Results 21 to 30 of about 1,102 (116)
HoloDetect: Few-Shot Learning for Error Detection
, 2019 We introduce a few-shot learning framework for error detection. We show that data augmentation (a form of weak supervision) is key to training high-quality, ML-based error detection models that require minimal human involvement. Our framework consists of
Bengio Yoshua +9 more
core +1 more source
An efficient confidentiality-preserving Proof of Ownership for deduplication [PDF]
, 2015 Data storage in the cloud is becoming widespread. Deduplication is a key mechanism to decrease the operating costs cloud providers face, due to the reduction of replicated data storage.
González Manzano, Lorena +1 more
core +1 more source
Facial expression recognition for emotion perception: A comprehensive science mapping
Ibrain, Volume 12, Issue 1, Page 38-51, Spring 2026.Facial expression recognition (FER) has emerged as a pivotal interdisciplinary research domain, bridging computer science, psychology, neuroscience, and medicine. By mapping the FER scientific knowledge graph, the study aimed to explore the technological evolution and forecast future application trends in this field.
Hou‐Ming Kan +10 more
wiley +1 more source
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
, 2017 The success of deep learning in vision can be attributed to: (a) models with high capacity; (b) increased computational power; and (c) availability of large-scale labeled data.
Gupta, Abhinav +3 more
core +1 more source
Transparency overlays and applications [PDF]
, 2016 In this paper, we initiate a formal study of transparency, which in recent years has become an increasingly critical requirement for the systems in which people place trust.
Chase, M, Meiklejohn, S
core +3 more sources
Interpretable Machine Learning: A Comprehensive Review of Foundations, Methods, and the Path Forward
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.This systematic review of 352 studies establishes a comprehensive taxonomy for Interpretable Machine Learning, transitioning from foundational intrinsic models to advanced deep learning explanations. It reveals a critical paradigm shift toward “mechanistic interpretability” and actionable recourse, emphasizing that future AI systems must be rigorously ...
Shimon Fridkin, Michael Bendersky
wiley +1 more source
RETSim: Resilient and Efficient Text Similarity
, 2023 This paper introduces RETSim (Resilient and Efficient Text Similarity), a lightweight, multilingual deep learning model trained to produce robust metric embeddings for near-duplicate text retrieval, clustering, and dataset deduplication tasks.
Bumin, Aysegul +4 more
core
Expert Systems, Volume 43, Issue 3, March 2026.ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam +3 more
wiley +1 more source
Privacy Side Channels in Machine Learning Systems
, 2023 Most current approaches for protecting privacy in machine learning (ML) assume that models exist in a vacuum, when in reality, ML models are part of larger systems that include components for training data filtering, output monitoring, and more.
Carlini, Nicholas +7 more
core
Generative AI for Requirements Engineering: A Systematic Literature Review
Software: Practice and Experience, Volume 56, Issue 2, Page 141-170, February 2026.ABSTRACT Introduction Requirements engineering (RE) faces challenges due to the handling of increasingly complex software systems. These challenges can be addressed using generative artificial intelligence (GenAI). Given that GenAI‐based RE has not been systematically analyzed in detail, this review examines the related research, focusing on trends ...
Haowei Cheng +6 more
wiley +1 more source