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Black box models in machine learning have demonstrated excellent predictive performance in complex problems and high-dimensional settings. However, their lack of transparency and interpretability restrict the applicability of such models in…

Machine Learning · Computer Science 2020-06-09 Numair Sani , Jaron Lee , Razieh Nabi , Ilya Shpitser

In this paper we show that there is a link between approximate Bayesian methods and prior robustness. We show that what is typically recognized as an approximation to the likelihood, either due to the simulated data as in the Approximate…

Methodology · Statistics 2020-04-03 Chaitanya Joshi , Fabrizio Ruggeri

Interdependent values make basic auction design tasks -- in particular maximizing welfare truthfully in single-item auctions -- quite challenging. Eden et al. recently established that if the bidders valuation functions are submodular over…

Computer Science and Game Theory · Computer Science 2021-07-20 Ameer Amer , Inbal Talgam-Cohen

Traditionally, the Bayesian optimal auction design problem has been considered either when the bidder values are i.i.d., or when each bidder is individually identifiable via her value distribution. The latter is a reasonable approach when…

Computer Science and Game Theory · Computer Science 2023-07-11 Nikhil R. Devanur , Zhiyi Huang , Christos-Alexandros Psomas

We continue the study of the performance for fixed-price mechanisms in the bilateral trade problem, and improve approximation ratios of welfare-optimal mechanisms in several settings. Specifically, in the case where only the buyer…

Computer Science and Game Theory · Computer Science 2023-03-29 Zhengyang Liu , Zeyu Ren , Zihe Wang

Motivated by applications such as stock exchanges and spectrum auctions, there is a growing interest in mechanisms for arranging trade in two-sided markets. Existing mechanisms are either not truthful, or do not guarantee an…

Computer Science and Game Theory · Computer Science 2018-05-02 Erel Segal-Halevi , Avinatan Hassidim , Yonatan Aumann

Most work in mechanism design assumes that buyers are risk neutral; some considers risk aversion arising due to a non-linear utility for money. Yet behavioral studies have established that real agents exhibit risk attitudes which cannot be…

Computer Science and Game Theory · Computer Science 2018-03-13 Shuchi Chawla , Kira Goldner , J. Benjamin Miller , Emmanouil Pountourakis

When agents with independent priors bid for a single item, Myerson's optimal auction maximizes expected revenue, whereas Vickrey's second-price auction optimizes social welfare. We address the natural question of trade-offs between the two…

Computer Science and Game Theory · Computer Science 2012-05-15 Ilias Diakonikolas , Christos Papadimitriou , George Pierrakos , Yaron Singer

We investigate Bayesian predictive inference for finite population quantities when there are unequal probabilities of selection. Only limited information about the sample design is available; i.e., only the first-order selection…

Methodology · Statistics 2018-04-10 Junheng Ma , Joe Sedransk , Balgobin Nandram , Lu Chen

A matching in a two-sided market often incurs an externality: a matched resource may become unavailable to the other side of the market, at least for a while. This is especially an issue in online platforms involving human experts as the…

Artificial Intelligence · Computer Science 2018-10-30 Virag Shah , Lennart Gulikers , Laurent Massoulie , Milan Vojnovic

Matrix completion refers to completing a low-rank matrix from a few observed elements of its entries and has been known as one of the significant and widely-used problems in recent years. The required number of observations for exact…

Information Theory · Computer Science 2021-11-02 Hamideh. Sadat Fazael Ardakani , Niloufar Rahmani , Sajad Daei

We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly different model that incorporates the notion of side information in…

Machine Learning · Computer Science 2007-07-13 Majid Fozunbal , Ton Kalker

Between Bayesian and frequentist inference, it's commonly believed that the former is for cases where one has a prior and the latter is for cases where one has no prior. But the prior/no-prior classification isn't exhaustive, and most…

Statistics Theory · Mathematics 2022-11-29 Ryan Martin

Stable matching in a community consisting of men and women is a classical combinatorial problem that has been the subject of intense theoretical and empirical study since its introduction in 1962 in a seminal paper by Gale and Shapley, who…

Data Structures and Algorithms · Computer Science 2021-12-14 Hugo Gimbert , Claire Mathieu , Simon Mauras

Prior specification for nonparametric Bayesian inference involves the difficult task of quantifying prior knowledge about a parameter of high, often infinite, dimension. Realistically, a statistician is unlikely to have informed opinions…

Methodology · Statistics 2012-05-01 David C. Kessler , Peter D. Hoff , David B. Dunson

The problem of assigning probability distributions which objectively reflect the prior information available about experiments is one of the major stumbling blocks in the use of Bayesian methods of data analysis. In this paper the method of…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Ariel Caticha , Roland Preuss

A seller wants to sell an item to $n$ buyers. Buyer valuations are drawn i.i.d. from a distribution unknown to the seller; the seller only knows that the support is included in $[a, b]$. To be robust, the seller chooses a DSIC mechanism…

Theoretical Economics · Economics 2025-01-03 Jerry Anunrojwong , Santiago R. Balseiro , Omar Besbes

Online platforms collect rich information about participants and then share some of this information back with them to improve market outcomes. In this paper we study the following information disclosure problem in two-sided markets: If a…

Theoretical Economics · Economics 2023-09-01 Bar Light , Ramesh Johari , Gabriel Weintraub

Bounded rationality is an important consideration stemming from the fact that agents often have limits on their processing abilities, making the assumption of perfect rationality inapplicable to many real tasks. We propose an…

Information Theory · Computer Science 2021-05-28 Benjamin Patrick Evans , Mikhail Prokopenko

In financial markets valuable information is rarely circulated homogeneously, because of time required for information to spread. However, advances in communication technology means that the 'lifetime' of important information is typically…

Pricing of Securities · Quantitative Finance 2011-08-05 Dorje C. Brody , Yan Tai Law
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