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Related papers: On Rational Inattention with Arbitrary Choice Sets

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We consider a framework involving behavioral economics and machine learning. Rationally inattentive Bayesian agents make decisions based on their posterior distribution, utility function and information acquisition cost Renyi divergence…

Machine Learning · Computer Science 2018-12-27 William Hoiles , Vikram Krishnamurthy

Accurately predicting the trajectory of surrounding vehicles is a critical challenge for autonomous vehicles. In complex traffic scenarios, there are two significant issues with the current autonomous driving system: the cognitive…

Robotics · Computer Science 2024-09-25 Wen Wei , Jiankun Wang

We study cautious reasoning in finite sequential games played by agents with perfect recall. Our contribution lies in formulating a definition of prudent rationalizability (Heifetz et al. 2021, BEJTE) as an iterative reduction procedure of…

Computer Science and Game Theory · Computer Science 2025-12-01 Nicodemo De Vito

Humans display a tendency to pay more attention to bad outcomes, often in a disproportionate way relative to their statistical occurrence. They also display euphorism, as well as a preference for the current state of affairs (status quo…

Artificial Intelligence · Computer Science 2022-03-24 Michel de Lara

Coordination is a desirable feature in many multi-agent systems such as robotic and socioeconomic networks. We consider a task allocation problem as a binary networked coordination game over an undirected regular graph. Each agent in the…

Systems and Control · Electrical Eng. & Systems 2023-10-02 Yifei Zhang , Marcos M. Vasconcelos

At the beginning of a dynamic game, players may have exogenous theories about how the opponents are going to play. Suppose that these theories are commonly known. Then, players will refine their first-order beliefs, and challenge their own…

Computer Science and Game Theory · Computer Science 2017-07-28 Emiliano Catonini

We analyze continuous optimal transport problems in the so-called Kantorovich form, where we seek a transport plan between two marginals that are probability measures on compact subsets of Euclidean space. We consider the case of…

Optimization and Control · Mathematics 2020-10-28 Christian Clason , Dirk A. Lorenz , Hinrich Mahler , Benedikt Wirth

We derive nearly tight and non-asymptotic convergence bounds for solutions of entropic semi-discrete optimal transport. These bounds quantify the stability of the dual solutions of the regularized problem (sometimes called Sinkhorn…

Artificial Intelligence · Computer Science 2022-05-05 Alex Delalande

An adaptive, adversarial methodology is developed for the optimal transport problem between two distributions $\mu$ and $\nu$, known only through a finite set of independent samples $(x_i)_{i=1..N}$ and $(y_j)_{j=1..M}$. The methodology…

Optimization and Control · Mathematics 2019-02-20 Montacer Essid , Debra Laefer , Esteban G. Tabak

In this paper, the problem of distributed opportunistic channel access in wireless relaying is investigated. A relay network with multiple source-destination pairs and multiple relays is considered. All the source nodes contend through a…

Information Theory · Computer Science 2015-03-19 Zhou Zhang , Hai Jiang

The aim of this paper is to examine the large-scale behavior of dynamical optimal transport on stationary random graphs embedded in $\R^n$. Our primary contribution is a stochastic homogenization result that characterizes the effective…

Probability · Mathematics 2025-07-16 Peter Gladbach , Eva Kopfer

In the field of optimal transport, two prominent subfields face each other: (i) unregularized optimal transport, "\`a-la-Kantorovich", which leads to extremely sparse plans but with algorithms that scale poorly, and (ii)…

Machine Learning · Computer Science 2024-02-19 Ehsan Amid , Frank Nielsen , Richard Nock , Manfred K. Warmuth

Under non-exponential discounting, we develop a dynamic theory for stopping problems in continuous time. Our framework covers discount functions that induce decreasing impatience. Due to the inherent time inconsistency, we look for…

Optimization and Control · Mathematics 2017-03-13 Yu-Jui Huang , Adrien Nguyen-Huu

Reasoning LLMs show improved performance with longer chains of thought. However, recent work has highlighted their tendency to overthink, continuing to revise answers even after reaching the correct solution. We quantitatively confirm this…

Machine Learning · Computer Science 2026-04-09 Xi Wang , James McInerney , Lequn Wang , Nathan Kallus

Constituting highly informative network embeddings is an important tool for network analysis. It encodes network topology, along with other useful side information, into low-dimensional node-based feature representations that can be…

Computation and Language · Computer Science 2019-06-06 Liqun Chen , Guoyin Wang , Chenyang Tao , Dinghan Shen , Pengyu Cheng , Xinyuan Zhang , Wenlin Wang , Yizhe Zhang , Lawrence Carin

Attention is a powerful component of modern neural networks across a wide variety of domains. However, despite its ubiquity in machine learning, there is a gap in our understanding of attention from a theoretical point of view. We propose a…

Machine Learning · Statistics 2020-07-21 James Vuckovic , Aristide Baratin , Remi Tachet des Combes

We consider the problem of minimizing the entropy of a law with respect to the law of a reference branching Brownian motion under density constraints at an initial and final time. We call this problem the branching Schr\"odinger problem by…

Probability · Mathematics 2021-12-14 Aymeric Baradat , Hugo Lavenant

In this paper, we investigate a general delay-aware channel allocation problem where the number of channels is less than that of users. Due to the proliferation of delay sensitive applications, the objective of our problem is chosen to be…

Information Theory · Computer Science 2020-05-22 Saad Kriouile , Mohamad Assaad , Maialen Larranaga

We study a simple example of a sequential game illustrating problems connected with making rational decisions that are universal for social sciences. The set of chooser's optimal decisions that manifest his preferences in case of a constant…

Physics and Society · Physics 2007-05-23 Edward W. Piotrowski , Marcin Makowski

Attention mechanisms play a central role in NLP systems, especially within recurrent neural network (RNN) models. Recently, there has been increasing interest in whether or not the intermediate representations offered by these modules may…

Computation and Language · Computer Science 2019-09-06 Sarah Wiegreffe , Yuval Pinter
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