Zobrazeno 1 - 10
of 2 442
pro vyhledávání: '"P Bartl"'
Autor:
Grieve, Jack, Bartl, Sara, Fuoli, Matteo, Grafmiller, Jason, Huang, Weihang, Jawerbaum, Alejandro, Murakami, Akira, Perlman, Marcus, Roemling, Dana, Winter, Bodo
In this paper, we introduce a sociolinguistic perspective on language modeling. We claim that large language models are inherently models of varieties of language, and we consider how this insight can inform the development and deployment of large la
Externí odkaz:
http://arxiv.org/abs/2407.09241
Autor:
Bartl, Marion, Leavy, Susan
Gender bias is not only prevalent in Large Language Models (LLMs) and their training data, but also firmly ingrained into the structural aspects of language itself. Therefore, adapting linguistic structures within LLM training data to promote gender-
Externí odkaz:
http://arxiv.org/abs/2407.04434
Autor:
Bartl, Daniel, Eckstein, Stephan
We address the problem of estimating the expected shortfall risk of a financial loss using a finite number of i.i.d. data. It is well known that the classical plug-in estimator suffers from poor statistical performance when faced with (heavy-tailed)
Externí odkaz:
http://arxiv.org/abs/2405.00357
We examine nonlinear Kolmogorov partial differential equations (PDEs). Here the nonlinear part of the PDE comes from its Hamiltonian where one maximizes over all possible drift and diffusion coefficients which fall within a $\varepsilon$-neighborhood
Externí odkaz:
http://arxiv.org/abs/2403.11910
Autor:
Mildner, Thomas, Cooney, Orla, Meck, Anna-Maria, Bartl, Marion, Savino, Gian-Luca, Doyle, Philip R., Garaialde, Diego, Clark, Leigh, Sloan, John, Wenig, Nina, Malaka, Rainer, Niess, Jasmin
Advances in natural language processing and understanding have led to a rapid growth in the popularity of conversational user interfaces (CUIs). While CUIs introduce novel benefits, they also yield risks that may exploit people's trust. Although rese
Externí odkaz:
http://arxiv.org/abs/2401.14746
Autor:
Bartl, Daniel, Mendelson, Shahar
We show that under minimal assumption on a class of functions $\mathcal{H}$ defined on a probability space $(\mathcal{X},\mu)$, there is a threshold $\Delta_0$ satisfying the following: for every $\Delta\geq\Delta_0$, with probability at least $1-2\e
Externí odkaz:
http://arxiv.org/abs/2312.06442
We examine optimization problems in which an investor has the opportunity to trade in $d$ stocks with the goal of maximizing her worst-case cost of cumulative gains and losses. Here, worst-case refers to taking into account all possible drift and vol
Externí odkaz:
http://arxiv.org/abs/2311.11248
Autor:
Bartl, Daniel, Mendelson, Shahar
Publikováno v:
International Mathematics Research Notices, 2023+
We construct the first non-gaussian ensemble that yields the optimal estimate in the Dvoretzky-Milman Theorem: the ensemble exhibits almost Euclidean sections in arbitrary normed spaces of the same dimension as the gaussian embedding -- despite being
Externí odkaz:
http://arxiv.org/abs/2309.12069
Autor:
Bartl, Daniel, Mendelson, Shahar
Let $G_1,\dots,G_m$ be independent copies of the standard gaussian random vector in $\mathbb{R}^d$. We show that there is an absolute constant $c$ such that for any $A \subset S^{d-1}$, with probability at least $1-2\exp(-c\Delta m)$, for every $t\in
Externí odkaz:
http://arxiv.org/abs/2309.02013
Autor:
Bartl, Daniel, Mendelson, Shahar
Let $X$ be a real-valued random variable with distribution function $F$. Set $X_1,\dots, X_m$ to be independent copies of $X$ and let $F_m$ be the corresponding empirical distribution function. We show that there are absolute constants $c_0$ and $c_1
Externí odkaz:
http://arxiv.org/abs/2308.04757