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Technical Perspective: Beautiful Symbolic Abstractions for Safe and Secure Machine Learning
From Communications of the ACM

Technical Perspective: Beautiful Symbolic Abstractions for Safe and Secure Machine Learning

"Proving Data-Poisoning Robustness in Decision Trees," by Samuel Drews et al., addresses the challenge of processing an intractably large set of trained models...

Proving Data-Poisoning Robustness in Decision Trees
From Communications of the ACM

Proving Data-Poisoning Robustness in Decision Trees

We present a sound verification technique based on abstract interpretation and implement it in a tool called Antidote, which abstractly trains decision trees for...

Technical Perspective: The Impact of Auditing for Algorithmic Bias
From Communications of the ACM

Technical Perspective: The Impact of Auditing for Algorithmic Bias

"Actionable Auditing Revisited," by Inioluwa Deborah Raji and Joy Buolamwini, examines how companies producing commercial facial classification software responded...

Actionable Auditing Revisited
From Communications of the ACM

Actionable Auditing Revisited: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products

This paper investigates the commercial impact of Gender Shades, the first algorithmic audit of gender- and skin-type performance disparities in commercial facial...

Technical Perspective: The 'Art' of Automatic Benchmark Extraction
From Communications of the ACM

Technical Perspective: The 'Art' of Automatic Benchmark Extraction

"DIAMetrics," by Shaleen Deep et al., describes a versatile framework from Google for automatic extraction of benchmarks and their distributed execution and performance...

DIAMETRICS
From Communications of the ACM

DIAMETRICS: Benchmarking Query Engines at Scale

This paper introduces DIAMetrics: a novel framework for end-to-end benchmarking and performance monitoring of query engines.

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: Achieve Big with Devices that Track Small Things
From Communications of the ACM

Technical Perspective: Achieve Big with Devices that Track Small Things

"AuraRing: Precise Electromagnetic Finger Tracking," by Farshid Salemi Parizi, Eric Whitmire, and Shwetak Patel, details the AuraRing system's remarkable ability...

AuraRing
From Communications of the ACM

AuraRing: Precise Electromagnetic Finger Tracking

We present AuraRing, a wearable magnetic tracking system designed for tracking fine-grained finger movement.

Technical Perspective: The Effectiveness of Security Measures
From Communications of the ACM

Technical Perspective: The Effectiveness of Security Measures

"Measuring Security Practices," by Louis F. DeKoven et al., provide a unique perspective into how users choose to implement common security advice in practice. ...

Measuring Security Practices
From Communications of the ACM

Measuring Security Practices

This paper seeks to make progress on the prevalence of popular security practices and their relationship to security outcomes via the longitudinal empirical measurement...

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.

Technical Perspective: hXDP
From Communications of the ACM

Technical Perspective: hXDP: Light and Efficient Packet Processing Offload

In "hXDP: Efficient Software Packet Processing on FPGA NICs," the authors offer an interesting solution to bridging the performance gap between the CPU and the...

hXDP
From Communications of the ACM

hXDP: Efficient Software Packet Processing on FPGA NICs

We present hXDP, a solution to run on FPGAs software packet processing tasks described with the eBPF technology and targeting the Linux's eXpress Data Path.

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.

Technical Perspective: Can Data Structures Treat Us Fairly?
From Communications of the ACM

Technical Perspective: Can Data Structures Treat Us Fairly?

In "Sampling Near Neighbors in Search for Fairness," Aumüller et al. investigate a basic problem in similarity search called near neighbor in the context of fair...
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