Results 41 to 50 of about 6,086,701 (288)

Optimal transformation: A new approach for covering the central subspace

Journal of Multivariate Analysis, 2013
This paper studies a general family of methods for sufficient dimension reduction (SDR) called the test function (TF), based on the introduction of a nonlinear transformation of the response. By considering order 1 and 2 conditional moments of the predictors given the response, we distinguish two classes of methods.
Portier, François, Delyon, Bernard
openaire   +4 more sources

Independent Subspace Analysis of the Sea Surface Temperature Variability: Non-Gaussian Sources and Sensitivity to Sampling and Dimensionality

Complexity, 2017
We propose an expansion of multivariate time-series data into maximally independent source subspaces. The search is made among rotations of prewhitened data which maximize non-Gaussianity of candidate sources.
Carlos A. L. Pires, Abdel Hannachi
doaj   +1 more source

Spatial‐spectral feature extraction of hyperspectral images using tensor‐based collaborative graph analysis

Electronics Letters, 2021
Although the collaborative graph‐based discriminant analysis (CGDA) method has shown promising performance for the feature extraction of the hyperspectral image (HSI), both the intrinsic local subspace structures and spatial structural information are ...
Lei Pan
doaj   +1 more source

Photoinduced Charge Separation in Single‐Component Squaraine Films: The Key Role of Electrostatic Disorder

Advanced Functional Materials, EarlyView.
ABSTRACT Neat films of organic dyes are an interesting technological platform for solar cells and photodetectors. Recently, the conventional biphasic bulk‐heterojunction paradigm for photoinduced charge separation was challenged by the observation that charge carriers can be photogenerated in single‐component materials. A comprehensive experimental and
Davide Giavazzi, João Pedro Ferreira Assunção, Michael Bauer, Matthias Diethelm, Wei‐Hsu Hu, Mohammad Jafarpour, Roland Widmer, Antonia Neels, Dimitrios Sapalidis, Bruno F. B. Silva, Roland Hany, Frank Nüesch, Anna Painelli   +12 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Short and Length‐Independent Group Delay Supported by Topological Edge States in Finite‐Size Su–Schrieffer–Heeger Chains

Advanced Materials Technologies, EarlyView.
This study demonstrates short, length‐independent group delay supported by topological edge states in open Su–Schrieffer–Heeger networks. Strong boundary port coupling enables an order‐of‐magnitude latency reduction compared to bulk modes, alongside robust protection against bulk disorder.
Yu‐Han Chang, Nadia Daniela Rivera Torres, Santiago Figueroa Manrique, Raul A. Robles Robles, Vanna Chrismas Silalahi, Cen‐Shawn Wu, Gang Wang, Giulia Marcucci, Laura Pilozzi, Claudio Conti, Ray‐Kuang Lee, Watson Kuo   +11 more
wiley   +1 more source

Subspace Tracking Based Blind MIMO Transmit Preprocessing

, 2007
In this contribution projection approximation subspace tracking using deflation (PASTD) is investigated in the context of MIMO transmit preprocessing systems by exploiting the specific property of Time Division Duplexing (TDD) techniques that the uplink ...
Liu, W., Yang, L.L., Hanzo, L.
core   +2 more sources

Unsupervised graph-based feature selection via subspace and pagerank centrality [PDF]

Expert Systems with Applications, 2018
Abstract Feature selection has become an indispensable part of intelligent systems, especially with the proliferation of high dimensional data. It identifies the subset of discriminative features leading to better learning performances, i.e., higher learning accuracy, lower computational cost and significant model interpretability.
Khadidja Henni, Neila Mezghani, Charles Gouin-Vallerand   +2 more
openaire   +2 more sources

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

Hamiltonian simulation in the low-energy subspace

npj Quantum Information, 2021
We study the problem of simulating the dynamics of spin systems when the initial state is supported on a subspace of low energy of a Hamiltonian H. This is a central problem in physics with vast applications in many-body systems and beyond, where the ...
Burak Şahinoğlu, Rolando D. Somma
doaj   +1 more source