Results 111 to 120 of about 4,693,052 (300)
Flexible Leaf‐Like Fuel Cell From Plasmonic Janus Nanosheet
Advanced Functional Materials, EarlyView.A flexible leaf‐like fuel cell is fabricated by conductive gold nanowire sponge‐supported plasmonic Janus nanosheet, which can generate a power of 8.93 mW cm⁻2 with less than 10% performance deterioration even being bent or twisted. Further assembly in a tree‐like layout demonstrates omnidirectional light harvesting capability and wind resistance ...
Yifeng Huang +3 more
wiley +1 more source
Carbon Nanotube 3D Integrated Circuits: From Design to Applications
Advanced Functional Materials, EarlyView.As Moore's law approaches its physical limits, carbon nanotube (CNT) 3D integrated circuits (ICs) emerge as a promising alternative due to the miniaturization, high mobility, and low power consumption. CNT 3D ICs in optoelectronics, memory, and monolithic ICs are reviewed while addressing challenges in fabrication, design, and integration.
Han‐Yang Liu +3 more
wiley +1 more source
Boosting-Based Sequential Meta-Tree Ensemble Construction for Improved Decision Trees [PDF]
arXivA decision tree is one of the most popular approaches in machine learning fields. However, it suffers from the problem of overfitting caused by overly deepened trees. Then, a meta-tree is recently proposed. It solves the problem of overfitting caused by overly deepened trees.
arxiv
Active Learning‐Driven Discovery of Sub‐2 Nm High‐Entropy Nanocatalysts for Alkaline Water Splitting
Advanced Functional Materials, EarlyView.High‐entropy nanoparticles (HENPs) hold great promise for electrocatalysis, yet optimizing their compositions remains challenging. This study employs active learning and Bayesian Optimization to accelerate the discovery of octonary HENPs for hydrogen and oxygen evolution reactions.
Sakthivel Perumal +5 more
wiley +1 more source
An Algorithmic Framework for Constructing Multiple Decision Trees by Evaluating Their Combination Performance Throughout the Construction Process [PDF]
arXivPredictions using a combination of decision trees are known to be effective in machine learning. Typical ideas for constructing a combination of decision trees for prediction are bagging and boosting. Bagging independently constructs decision trees without evaluating their combination performance and averages them afterward.
arxiv
High‐Entropy Magnetism of Murunskite
Advanced Functional Materials, EarlyView.The study of murunskite (K2FeCu3S4) reveals that its magnetic and orbital order emerges in a simple I4/mmm crystal structure with complete disorder in the transition metal positions. Mixed‐valence Fe ions randomly occupy 1/4 of the tetrahedral sites, with the remaining 3/4 being filled by non‐magnetic Cu+ ions.
Davor Tolj +18 more
wiley +1 more source
Hardware Acceleration of Sparse Oblique Decision Trees for Edge Computing
Elektronika ir Elektrotechnika, 2019 This paper presents a hardware accelerator for sparse decision trees intended for FPGA applications. To the best of authors’ knowledge, this is the first accelerator of this type. Beside the hardware accelerator itself, a novel algorithm for induction of
Predrag Teodorovic +1 more
doaj +1 more source
Provably optimal decision trees with arbitrary splitting rules in polynomial time [PDF]
arXivIn this paper, we introduce a generic data structure called decision trees, which integrates several well-known data structures, including binary search trees, K-D trees, binary space partition trees, and decision tree models from machine learning. We provide the first axiomatic definition of decision trees.
arxiv
An inequality for the Fourier spectrum of parity decision trees [PDF]
arXiv, 2015 We give a new bound on the sum of the linear Fourier coefficients of a Boolean function in terms of its parity decision tree complexity. This result generalizes an inequality of O'Donnell and Servedio for regular decision trees. We use this bound to obtain the first non-trivial lower bound on the parity decision tree complexity of the recursive ...
arxiv