Results 31 to 40 of about 7,450 (264)
Online group-structured dictionary learning [PDF]
CVPR 2011, 2011 We develop a dictionary learning method which is (i) online, (ii) enables overlapping group structures with (iii) non-convex sparsity-inducing regularization and (iv) handles the partially observable case. Structured sparsity and the related group norms have recently gained widespread attention in group-sparsity regularized problems in the case when ...
Zoltán Szabó 0001 +2 more
openaire +1 more source
Vanade sõnastike veebiandmebaas ja mida sealt leida
Eesti ja Soome-ugri Keeleteaduse Ajakiri, 2013 Eesti keele kolm vanimat trükitud sõnastikku pärinevad 17. sajandist ja nende aines oli 21. sajandi alguseni uurijatele kättesaadav üksnes faksiimileväljaannetena. Tartu Ülikooli vana kirjakeele töörühmas on viidud need sõnastikud elektroonilisele kujule,
Külli Prillop, Kristel Ress
doaj +1 more source
Online multidimensional dictionary learning
CoRRDictionary learning is a widely used technique in signal processing and machine learning that aims to represent data as a linear combination of a few elements from an overcomplete dictionary. In this work, we propose a generalization of the dictionary learning technique using the t-product framework, enabling efficient handling of multidimensional ...
Ferdaous Ait Addi +2 more
openaire +2 more sources
On the Size of the Online Kernel Sparsification Dictionary [PDF]
CoRR, 2012 ICML2012
Yi Sun 0003 +2 more
openaire +2 more sources
Super-resolution reconstruction method of mine image based on online multi-dictionary learning
Gong-kuang zidonghua, 2020 Aiming at problem that dictionary learning method was poorly effective in reconstruction of mine image with noise and complex environment, a super-resolution reconstruction method of mine image based on online multi-dictionary learning was proposed.
WANG Haitao, YU Wenjie, ZHANG Guanglei
doaj +1 more source
Online dictionary learning for sparse coding [PDF]
Proceedings of the 26th Annual International Conference on Machine Learning, 2009 Sparse coding---that is, modelling data vectors as sparse linear combinations of basis elements---is widely used in machine learning, neuroscience, signal processing, and statistics. This paper focuses on learning the basis set, also called dictionary, to adapt it to specific data, an approach that has recently proven to be very effective for signal ...
Mairal, Julien +3 more
openaire +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Exploring cultural conceptualisations in two online Singlish dictionaries
Altre Modernità, 2022 The global spread of English has resulted in new varieties and cultures being associated with it; Cultural Linguistics studies these by emphasising the relationship between language and culturally-constructed conceptualisations. English is often seen as
Martina Guzzetti
doaj +1 more source
Advanced Robotics Research, EarlyView.This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Two‐photon polymerization enables high‐resolution microfabrication, but performing alignment when printing multiple structures is difficult. Here, we present a fast, robust, and open‐source protocol for automated alignment on Nanoscribe systems. Achieving ≈0.4 μm accuracy in under 5 s, our protocol reduces time and error in multimaterial printing. This
Daniel Maher +4 more
wiley +1 more source