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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: 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.

Technical Perspective: 'What Is the Ideal Operating System?'
From Communications of the ACM

Technical Perspective: 'What Is the Ideal Operating System?'

The authors of "Set the Configuration for the Heart of the OS" put a fresh view on the practicability of automatic kernel debloating.

Set the Configuration for the Heart of the OS
From Communications of the ACM

Set the Configuration for the Heart of the OS: On the Practicality of Operating System Kernel Debloating

This paper presents a study on the practicality of operating system kernel debloating, that is, reducing kernel code that is not needed by the target applications...

Technical Perspective: How Do Experts Learn New Programming Languages?
From Communications of the ACM

Technical Perspective: How Do Experts Learn New Programming Languages?

"Here We Go Again: Why Is It Difficult for Developers to Learn Another Programming Language?" by Shrestha et al. provides insight into the difficulty of learning...

Here We Go Again
From Communications of the ACM

Here We Go Again: Why Is It Difficult for Developers to Learn Another Programming Language?

Our findings demonstrate that interference is a widespread phenomenon, forcing programmers to adopt suboptimal, opportunistic learning strategies.

Technical Perspective: Applying Design-Space Exploration to Quantum Architectures
From Communications of the ACM

Technical Perspective: Applying Design-Space Exploration to Quantum Architectures

"Toward Systematic Architectural Design of Near-Term Trapped Ion Quantum Computers" presents a study on scaling trapped-ion quantum architectures, and challenges...

Toward Systematic Architectural Design of Near-Term Trapped Ion Quantum Computers
From Communications of the ACM

Toward Systematic Architectural Design of Near-Term Trapped Ion Quantum Computers

Toward realizing QCCD-based trapped ion systems with 50-100 qubits, we perform an extensive application-driven architectural study evaluating the key design choices...

Technical Perspective: Personalized Recommendation of PoIs to People with Autism
From Communications of the ACM

Technical Perspective: Personalized Recommendation of PoIs to People with Autism

"Supporting People with Autism Spectrum Disorders in the Exploration of PoIs" is an example of work that takes seriously the task of supporting a small group that...

Supporting People with Autism Spectrum Disorders in the Exploration of PoIs
From Communications of the ACM

Supporting People with Autism Spectrum Disorders in the Exploration of PoIs: An Inclusive Recommender System

We propose a novel Top-N recommendation model that combines information about an autistic user's idiosyncratic aversions with her/his preferences in a personalized...

Technical Perspective: On Proofs, Entanglement, and Games
From Communications of the ACM

Technical Perspective: On Proofs, Entanglement, and Games

"MIP* = RE," by Zhengfeng Ji et al., studies quantum interactive proofs.

MIP* = RE
From Communications of the ACM

MIP* = RE

In this work, we study a fourth modification to the notion of efficient verification that originates in the study of quantum entanglement.

Technical Perspective: Does Your Experiment Smell?
From Communications of the ACM

Technical Perspective: Does Your Experiment Smell?

"PlanAlyzer," by Emma Tosch et al., details PlanAlyzer software, the first tool to statically check the validity of online experiments.

PlanAlyzer
From Communications of the ACM

PlanAlyzer: Assessing Threats to the Validity of Online Experiments

We present the first approach for checking the internal validity of online experiments statically, that is, from code alone.
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