25,124 Result(s)
within
Chapter
**e **an
Algorithm Analysis and Problem Complexity
Artificial Intelligence
Information Systems Applications (incl. Internet)
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Chapter and Conference Paper
Explicitly Simple Near-Tie Auctions
We consider the problem of truthfully auctioning a single item, that can be either fractionally or probabilistically divided among several winners when their bids are sufficiently close to a tie.
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Chapter and Conference Paper
Expressive Graph Informer Networks
Applying machine learning to molecules is challenging because of their natural representation as graphs rather than vectors. Several architectures have been recently proposed for deep learning from molecular g...
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Chapter and Conference Paper
Threshold Tests as Quality Signals: Optimal Strategies, Equilibria, and Price of Anarchy
We study a signaling game between two firms competing to have their product chosen by a principal. The products have (real-valued) qualities, which are drawn i.i.d. from a common prior. The principal aims to ...
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Chapter and Conference Paper
Approximating Nash Social Welfare Under Binary XOS and Binary Subadditive Valuations
We study the problem of allocating indivisible goods among agents in a fair and economically efficient manner. In this context, the Nash social welfare—defined as the geometric mean of agents’ valuations for t...
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Chapter and Conference Paper
Allocating Indivisible Goods to Strategic Agents: Pure Nash Equilibria and Fairness
We consider the problem of fairly allocating a set of indivisible goods to a set of strategic agents with additive valuation functions. We assume no monetary transfers and, therefore, a mechanism in our setting i...
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Chapter and Conference Paper
Complexity of Public Goods Games on Graphs
We study the computational complexity of “public goods games on networks”. In this model, each vertex in a graph is an agent that needs to take a binary decision of whether to “produce a good” or not. Each age...
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Chapter and Conference Paper
Randomized Iterative Methods for Matrix Approximation
Standard tools to update approximations to a matrix A (for example, Quasi-Newton Hessian approximations in optimization) incorporate computationally expensive one-sided samples
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Chapter and Conference Paper
Thresholding Procedure via Barzilai-Borwein Rules for the Steplength Selection in Stochastic Gradient Methods
A crucial aspect in designing a learning algorithm is the selection of the hyperparameters (parameters that are not trained during the learning process). In particular the effectiveness of the stochastic gradi...
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Chapter and Conference Paper
Deep Reinforcement Learning for Optimal Energy Management of Multi-energy Smart Grids
This paper proposes a Deep Reinforcement Learning approach for optimally managing multi-energy systems in smart grids. The optimal control problem of the production and storage units within the smart grid is f...
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Chapter and Conference Paper
A Consumer-Theoretic Characterization of Fisher Market Equilibria
In this paper, we bring consumer theory to bear in the analysis of Fisher markets whose buyers have arbitrary continuous, concave, homogeneous (CCH) utility functions representing locally non-satiated preferen...
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Chapter and Conference Paper
Planning on an Empty Stomach: On Agents with Projection Bias
People often believe that their future preferences will be similar to their current ones. For example, people who go hungry to the supermarket, often buy less healthy food items than when they go on a full sto...
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Chapter and Conference Paper
Building Knowledge Base for the Domain of Economic Mobility of Older Workers
This paper presents the work of building a knowledge base for the domain of economic mobility for older workers. To extract high-quality entities and relations that are important to the specific domain, domain...
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Chapter and Conference Paper
Modular Networks Prevent Catastrophic Interference in Model-Based Multi-task Reinforcement Learning
In a multi-task reinforcement learning setting, the learner commonly benefits from training on multiple related tasks by exploiting similarities among them. At the same time, the trained agent is able to solve...
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Chapter and Conference Paper
A Machine Learning Approach to Daily Capacity Planning in E-Commerce Logistics
Due to the accelerated activity in e-commerce especially since the COVID-19 outbreak, the congestion in the transportation systems is continually increasing, which affects on-time delivery of regular parcels a...
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Chapter and Conference Paper
Decentralized Asset Custody Scheme with Security Against Rational Adversary
Asset custody is a core financial service in which the custodian holds in-safekee** assets on behalf of the client. Although traditional custody service is typically endorsed by centralized authorities, dece...
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Chapter and Conference Paper
PPAD-Complete Pure Approximate Nash Equilibria in Lipschitz Games
Lipschitz games, in which there is a limit \(\lambda \) λ (the Lipschitz va...
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Chapter and Conference Paper
An Optimization Method for Accurate Nonparametric Regressions on Stiefel Manifolds
We consider the problem of regularized nonlinear regression on Riemannian Stiefel manifolds when only few observations are available. In this paper, we introduce a novel geometric method to estimate missing da...
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Chapter and Conference Paper
Online Semi-supervised Learning from Evolving Data Streams with Meta-features and Deep Reinforcement Learning
Online semi-supervised learning (SSL) from data streams is an emerging area of research with many applications due to the fact that it is often expensive, time-consuming, and sometimes even unfeasible to colle...
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Chapter and Conference Paper
Maximal Information Propagation via Lotteries
Propagating information to more people through their friends is becoming an increasingly important technology used in domains such as blockchain, advertising, and social media. To incentivize people to broadca...
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Chapter and Conference Paper
Financial Networks with Singleton Liability Priorities
Financial networks model debt obligations between economic firms. Computational and game-theoretic analyses of these networks have been recent focus of the literature. The main computational challenge in this ...
