2019 Principles of Distributed Computing Doctoral Dissertation Award

P. Jayanti, N. Lynch, B. Patt-Shamir, U. Schmid
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Abstract

The winner of the 2019 Principles of Distributed Computing Doctoral Dissertation Award is Dr. Sepehr Assadi for his dissertation Combinatorial Optimization on Massive Datasets: Streaming, Distributed, and Massively Parallel Computation, written under the supervision of Prof. Sanjeev Khanna at the University of Pennsylvania. The thesis resolves a number of long-standing problems in the exciting and still relatively new area of sublinear computation. The area of sublinear computation focuses on design of algorithms that use sublinear space, time, or communication to solve global optimization problems on very large datasets. In addition to addressing a wide range of different problems, comprising graph optimization problems (matching, vertex cover, and connectivity), submodular optimization (set cover and maximum coverage), and resource-constrained optimization (combinatorial auctions and learning), these problems are studied in three different models of computation, namely, streaming algorithms, multiparty communication, and massively parallel computation (MPC). The thesis also reveals interesting relations between these different models, including generic algorithmic and analysis techniques that can be applied in all of them. For many fundamental optimization problems, the thesis gives asymptotically matching algorithmic and intractability results, completely resolving several long-standing problems. This is accomplished by using a broad spectrum of mathematical methods in very detailed and intricate proofs. In addition to a wide variety of classic techniques, ranging from graph theory, combinatorics, probability, linear algebra and calculus, it also makes heavy use of communication complexity and information theory, for example. Sepehr's dissertation work has been published in a remarkably large number of top-conference papers. It received multiple best paper awards and multiple special issue invitations, as well as two invitations to the Highlights of Algorithms (HALG) conference. Due to its contributions to the field of distributed computing and all the merits mentioned above, the award committee unanimously selected this thesis as the winner of the 2019 Principles of Distributed Computing Doctoral Dissertation Award.
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2019年《分布式计算原理》博士论文奖
2019年分布式计算原理博士论文奖的获得者是Sepehr Assadi博士,他的论文《大规模数据集的组合优化:流,分布式和大规模并行计算》是在宾夕法尼亚大学Sanjeev Khanna教授的监督下撰写的。本文解决了一些长期存在的问题,在令人兴奋的和仍然相对较新的亚线性计算领域。亚线性计算领域侧重于设计使用亚线性空间、时间或通信来解决非常大数据集上的全局优化问题的算法。除了解决各种不同的问题,包括图优化问题(匹配、顶点覆盖和连通性)、子模块优化(集合覆盖和最大覆盖)和资源约束优化(组合拍卖和学习),这些问题还在三种不同的计算模型中进行了研究,即流算法、多方通信和大规模并行计算(MPC)。本文还揭示了这些不同模型之间的有趣关系,包括可以应用于所有模型的通用算法和分析技术。对于许多基本优化问题,本文给出了渐近匹配算法和求解结果,彻底解决了几个长期存在的问题。这是通过在非常详细和复杂的证明中使用广泛的数学方法来完成的。除了各种各样的经典技术,从图论,组合学,概率论,线性代数和微积分,它还大量使用通信复杂性和信息论,例如。Sepehr的论文发表在相当多的顶级会议论文中。它获得了多个最佳论文奖和多个特刊邀请,以及两次受邀参加算法亮点(HALG)会议。鉴于该论文在分布式计算领域的贡献和上述所有优点,评奖委员会一致选择该论文为2019年分布式计算原理博士论文奖得主。
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