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Combinatorial auctions are formulated as frustrated lattice gases on sparse random graphs, allowing the determination of the optimal revenue by methods of statistical physics. Transitions between computationally easy and hard regimes are…

Statistical Mechanics · Physics 2009-11-11 Tobias Galla , Michele Leone , Matteo Marsili , Mauro Sellitto , Martin Weigt , Riccardo Zecchina

We consider interactive learning and covering problems, in a setting where actions may incur different costs, depending on the response to the action. We propose a natural greedy algorithm for response-dependent costs. We bound the…

Machine Learning · Computer Science 2018-11-21 Sivan Sabato

In this article, we present two new greedy algorithms for the computation of the lowest eigenvalue (and an associated eigenvector) of a high-dimensional eigenvalue problem, and prove some convergence results for these algorithms and their…

Numerical Analysis · Mathematics 2013-04-10 Eric Cancès , Virginie Ehrlacher , Tony Lelièvre

The paper gives a systematic study of the approximate versions of three greedy-type algorithms that are widely used in convex optimization. By approximate version we mean the one where some of evaluations are made with an error. Importance…

Machine Learning · Statistics 2014-12-11 Vladimir Temlyakov

We consider the problem of optimizing lifetime consumption under a habit formation model, both with and without an exogenous pension. Unlike much of the existing literature, we apply a power utility to the ratio of consumption to habit,…

Portfolio Management · Quantitative Finance 2023-05-09 Snezhana Kirusheva , Thomas S. Salisbury

Combinatorial optimization is a broadly attractive area for potential quantum advantage, but no quantum algorithm has yet made the leap. Noise in quantum hardware remains a challenge, and more sophisticated quantum-classical algorithms are…

This paper investigates two issues on identification of switched linear systems: persistence of excitation and numerical algorithms. The main contribution is a much weaker condition on the regressor to be persistently exciting that…

Systems and Control · Electrical Eng. & Systems 2021-12-07 Biqiang Mu , Tianshi Chen , Changming Cheng , Er-Wei Bai

We revisit the problem of designing optimal, individually rational matching mechanisms (in a general sense, allowing for cycles in directed graphs), where each player --- who is associated with a subset of vertices --- matches as many of…

Data Structures and Algorithms · Computer Science 2016-09-15 Avrim Blum , Ioannis Caragiannis , Nika Haghtalab , Ariel D. Procaccia , Eviatar B. Procaccia , Rohit Vaish

When users access shared resources in a selfish manner, the resulting societal cost and perceived users' cost is often higher than what would result from a centrally coordinated optimal allocation. While several contributions in mechanism…

Computer Science and Game Theory · Computer Science 2024-03-08 Leonardo Pedroso , Andrea Agazzi , W. P. M. H. Heemels , Mauro Salazar

The coordinate-exchange algorithm is commonly used to construct optimal experimental designs. Every execution of the coordinate-exchange algorithm produces a new, seemingly random, order of the selected design points. In this short…

Methodology · Statistics 2026-03-24 Arno Strouwen , Peter Goos

The subset sum algorithm is a natural heuristic for the classical Bin Packing problem: In each iteration, the algorithm finds among the unpacked items, a maximum size set of items that fits into a new bin. More than 35 years after its first…

Computer Science and Game Theory · Computer Science 2009-07-27 Leah Epstein , Elena Kleiman , Julian Mestre

Two general algorithms based on opportunity costs are given for approximating a revenue-maximizing set of bids an auctioneer should accept, in a combinatorial auction in which each bidder offers a price for some subset of the available…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Karhan Akcoglu , James Aspnes , Bhaskar DasGupta , Ming-Yang Kao

Submodular optimization is a special class of combinatorial optimization arising in several machine learning problems, but also in cooperative control of complex systems. In this paper, we consider agents in an asynchronous, unreliable and…

Systems and Control · Computer Science 2018-12-17 Andrea Testa , Ivano Notarnicola , Giuseppe Notarstefano

Motivated by a wide range of applications in data mining and machine learning, we consider the problem of maximizing a submodular function subject to supermodular cost constraints. In contrast to the well-understood setting of cardinality…

Data Structures and Algorithms · Computer Science 2026-02-19 Ajitesh Srivastava , Shanghua Teng

We discuss the upper and lower estimates for the rate of convergence of Pure and Orthogonal Greedy Algorithms for dictionary with bounded cumulative coherence.

Numerical Analysis · Mathematics 2009-11-10 Eugene Livshitz

Many algorithms for maximizing a monotone submodular function subject to a knapsack constraint rely on the natural greedy heuristic. We present a novel refined analysis of this greedy heuristic which enables us to: $(1)$ reduce the…

Data Structures and Algorithms · Computer Science 2021-03-16 Ariel Kulik , Roy Schwartz , Hadas Shachnai

We consider mechanisms that provide traders the opportunity to exchange commodity $i$ for commodity $j$, for certain ordered pairs $ij$. Given any connected graph $G$ of opportunities, we show that there is a unique mechanism $M_{G}$ that…

Computer Science and Game Theory · Computer Science 2024-09-24 Pradeep Dubey , Siddhartha Sahi , Martin Shubik

Multidimensional combinatorial substitutions are rules that replace symbols by finite patterns of symbols in $\mathbb Z^d$. We focus on the case where the patterns are not necessarily rectangular, which requires a specific description of…

Discrete Mathematics · Computer Science 2014-06-27 Timo Jolivet , Jarkko Kari

In this paper we consider multidimensional mechanism design problem for selling discrete substitutable items to a group of buyers. Previous work on this problem mostly focus on stochastic description of valuations used by the seller.…

Computer Science and Game Theory · Computer Science 2017-01-05 Maciej Drwal

The random cost problem is the problem of finding the minimum in an exponentially long list of random numbers. By definition, this problem cannot be solved faster than by exhaustive search. It is shown that a classical NP-hard optimization…

Disordered Systems and Neural Networks · Physics 2009-10-31 Stephan Mertens