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We have investigated the essential ingredients allowing a system to show Self Organized Criticality (SOC) in its collective behavior. Using the Bak-Sneppen model of biological evolution as our paradigm, we show that the random microscopic…

Condensed Matter · Physics 2009-10-30 Paolo De Los Rios , Angelo Valleriani , José Luis Vega

Behavior cloning provides strong imitation learning guarantees when training and test environments share the same dynamics. However, in many deployment settings the test environment's transitions differ from training, and classical offline…

Machine Learning · Computer Science 2026-05-19 Surbhi Goel , Jonathan Pei , James Wang

No-Cloning and No-Deleting theorems are verified with the constraint on local state transformations via the existence of incomparable states. Assuming the existence of exact cloning or deleting operation defined on a minimum number of two…

Quantum Physics · Physics 2007-11-04 Amit Bhar , Indrani Chattopadhyay , Debasis Sarkar

A simple mechanism for allocating indivisible resources is sequential allocation in which agents take turns to pick items. We focus on possible and necessary allocation problems, checking whether allocations of a given form occur in some or…

Artificial Intelligence · Computer Science 2014-12-09 Haris Aziz , Toby Walsh , Lirong Xia

We initiate an investigation how the fundamental concept of independence can be represented effectively in the presence of incomplete information in relational databases. The concepts of possible and certain independence are proposed, and…

Databases · Computer Science 2025-10-10 Miika Hannula , Minna Hirvonen , Juha Kontinen , Sebastian Link

Committee scoring voting rules are multiwinner analogues of positional scoring rules which constitute an important subclass of single-winner voting rules. We identify several natural subclasses of committee scoring rules, namely, weakly…

Computer Science and Game Theory · Computer Science 2018-02-20 Piotr Faliszewski , Piotr Skowron , Arkadii Slinko , Nimrod Talmon

Iterative learning control (ILC) is a control strategy for repetitive tasks wherein information from previous runs is leveraged to improve future performance. Optimization-based ILC (OB-ILC) is a powerful design framework for constrained…

Systems and Control · Electrical Eng. & Systems 2022-05-27 Dominic Liao-McPherson , Efe C. Balta , Alisa Rupenyan , John Lygeros

Lower bounds and impossibility results in distributed computing are both intellectually challenging and practically important. Hundreds if not thousands of proofs appear in the literature, but surprisingly, the vast majority of them apply…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-13 Guy Goren , Yoram Moses , Alexander Spiegelman

Electing a committee of size k from m alternatives (k < m) is an interesting problem under the multi-winner voting rules. However, very few committee selection rules found in the literature consider the coalitional possibilities among the…

Theoretical Economics · Economics 2023-08-08 Ritu Dutta , Rajnish Kumnar , Surajit Borkotokey

STIT logic is a prominent framework for the analysis of multi-agent choice-making. In the available deontic extensions of STIT, the principle of Ought-implies-Can (OiC) fulfills a central role. However, in the philosophical literature a…

Logic in Computer Science · Computer Science 2026-04-02 Kees van Berkel , Tim S. Lyon

In strategic classification, agents modify their features, at a cost, to ideally obtain a positive classification from the learner's classifier. The typical response of the learner is to carefully modify their classifier to be robust to…

Machine Learning · Computer Science 2024-02-15 Lee Cohen , Saeed Sharifi-Malvajerdi , Kevin Stangl , Ali Vakilian , Juba Ziani

Algorithmic decision-making in practice must be fair for legal, ethical, and societal reasons. To achieve this, prior research has contributed various approaches that ensure fairness in machine learning predictions, while comparatively…

Machine Learning · Computer Science 2023-10-10 Dennis Frauen , Valentyn Melnychuk , Stefan Feuerriegel

Off-policy evaluation (OPE) is to evaluate a target policy with data generated by other policies. Most previous OPE methods focus on precisely estimating the true performance of a policy. We observe that in many applications, (1) the end…

Machine Learning · Computer Science 2022-06-22 Yue Jin , Yue Zhang , Tao Qin , Xudong Zhang , Jian Yuan , Houqiang Li , Tie-Yan Liu

Probabilistic independence is a useful concept for describing the result of random sampling---a basic operation in all probabilistic languages---and for reasoning about groups of random variables. Nevertheless, existing verification methods…

Programming Languages · Computer Science 2020-07-21 Gilles Barthe , Justin Hsu , Kevin Liao

One-Class Classification (OCC) is a special case of multi-class classification, where data observed during training is from a single positive class. The goal of OCC is to learn a representation and/or a classifier that enables recognition…

Computer Vision and Pattern Recognition · Computer Science 2021-01-11 Pramuditha Perera , Poojan Oza , Vishal M. Patel

We study the problem of deriving a specification for a third-party component, based on the specification of the system and the environment in which the component is supposed to reside. Particularly, we are interested in using component…

Software Engineering · Computer Science 2013-03-06 Neda Noroozi , Mohammad Reza Mousavi , Tim A. C. Willemse

To understand and summarize approval preferences and other binary evaluation data, it is useful to order the items on an axis which explains the data. In a political election using approval voting, this could be an ideological left-right…

Computer Science and Game Theory · Computer Science 2024-05-08 Théo Delemazure , Chris Dong , Dominik Peters , Magdaléna Tydrichová

We consider the problem of whether a given decision model, working with structured data, has individual fairness. Following the work of Dwork, a model is individually biased (or unfair) if there is a pair of valid inputs which are close to…

Machine Learning · Computer Science 2020-06-23 Philips George John , Deepak Vijaykeerthy , Diptikalyan Saha

Voting rules may implement the will of the society when all eligible voters vote, and only them. However, they may fail to do so when sybil (fake or duplicate) votes are present and when only some honest (non sybil) voters actively…

Multiagent Systems · Computer Science 2025-10-22 Reshef Meir , Gal Shahaf , Ehud Shapiro , Nimrod Talmon

We study random joint choice rules, allowing for interdependence of choice across agents. These capture random choice by multiple agents, or a single agent across goods or time periods. Our interest is in separable choice rules, where each…

Theoretical Economics · Economics 2023-03-07 Christopher P. Chambers , Yusufcan Masatlioglu , Christopher Turansick
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