externí odkaz:
http://arxiv.org/abs/2403.07026
We present novel improvements in the context of symbol-based multigrid procedures for solving large block structured linear systems. We study the application of an aggregation-based grid transfer operator that transforms the symbol of a block Toeplit
Externí odkaz:
http://arxiv.org/abs/2403.02139
Autor:
Bianchi, Davide, Evangelista, Davide, Aleotti, Stefano, Donatelli, Marco, Piccolomini, Elena Loli, Li, Wenbin
We investigate a variational method for ill-posed problems, named $\texttt{graphLa+}\Psi$, which embeds a graph Laplacian operator in the regularization term. The novelty of this method lies in constructing the graph Laplacian based on a preliminary
Externí odkaz:
http://arxiv.org/abs/2312.16936