Communications of the ACM
Latest Research
From Communications of the ACM
Generative Adversarial Networks
In this overview paper, we describe one particular approach to unsupervised learning via generative modeling called generative adversarial networks. We briefly...
From Communications of the ACM
Technical Perspective: Entity Matching with Magellan
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...
From Communications of the ACM
Magellan: Toward Building Ecosystems of Entity Matching Solutions
Entity matching can be viewed as a special class of data science problems and thus can benefit from system building ideas in data science.
From Communications of the ACM
Technical Perspective: Algorithm Selection as a Learning Problem
"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...
From Communications of the ACM
Data-Driven Algorithm Design
We model the problem of identifying a good algorithm from data as a statistical learning problem.
From Communications of the ACM
Technical Perspective: An Answer to Fair Division's Most Enigmatic Question
The envy-free cake-cutting problem stood its ground for two decades, until it was cracked by Aziz and Mackenzie. Their solution is presented in "A Bounded and Envy...
From Communications of the ACM
A Bounded and Envy-Free Cake Cutting Algorithm
We report on our algorithm that resolved the well-studied cake cutting problem in which the goal is to find an envy-free allocation of a divisible resource based...
From Communications of the ACM
Technical Perspective: A Perspective on Pivot Tracing
Instead of handing trace records off to a collector for long-term storage and future processing, the system described in "Pivot Tracing: Dynamic Causal Monitoring...
From Communications of the ACM
Pivot Tracing: Dynamic Causal Monitoring for Distributed Systems
This paper presents Pivot Tracing, a monitoring framework for distributed systems, which addresses the limitations of today's monitoring and diagnosis tools by...
From Communications of the ACM
Technical Perspective: Lighting the Way to Visual Privacy
"Automating Visual Privacy Protection Using a Smart LED," presents a new technique to address the issue of cameras capturing proprietary or private information—it...
From Communications of the ACM
Automating Visual Privacy Protection Using a Smart LED
We introduce LiShield, which automatically protects a physical scene against photographing, by illuminating it with smart LEDs flickering in specialized waveforms...
From Communications of the ACM
Technical Perspective: Bootstrapping a Future of Open Source, Specialized Hardware
OpenPiton research is one of the watershed moments in the fundamental shift toward the construction of an open source ecosystem for implementing prototype chips...
From Communications of the ACM
OpenPiton: An Open Source Hardware Platform For Your Research
We present OpenPiton, an open source framework for building scalable architecture research prototypes from one core to 500 million cores.
From Communications of the ACM
Technical Perspective: A Whitebox Solution for Blackbox-Like Behaviors
DeepXplore brings a software testing perspective to deep neural networks and, in doing so, creates the opportunity for enormous amounts of follow-on work in several...
From Communications of the ACM
DeepXplore: Automated Whitebox Testing of Deep Learning Systems
We design, implement, and evaluate DeepXplore, the first white-box framework for systematically testing real-world deep learning systems.
From Communications of the ACM
Technical Perspective: From Virtual Worlds to Digital Fabrication
The authors of "OpenFab" propose to revisit the processing pipeline that turns a 3D model into machine instructions in light of the solutions developed in computer...
From Communications of the ACM
OpenFab: A Programmable Pipeline for Multimaterial Fabrication
We present OpenFab, a programmable pipeline for synthesis of multimaterial 3D printed objects that is inspired by RenderMan and modern GPU pipelines.
From Communications of the ACM
Technical Perspective: Compressing Matrices for Large-Scale Machine Learning
Demand for more powerful big data analytics solutions has spurred the development of novel programming models, abstractions, and platforms. "Scaling Machine Learning...
From Communications of the ACM
Compressed Linear Algebra for Declarative Large-Scale Machine Learning
General-purpose compression struggles to achieve both good compression ratios and fast decompression for blockwise uncompressed operations. Therefore, we introduce...
From Communications of the ACM