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Mehrafarin Kazemi

Publications and source records attributed to Mehrafarin Kazemi.

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EFX Allocations and Orientations on Bipartite Multi-graphs: A Complete Picture

We consider the fundamental problem of fairly allocating a set of indivisible items among agents having valuations that are represented by a multi-graph -- here, agents appear as vertices and items as edges between them and each vertex (agent) only values the set of its incident edges (items). The goal is to find a fair, i.e., envy-free up to any item (EFX) allocation. This model has recently been introduced by Christodoulou et al. (EC-23) where they show that EFX allocations always exist on simple graphs for monotone valuations, i.e., where any two agents can share at most one edge (item). A natural question arises as to what happens when we go beyond simple graphs and study various classes of multi-graphs? We answer the above question affirmatively for the valuation class of bipartite multi-graphs and multi-cycles. The main contribution of this work is to establish the existence of EFX allocations on bipartite multi-graphs for monotone valuations and on multi-cycles for MMS-feasible valuations. We also present pseudo-polynomial time algorithms to compute EFX allocations for the above settings. Furthermore, we show that for bipartite multi-graphs with cancelable valuations, EFX allocations can be computed in polynomial time. We thus widen the spectrum where EFX allocations are guaranteed to exist. Next, we study EFX orientations (allocations where every item is assigned to one of its two endpoint agents) and provide a complete characterization of their existence on bipartite multi-graphs in terms of two key parameters: (i) the number of edges shared between any two agents and (ii) the diameter of the graph. Finally, we prove that it is NP-complete to determine whether a given fair division instance on a bipartite multi-graph admits an EFX orientation, even with a constant number of agents.

cs.GT

MMS Approximations Under Additive Leveled Valuations

We study the problem of fairly allocating indivisible goods to a set of agents with additive leveled valuations. A valuation function is called leveled if and only if bundles of larger size have larger value than bundles of smaller size. The economics literature has well studied such valuations. We use the maximin-share (MMS) and EFX as standard notions of fairness. We show that an algorithm introduced by Christodoulou et al. ([11]) constructs an allocation that is EFX and $\frac{\lfloor \frac{m}{n} \rfloor}{\lfloor \frac{m}{n} \rfloor + 1}\text{-MMS}$. In the paper, it was claimed that the allocation is EFX and $\frac{2}{3}\text{-MMS}$. However, the proof of the MMS-bound is incorrect. We give a counter-example to their proof and then prove a stronger approximation of MMS.

cs.GT

TeleBTC: Trustless Wrapped Bitcoin

This paper introduces TeleBTC, a fully decentralized protocol designed to wrap Bitcoin (BTC) on programmable blockchains. The creation of a decentralized wrapped BTC presents challenges due to the non-programmable nature of Bitcoin, making it difficult to custody BTCs in a decentralized way. Existing solutions have addressed this challenge by introducing an external layer of validators who take custody of users' BTCs. However, the security and decentralization of this layer are inferior to the underlying blockchains on which wrapped BTC is built. Moreover, the process of joining or leaving for a validator has become overly complex and expensive. To overcome these limitations, we propose a novel approach that eliminates the need for such an external layer by leveraging the light client bridge protocol. Additionally, we employ economic mechanisms such as incentivization and slashing, resulting in a secure and trust-minimized wrapped BTC solution. With TeleBTC, users can seamlessly transfer their BTC to other blockchains and utilize it within decentralized applications. Furthermore, they can unwrap their TeleBTC and reclaim the native BTC. To address the high costs associated with light client bridges, we present an optimistic approach that minimizes the cost. This approach significantly reduces the operational expenses of running the protocol.

cs.CR