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Related papers: Comparing Different Information Levels

200 papers

The Predictive Information is the mutual information between the past and the future, I(X_past; X_future). We hypothesize that capturing the predictive information is useful in RL, since the ability to model what will happen next is…

Machine Learning · Computer Science 2020-10-27 Kuang-Huei Lee , Ian Fischer , Anthony Liu , Yijie Guo , Honglak Lee , John Canny , Sergio Guadarrama

Consider a pair of random variables $(X,Y)$ distributed according to a given joint distribution $p_{XY}$. A curator wishes to maximally disclose information about $Y$, while limiting the information leakage incurred on $X$. Adopting mutual…

Information Theory · Computer Science 2023-01-30 Borzoo Rassouli , Deniz Gündüz

Peer prediction mechanisms are often adopted to elicit truthful contributions from crowd workers when no ground-truth verification is available. Recently, mechanisms of this type have been developed to incentivize effort exertion, in…

Computer Science and Game Theory · Computer Science 2016-12-05 Yang Liu , Yiling Chen

This paper compares statistical experiments in discounted problems, ranging from the simplest ones where the state is fixed and the flow of information exogenous to more complex ones, where the decision-maker controls the flow of…

Theoretical Economics · Economics 2025-04-08 Ludovic Renou , Xavier Venel

We study an optimal investment problem under default risk where related information such as loss or recovery at default is considered as an exogenous random mark added at default time. Two types of agents who have different levels of…

Pricing of Securities · Quantitative Finance 2017-03-02 Ying Jiao , Idris Kharroubi

We study the effectiveness of stochastic side information in deterministic online learning scenarios. We propose a forecaster to predict a deterministic sequence where its performance is evaluated against an expert class. We assume that…

Machine Learning · Computer Science 2023-03-13 Junzhang Jia , Xuetong Wu , Jingge Zhu , Jamie Evans

This paper develops a data-driven approach to Bayesian persuasion. The receiver is privately informed about the prior distribution of the state of the world, the sender knows the receiver's preferences but does not know the distribution of…

Theoretical Economics · Economics 2025-08-06 Maxwell Rosenthal

In medical decision making, we have to choose among several expensive diagnostic tests such that the certainty about a patient's health is maximized while remaining within the bounds of resources like time and money. The expected increase…

Artificial Intelligence · Computer Science 2019-09-19 Sarthak Ghosh , C. R. Ramakrishnan

I study a principal-agent model in which a principal hires an agent to collect information about an unknown continuous state. The agent acquires a signal whose distribution is centered around the state, controlling the signal's precision at…

Theoretical Economics · Economics 2026-05-05 Fan Wu

Goods and services -- public housing, medical appointments, schools -- are often allocated to individuals who rank them similarly but differ in their preference intensities. We characterize optimal allocation rules when individual…

Theoretical Economics · Economics 2021-08-30 Pietro Ortoleva , Evgenii Safonov , Leeat Yariv

Scheduling the transmission of time-sensitive data to multiple users over error-prone communication channels is studied with the goal of minimizing the long-term average age of information (AoI) at the users under a constraint on the…

Machine Learning · Computer Science 2018-06-04 Elif Tuğçe Ceran , Deniz Gündüz , András György

In wireless networks, the rate achieved depends on factors like level of interference, hardware impairments, and channel gain. Often, instantaneous values of some of these factors can be measured, and they provide useful information about…

Information Theory · Computer Science 2022-02-24 Manjesh K. Hanawal , Sumit J. Darak

A wireless system with multiple channels is considered, where each channel has several transmission states. A user learns about the instantaneous state of an available channel by transmitting a control packet in it. Since probing all…

Data Structures and Algorithms · Computer Science 2008-04-11 Sudipto Guha , Kamesh Munagala , Saswati Sarkar

We study a crowdsourcing problem where the platform aims to incentivize distributed workers to provide high quality and truthful solutions without the ability to verify the solutions. While most prior work assumes that the platform and…

Computer Science and Game Theory · Computer Science 2021-04-12 Chao Huang , Haoran Yu , Jianwei Huang , Randall A. Berry

We study a reputational cheap-talk environment in which a judge, who is privately and imperfectly informed about a state, must choose between two speakers of unknown reliability. Exactly one speaker is an expert who perfectly observes the…

Theoretical Economics · Economics 2026-01-05 Johannes Hörner , Paula Onuchic

The information ratio offers an approach to assessing the efficacy with which an agent balances between exploration and exploitation. Originally, this was defined to be the ratio between squared expected regret and the mutual information…

Machine Learning · Computer Science 2021-02-19 Adithya M. Devraj , Benjamin Van Roy , Kuang Xu

We provide algorithms that learn simple auctions whose revenue is approximately optimal in multi-item multi-bidder settings, for a wide range of valuations including unit-demand, additive, constrained additive, XOS, and subadditive. We…

Computer Science and Game Theory · Computer Science 2017-09-04 Yang Cai , Constantinos Daskalakis

The accessible information and the informational power quantify the maximum amount of information that can be extracted from a quantum ensemble and by a quantum measurement, respectively. Here, we investigate the tradeoff between the…

Quantum Physics · Physics 2019-06-05 Michele Dall'Arno , Francesco Buscemi

According to the probability ranking principle, the document set with the highest values of probability of relevance optimizes information retrieval effectiveness given the probabilities are estimated as accurately as possible. The key…

Information Retrieval · Computer Science 2011-08-30 Massimo Melucci

We study the intrinsic limitations of sequential convex optimization through the lens of feedback information theory. In the oracle model of optimization, an algorithm queries an {\em oracle} for noisy information about the unknown…

Information Theory · Computer Science 2011-09-12 Maxim Raginsky , Alexander Rakhlin