The key insight of the "Generative Adversarial Networks," by Ian Goodfellow et al., is to learn a generative model's loss function at the same time as learning...Alexei A. Efros, Aaron Hertzmann From Communications of the ACM | November 2020
In this overview paper, we describe one particular approach to unsupervised learning via generative modeling called generative adversarial networks. We briefly...Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio From Communications of the ACM | November 2020
"MadMax: Analyzing the Out-of-Gas World of Smart Contracts," by Neville Grech et al., effectively discovers a new smart contract vulnerability, and proposes a detection...Benjamin Livshits From Communications of the ACM | October 2020
We identify gas-focused vulnerabilities and present MadMax: a static program analysis technique that automatically detects gas-focused vulnerabilities with very...Neville Grech, Michael Kong, Anton Jurisevic, Lexi Brent, Bernhard Scholz, Yannis Smaragdakis From Communications of the ACM | October 2020
"Lower Bounds for External Memory Integer Sorting via Network Coding" proves a remarkable connection between how efficiently computers can perform sorting and transmitting...Paul Beame From Communications of the ACM | October 2020
In this paper, we present a tight conditional lower bound on the complexity of external memory sorting of integers.
Alireza Farhadi, Mohammad Taghi Hajiaghayi, Kasper Green Larsen, Elaine Shi From Communications of the ACM | October 2020
There are few algorithms for multi-flow graphs beyond flow accumulation. The authors of "Flood-Risk Analysis on Terrains" take a big step to fill this knowledge...Shashi Shekhar From Communications of the ACM | September 2020
In this paper, we study a number of flood-risk related problems, give an overview of efficient algorithms for them, as well as explore the efficacy and efficiency...Aaron Lowe, Pankaj K. Agarwal, Mathias Rav From Communications of the ACM | September 2020
"Computing Value of Spatiotemporal Information," by Heba Aly et al., describes a technique for computing the monetary value of a person's location data for a potential...Cyrus Shahabi From Communications of the ACM | September 2020
We investigate the intrinsic value of location data in the context of strong privacy, where location information is only available from end users via purchase.
...Heba Aly, John Krumm, Gireeja Ranade, Eric Horvitz From Communications of the ACM | September 2020
We show that by making just a few changes to a parallel/distributed relational database system, such a system can become a competitive platform for scalable linear...Shangyu Luo, Zekai J. Gao, Michael Gubanov, Luis L. Perez, Dimitrije Jankov, Christopher Jermaine From Communications of the ACM | August 2020
Magellan's key insight is that a successful entity matching system must offer a versatile system building paradigm for entity matching that can be easily adapted...Wang-Chiew Tan From Communications of the ACM | August 2020
Entity matching can be viewed as a special class of data science problems and thus can benefit from system building ideas in data science.
AnHai Doan, Pradap Konda, Paul Suganthan G. C., Yash Govind, Derek Paulsen, Kaushik Chandrasekhar, Philip Martinkus, Matthew Christie From Communications of the ACM | August 2020
Can we build purpose-built, warehouse-scale datacenters customized for large-scale arrays of ASIC accelerators or, to use a term coined in the paper by Michael...Parthasarathy Ranganathan From Communications of the ACM | July 2020
This paper distills lessons from Bitcoin ASIC Clouds and applies them to other large scale workloads, showing superior TCO (total cost of ownership) versus CPU...Michael Bedford Taylor, Luis Vega, Moein Khazraee, Ikuo Magaki, Scott Davidson, Dustin Richmond From Communications of the ACM | July 2020
"Spectre Attacks: Exploiting Speculative Execution," by Paul Kocher, et al., reviews how speculative execution and caches can be exploited, presents specific exploits...Mark D. Hill From Communications of the ACM | July 2020
This paper describes practical attacks that combine methodology from side-channel attacks, fault attacks, and return-oriented programming that can read arbitrary...Paul Kocher, Jann Horn, Anders Fogh, Daniel Genkin, Daniel Gruss, Werner Haas, Mike Hamburg, Moritz Lipp, Stefan Mangard, Thomas Prescher, Michael Schwarz, Yuval Yarom From Communications of the ACM | July 2020
"Data-Driven Algorithm Design," by Rishi Gupta and Tim Roughgarden, addresses the issue that the best algorithm to use for many problems depends on what the input...Avrim Blum From Communications of the ACM | June 2020