Sign In

Communications of the ACM

Latest Research



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...

OpenFab
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...

Compressed Linear Algebra for Declarative Large-Scale 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

Technical Perspective: To Do or Not To Do: Extending SQL with Integer Linear Programming?

"Scalable Computation of High-Order Optimization Queries," by Brucato et al., makes a case for marrying the well-established paradigms of constrained optimization...

Scalable Computation of High-Order Optimization Queries
From Communications of the ACM

Scalable Computation of High-Order Optimization Queries

We present a complete system that supports package queries, a new query model that extends traditional database queries to handle complex constraints and preferences...

From Communications of the ACM

Technical Perspective: Photorealistic Facial Digitization and Manipulation

If facial performance capture is possible for conventional RGB videos in real time, then believable facial expressions can be transferred effortlessly from one...

Face2Face
From Communications of the ACM

Face2Face: Real-Time Face Capture and Reenactment of RGB Videos

Face2Face is an approach for real-time facial reenactment of a monocular target video sequence. Our goal is to animate the facial expressions of the target video...

From Communications of the ACM

Technical Perspective: Making Sleep Tracking More ­User Friendly

"LIBS: A Bioelectrical Sensing System from Human Ears for Staging Whole-Night Sleep Study" provides a nice balance in terms of minimizing the burden on users and...

LIBS
From Communications of the ACM

LIBS: A Bioelectrical Sensing System from Human Ears for Staging Whole-Night Sleep Study

We explore a new form of wearable systems, called LIBS, that can continuously record biosignals such as brain wave, eye movements, and facial muscle contractions...

From Communications of the ACM

Technical Perspective: The Future of MPI

"Enabling Highly Scalable Remote Memory Access Programming with MPI-3 One Sided" convincingly shows that the potential of MPI one-sided communication can be realized...

Enabling Highly Scalable Remote Memory Access Programming with MPI-3 One Sided
From Communications of the ACM

Enabling Highly Scalable Remote Memory Access Programming with MPI-3 One Sided

In this work, we design and develop bufferless protocols that demonstrate how to implement the MPI-3 RMA interface and support scaling to millions of cores.

From Communications of the ACM

Technical Perspective: Graphs, Betweenness Centrality, and the GP­U

"Accelerating GPU Betweenness Centrality" by McLaughlin and Bader ably addresses the challenges to authors of efficient graph implementations in the important context...

Accelerating GP­U Betweenness Centrality
From Communications of the ACM

Accelerating GP­U Betweenness Centrality

We present a hybrid GPU implementation that provides good performance on graphs of arbitrary structure rather than just scale-free graphs as was done previously...

From Communications of the ACM

Technical Perspective: The Rewards of Selfish Mining

"Majority Is Not Enough: Bitcoin Mining Is Vulnerable," by Eyal and Sirer, questions the 2009 Bitcoin white paper's implicit assumption of perfect information—that...

Majority Is Not Enough
From Communications of the ACM

Majority Is Not Enough: Bitcoin Mining Is Vulnerable

We propose a practical modification to the Bitcoin protocol that protects Bitcoin in the general case.

From Communications of the ACM

Technical Perspective: Breaking the Mold of Machine Learning

"Never-Ending Learning" is the latest and one of the most compelling incarnations of Tom Mitchell and his collaborators' research investigating how to broaden the...

Never-Ending Learning
From Communications of the ACM

Never-Ending Learning

In this paper we define more precisely the never-ending learning paradigm for machine learning, and present one case study: the Never-Ending Language Learner (NELL)...

From Communications of the ACM

Technical Perspective: Expressive Probabilistic Models and Scalable Method of Moments

The authors of "Learning Topic Models—Provably and Efficiently," developed a new method for fitting topic models and at large scale.

Learning Topic Models – Provably and Efficiently
From Communications of the ACM

Learning Topic Models – Provably and Efficiently

This article shows that some new theoretical algorithms that have provable guarantees can be adapted to yield highly practical tools for topic modeling.
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account