"Leveraging Social Media to Buy Fake Reviews," by Sherry He et al., represents a breakthrough in our empirical understanding of fake reviews on Amazon.
Shreyas Sekar From Communications of the ACM | October 2023
The authors of "Offline and Online Algorithms for SSD Management" propose a more accurate theoretical model of flash-based SSDs that views each page as containing...Ramesh K. Sitaraman From Communications of the ACM | July 2023
We explore the problem of reducing high internal overhead of flash media which is referred to as write amplification from an algorithmic perspective, considering...Tomer Lange, Joseph (Seffi) Naor, Gala Yadgar From Communications of the ACM | July 2023
FoundationDB, as explored in "FoundationDB: A Distributed Key-Value Store," by Jingyu Zhou et al., pioneered the development of a scalable distributed key-value...Alfons Kemper From Communications of the ACM | June 2023
FoundationDB, an open-source transactional key-value store, is one of the first systems to combine the flexibility and scalability of NoSQL architectures with the...Jingyu Zhou, Meng Xu, Alexander Shraer, Bala Namasivayam, Alex Miller, Evan Tschannen, Steve Atherton, Andrew J. Beamon, Rusty Sears, John Leach, Dave Rosenthal, Xin Dong, Will Wilson, Ben Collins, David Scherer, Alec Grieser, Yang Liu, Alvin Moore, Bhaskar Muppana, Xiaoge Su, Vishesh Yadav From Communications of the ACM | June 2023
The breakthrough of "Achieving High Performance the Functional Way," by Bastian Hagedorn et al., is in fundamentally rethinking the design of user-schedulable languages...Jonathan Ragan-Kelley From Communications of the ACM | March 2023
We show how to employ functional programming techniques to solve with elegance the challenge of using a high-level language to describe functionality and a separate...Bastian Hagedorn, Johannes Lenfers, Thomas Kœhler, Xueying Qin, Sergei Gorlatch, Michel Steuwer From Communications of the ACM | March 2023
"Proving Data-Poisoning Robustness in Decision Trees," by Samuel Drews et al., addresses the challenge of processing an intractably large set of trained models...Martin Vechev From Communications of the ACM | February 2023
We present a sound verification technique based on abstract interpretation and implement it in a tool called Antidote, which abstractly trains decision trees for...Samuel Drews, Aws Albarghouthi, Loris D'Antoni From Communications of the ACM | February 2023
"DIAMetrics," by Shaleen Deep et al., describes a versatile framework from Google for automatic extraction of benchmarks and their distributed execution and performance...Peter Boncz From Communications of the ACM | December 2022
This paper introduces DIAMetrics: a novel framework for end-to-end benchmarking and performance monitoring of query engines.
Shaleen Deep, Anja Gruenheid, Kruthi Nagaraj, Hiro Naito, Jeff Naughton, Stratis Viglas From Communications of the ACM | December 2022
We propose several efficient data structures for the exact and approximate variants of the fair near neighbor problem.
Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri From Communications of the ACM | August 2022
In "Sampling Near Neighbors in Search for Fairness," Aumüller et al. investigate a basic problem in similarity search called near neighbor in the context of fair...Qin Zhang From Communications of the ACM | August 2022
"Expressive Querying for Accelerating Visual Analytics," by Tarique Siddiqui et al., provides a general abstraction, along with advanced interfaces, focusing on...Bill Howe From Communications of the ACM | July 2022
In this work, we introduce the problem of visualization search and highlight two underlying challenges of search enumeration and visualization matching.
Tarique Siddiqui, Paul Luh, Zesheng Wang, Karrie Karahalios, Aditya G. Parameswaran From Communications of the ACM | July 2022
"On Sampled Metrics for Item Recommendation," by Walid Krichene and Steffen Rendle, exposes a crucial aspect for the evaluation of algorithms and tools: the impact...Fabio Vandin From Communications of the ACM | July 2022
This paper investigates sampled metrics and shows that it is possible to improve the quality of sampled metrics by applying a correction, obtained by minimizing...Walid Krichene, Steffen Rendle From Communications of the ACM | July 2022
"Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication" addresses the problem of selecting code rates to optimize system performance...Emina Soljanin From Communications of the ACM | May 2022
We propose a rateless fountain coding strategy and prove that its latency is asymptotically equal to ideal load balancing, and it performs asymptotically zero redundant...Ankur Mallick, Malhar Chaudhari, Utsav Sheth, Ganesh Palanikumar, Gauri Joshi From Communications of the ACM | May 2022