Communications of the ACM
Latest Research
From Communications of the ACM
Technical Perspective: The Quest for Optimal Multi-Item Auctions
"Optimal Auctions Through Deep Learning," by Paul Dütting et al., contributes a very interesting and forward-looking new take on the optimal multi-item mechanism...
From Communications of the ACM
Optimal Auctions Through Deep Learning
We overview recent research results that show how tools from deep learning are shaping up to become a powerful tool for the automated design of near-optimal auctions...
From Communications of the ACM
Technical Perspective: Tracking Pandemic-Driven Internet Traffic
"A Year in Lockdown," by Anja Feldmann, et al., offers a detailed look at how Internet traffic changed during the COVID-19 pandemic.
From Communications of the ACM
A Year in Lockdown: How the Waves of COVID-19 Impact Internet Traffic
We review the impact of the first year of the COVID-19 pandemic on Internet traffic in order to analyze its performance.
From Communications of the ACM
Technical Perspective: An Elegant Model for Deriving Equations
"Deriving Equations from Sensor Data Using Dimensional Function Synthesis," by Vasileios Tsoutsouras, et al., addresses the key problem of discovering relationships...
From Communications of the ACM
Deriving Equations from Sensor Data Using Dimensional Function Synthesis
We present a new method, which we call dimensional function synthesis, for deriving functions that model the relationship between multiple signals in a physical...
From Communications of the ACM
Technical Perspective: Race Logic Presents a Novel Form of Encoding
"In-Sensor Classification With Boosted Race Trees," by Georgios Tzimpragos, et al., proposes a surprising, novel, and creative approach to post-Moore's Law computing...
From Communications of the ACM
In-Sensor Classification With Boosted Race Trees
We demonstrate the potential of a novel form of encoding, race logic, in which information is represented as the delay in the arrival of a signal.
From Communications of the ACM
Technical Perspective: A Chiplet Prototype System for Deep Learning Inference
"Simba," by Yakun Sophia Shao, et al., presents a scalable deep learning accelerator architecture that tackles issues ranging from chip integration technology to...
From Communications of the ACM
Simba: Scaling Deep-Learning Inference with Chiplet-Based Architecture
This work investigates and quantifies the costs and benefits of using multi-chip-modules with fine-grained chiplets for deep learning inference, an application...
From Communications of the ACM
Technical Perspective: Robust Statistics Tackle New Problems
"Robustness Meets Algorithms," by Ilias Diakonikolas, et al., represents the beginning of a long and productive line of work on robust statistics in high dimensions...
From Communications of the ACM
Robustness Meets Algorithms
We give the first efficient algorithm for estimating the parameters of a high-dimensional Gaussian that is able to tolerate a constant fraction of corruptions that...
From Communications of the ACM
Technical Perspective: A Logical Step Toward the Graph Isomorphism Problem
In "Isomorphism, Canonization, and Definability for Graphs of Bounded Rank Width," Grohe and Neuen show that the Weisfeiler-Leman algorithm in its plain form solves...
From Communications of the ACM
Isomorphism, Canonization, and Definability for Graphs of Bounded Rank Width
In this paper we study the graph isomorphism problem and the closely related graph canonization problem as well as logical definability and descriptive complexity...
From Communications of the ACM
Technical Perspective: The Strength of SuRF
The authors of "Succinct Range Filters" make a critical and insightful observation: For a given set of queries, the upper levels of the trie incur many more accesses...
From Communications of the ACM
Succinct Range Filters
We present the Succinct Range Filter (SuRF), a fast and compact data structure for approximate membership tests.
From Communications of the ACM
Technical Perspective: Why Don't Today's Deep Nets Overfit to Their Training Data?
"Understanding Deep Learning (Still) Requires Rethinking Generalization," Chiyuan Zhang, et al., brings a fundamental new theoretical challenge: Why don't today's...
From Communications of the ACM
Understanding Deep Learning (Still) Requires Rethinking Generalization
In this work, we presented a simple experimental framework for interrogating purported measures of generalization.
From Communications of the ACM
Technical Perspective: Localizing Insects Outdoors
"3D Localization for Subcentimeter-Sized Devices," by Iyer, et al., neatly separates and solves the problems of robotic locomotion, sensing, localization, and communications...
From Communications of the ACM