Results 121 to 130 of about 1,029,862 (299)

Adaptive fuzzy prototype learning with view-balanced multi-view embeddings for multi-behavior recommendation

Journal of King Saud University: Computer and Information Sciences
Multi-behavior recommender systems(RS) leverages diverse user actions(e.g. click, cart, purchase) to model preferences more comprehensively, yet it often suffers from noisy behavior signals and heterogeneous user–item representations.
Juan Liao, Zhe Liu, Aman Jantan, Narinderjit Singh Sawaran Singh, Wulfran Fendzi Mbasso, Himanshu Dhumras, Mehdi Hosseinzadeh   +6 more
doaj   +1 more source

A unifying framework for vector-valued manifold regularization and multi-view learning [PDF]

, 2013
This paper presents a general vector-valued reproducing kernel Hilbert spaces (RKHS) formulation for the problem of learning an unknown functional dependency between a structured input space and a structured output space, in the Semi-Supervised Learning ...
Minh, H. Q., BAZZANI, Loris, MURINO, Vittorio   +2 more
core  

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Multi-domain feature joint optimization based on multi-view learning for improving the EEG decoding. [PDF]

Front Hum Neurosci, 2023
Shi B, Yue Z, Yin S, Zhao J, Wang J.
europepmc   +1 more source

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

Advanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa, Milan Buttberg, Ke Ran, Rana Walied Ahmad, Dennis Braun, Lukas Völkel, Jimin Lee, Sofía Cruces, Bart Macco, Bárbara Canto, Holger Lerch, Thorsten Wahlbrink, Holger Kalisch, Michael Heuken, Andrei Vescan, Joachim Mayer, Zhenxing Wang, Ilia Valov, Stephan Menzel, Max C. Lemme   +19 more
wiley   +1 more source

Multi-view representation learning and understanding [PDF]

Multimedia Tools and Applications, 2021
openaire   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Structure-guided decoupled contrastive framework for partial multi-view incomplete multi-label classification

Journal of King Saud University: Computer and Information Sciences
Recently, multi-view multi-label learning has gained significant attention due to its applicability in various domains. However, due to the limitations of data collection and the subjectivity of manual labeling, multi-view multi-label learning often ...
Linqian Yang, Tao Zhuang, Xing Jin, Tianyang Cao, Xiyin Wu   +4 more
doaj   +1 more source

Multi-View Learning to Unravel the Different Levels Underlying Hepatitis B Vaccine Response. [PDF]

Vaccines (Basel), 2023
Affaticati F, Bartholomeus E, Mullan K, Damme PV, Beutels P, Ogunjimi B, Laukens K, Meysman P.   +7 more
europepmc   +1 more source

On surrogate supervision multi-view learning [PDF]

Data can be represented in multiple views. Traditional multi-view learning methods (i.e., co-training, multi-task learning) focus on improving learning performance using information from the auxiliary view, although information from the target view is ...
Jin, Gaole
core   +1 more source