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The ever-growing size of the foundation language model has brought significant performance gains in various types of downstream tasks. With the existence of side-effects brought about by the large size of the foundation language model such…

Computation and Language · Computer Science 2022-10-14 Zhengqi He , Taro Toyoizumi

A new multivariate distribution possessing arbitrarily parametrized and positively dependent univariate Pareto margins is introduced. Unlike the probability law of Asimit et al. (2010) [Asimit, V., Furman, E. and Vernic, R. (2010) On a…

Risk Management · Quantitative Finance 2016-07-19 Jianxi Su , Edward Furman

We derive valuations of a portfolio of financial instruments from a securities lending perspective, under different assumptions, and show a weighting scheme that converges to the true valuation. We illustrate conditions under which our…

Pricing of Securities · Quantitative Finance 2019-07-23 Ravi Kashyap

I think we can agree that dealing with uncertainty is not easy. Probability is the main tool for dealing with uncertainty, and we know there are many probability-related puzzles and paradoxes. Here I describe a rather idiosyncratic…

Other Statistics · Statistics 2022-01-19 Yudi Pawitan

We study the interplay between sequential decision making and avoiding discrimination against protected groups, when examples arrive online and do not follow distributional assumptions. We consider the most basic extension of classical…

Machine Learning · Computer Science 2019-04-02 Avrim Blum , Suriya Gunasekar , Thodoris Lykouris , Nathan Srebro

Portfolio optimization methods suffer from a catalogue of known problems, mainly due to the facts that pair correlations of asset returns are unstable, and that extremal risk measures such as maximum drawdown are difficult to predict due to…

Portfolio Management · Quantitative Finance 2022-05-20 Jan Rosenzweig

In this article we demonstrate how algorithmic probability theory is applied to situations that involve uncertainty. When people are unsure of their model of reality, then the outcome they observe will cause them to update their beliefs. We…

Artificial Intelligence · Computer Science 2014-05-26 Phil Maguire , Philippe Moser , Rebecca Maguire , Mark Keane

We provide an operational interpretation of the multivariate R\'enyi divergence in terms of economic-theoretic tasks based on betting, risk aversion, and multiple lotteries. We show that the multivariate R\'enyi divergence…

Quantum Physics · Physics 2026-01-27 Andrés F. Ducuara , Erkka Haapasalo , Ryo Takakura

Reciprocity in social networks helps understand information exchange between two individuals, and indicates interaction patterns between pairs of users. A recent study indicates the reciprocity coefficient of a classical directed…

Physics and Society · Physics 2022-01-12 Daniel Cirkovic , Tiandong Wang , Sidney Resnick

In this paper, we establish a mathematical duality between utility transforms and probability distortions. These transforms play a central role in decision under risk by forming the foundation for the classic theories of expected utility,…

Theoretical Economics · Economics 2024-03-21 Christopher P. Chambers , Peng Liu , Ruodu Wang

We consider the problem of estimating assortment probabilities, which is common in operations management applications, including product bundling, advertising, etc. Existing approaches typically model each assortment as a category and apply…

Statistics Theory · Mathematics 2026-03-23 Alexandre Belloni , Yan Chen , Matthew Harding

Computing the probability of a formula given the probabilities or weights associated with other formulas is a natural extension of logical inference to the probabilistic setting. Surprisingly, this problem has received little attention in…

Artificial Intelligence · Computer Science 2012-03-19 Vibhav Gogate , Pedro Domingos

We present new theoretical results on differentially private data release useful with respect to any target class of counting queries, coupled with experimental results on a variety of real world data sets. Specifically, we study a simple…

Data Structures and Algorithms · Computer Science 2012-03-16 Moritz Hardt , Katrina Ligett , Frank McSherry

In random expected utility (Gul and Pesendorfer, 2006), the distribution of preferences is uniquely recoverable from random choice. This paper shows through two examples that such uniqueness fails in general if risk preferences are random…

Theoretical Economics · Economics 2020-09-10 Yi-Hsuan Lin

We introduce a new type of preferential attachment tree that includes choices in its evolution, like with Achlioptas processes. At each step in the growth of the graph, a new vertex is introduced. Two possible neighbor vertices are selected…

Probability · Mathematics 2014-02-18 Yury Malyshkin , Elliot Paquette

Probability models have been proposed in the literature to account for "intelligent" behavior in many contexts. In this paper, probability propagation is applied to model agent's motion in potentially complex scenarios that include goals…

In real-world Bayesian inference applications, prior assumptions regarding the parameters of interest may be unrepresentative of their actual values for a given dataset. In particular, if the likelihood is concentrated far out in the wings…

Computation · Statistics 2018-11-01 Xi Chen , Mike Hobson , Saptarshi Das , Paul Gelderblom

This paper axiomatizes, in a two-stage setup, a new theory for decision under risk and ambiguity. The axiomatized preference relation $\succeq$ on the space $\tilde{V}$ of random variables induces an ambiguity index $c$ on the space…

Optimization and Control · Mathematics 2026-03-24 Roger J. A. Laeven , Mitja Stadje

In most social choice settings, the participating agents express their preferences over the different alternatives in the form of linear orderings. While this clearly simplifies preference elicitation, it inevitably leads to poor…

Computer Science and Game Theory · Computer Science 2022-10-05 Georgios Amanatidis , Georgios Birmpas , Aris Filos-Ratsikas , Alexandros A. Voudouris

In this paper, we consider the revealed preferences problem from a learning perspective. Every day, a price vector and a budget is drawn from an unknown distribution, and a rational agent buys his most preferred bundle according to some…

Computer Science and Game Theory · Computer Science 2012-11-20 Morteza Zadimoghaddam , Aaron Roth
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