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Technical Perspective: How Easy Is It to Describe Hard Polynomials?
From Communications of the ACM

Technical Perspective: How Easy Is It to Describe Hard Polynomials?

"Superpolynomial Lower Bounds Against Low-Depth Algebraic Circuits," by Nutan Limaye et al., achieves a landmark in the larger quest of understanding hardness,...

Taming Algorithmic Priority Inversion in Mission-Critical Perception Pipelines
From Communications of the ACM

Taming Algorithmic Priority Inversion in Mission-Critical Perception Pipelines

This paper discusses algorithmic priority inversion in mission-critical machine inference pipelines used in modern neural-network-based perception subsystems and...

Technical Perspective: Maximum Flow through a Network: A Storied Problem and a Groundbreaking Solution
From Communications of the ACM

Technical Perspective: Maximum Flow through a Network: A Storied Problem and a Groundbreaking Solution

"Almost-Linear-Time Algorithms for Maximum Flow and Minimum-Cost Flow," by Li Chen et al., comes within striking distance of answering the question: "Does maximum...

Technical Perspective: A Rare Glimpse of Tracking Fake Reviews
From Communications of the ACM

Technical Perspective: A Rare Glimpse of Tracking Fake Reviews

"Leveraging Social Media to Buy Fake Reviews," by Sherry He et al., represents a breakthrough in our empirical understanding of fake reviews on Amazon.

Leveraging Social Media to Buy Fake Reviews
From Communications of the ACM

Leveraging Social Media to Buy Fake Reviews

We study the market for fake product reviews on Amazon.com.

Technical Perspective: Can We Uncover Private Backbone Infrastructures?
From Communications of the ACM

Technical Perspective: Can We Uncover Private Backbone Infrastructures?

In "A Manifold View of Connectivity in the Private Backbone Networks of Hyperscalers," Salamatian et al. assemble techniques from the two broad strategies developed...

A Manifold View of Connectivity in the Private Backbone Networks of Hyperscalers
From Communications of the ACM

A Manifold View of Connectivity in the Private Backbone Networks of Hyperscalers

We present a new empirical approach for elucidating connectivity in privately owned and operated backbone networks.

Technical Perspective: Opening the Door to SSD Algorithmics
From Communications of the ACM

Technical Perspective: Opening the Door to SSD Algorithmics

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...

Offline and Online Algorithms for SSD Management
From Communications of the ACM

Offline and Online Algorithms for SSD Management

We explore the problem of reducing high internal overhead of flash media which is referred to as write amplification from an algorithmic perspective, considering...

Technical Perspective: FoundationDB Performs Balancing Act
From Communications of the ACM

Technical Perspective: FoundationDB Performs Balancing Act

FoundationDB, as explored in "FoundationDB: A Distributed Key-Value Store," by Jingyu Zhou et al., pioneered the development of a scalable distributed key-value...

FoundationDB: A Distributed Key-Value Store
From Communications of the ACM

FoundationDB: A Distributed Key-Value Store

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...

Technical Perspective: On Abstractions and Embedded Networks
From Communications of the ACM

Technical Perspective: On Abstractions and Embedded Networks

"Symbol-Synchronous Buses," by Jonathan Oostvogels et al., conceives a notion of a symbol-synchronous bus, which effectively makes a multi-hop wireless network...

Symbol-Synchronous Buses: Deterministic, Low-Latency Wireless Mesh Networking with LEDs
From Communications of the ACM

Symbol-Synchronous Buses: Deterministic, Low-Latency Wireless Mesh Networking with LEDs

We describe a novel networking paradigm that aims to enable a new class of latency-sensitive applications by systematically breaking networking abstractions.

Technical Perspective: The Power of Low-Power GPS Receivers for Nanosats
From Communications of the ACM

Technical Perspective: The Power of Low-Power GPS Receivers for Nanosats

The work explored in "Hummingbird," by Sujay Narayana et al., focuses on the energy consumption of a typical GPS receiver and its operational challenges in a nanosat...

Hummingbird
From Communications of the ACM

Hummingbird: An Energy-Efficient GPS Receiver for Small Satellites

In this work, we elucidate the design of a low-cost, low-power GPS receiver for small satellites.

Technical Perspective: Traffic Classification in the Era of Deep Learning
From Communications of the ACM

Technical Perspective: Traffic Classification in the Era of Deep Learning

"Traffic Classification in an Increasingly Encrypted Web," by Iman Akbari et al., does a great job in reviewing related work in the network traffic classification...

Traffic Classification in an Increasingly Encrypted Web
From Communications of the ACM

Traffic Classification in an Increasingly Encrypted Web

In this paper, we design a novel feature engineering approach used for encrypted Web protocols, and develop a neural network architecture based on stacked long...

Technical Perspective: Physical Layer Resilience through Deep Learning in Software Radios
From Communications of the ACM

Technical Perspective: Physical Layer Resilience through Deep Learning in Software Radios

"Polymorphic Wireless Receivers," by Francesco Restuccia and Tommaso Melodia, tackles the problem of physical layer resilience in wireless systems from a completely...

Polymorphic Wireless Receivers
From Communications of the ACM

Polymorphic Wireless Receivers

We introduce PolymoRF, a deep learning-based polymorphic receiver able to reconfigure itself in real time based on the inferred waveform parameters.

Sampling Near Neighbors in Search for Fairness
From Communications of the ACM

Sampling Near Neighbors in Search for Fairness

We propose several efficient data structures for the exact and approximate variants of the fair near neighbor problem.
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