Results 171 to 180 of about 1,338,246 (278)

Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices

Advanced Science, EarlyView.
Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen, Wei Zeng, Zherui Zhao, JiYu Zhao, Ziyan Huang, Zhuo Chen, Kui Zhou, Guanglong Ding, Su‐Ting Han, Ye Zhou   +9 more
wiley   +1 more source

A Geometric Interpretation of Stochastic Gradient Descent Using Diffusion Metrics. [PDF]

Entropy (Basel), 2020
Fioresi R, Chaudhari P, Soatto S.
europepmc   +1 more source

Convergence of Hyperbolic Neural Networks Under Riemannian Stochastic Gradient Descent

We prove, under mild conditions, the convergence of a Riemannian gradient descent method for a hyperbolic neural network regression model, both in batch gradient descent and stochastic gradient descent.
Wang, Bao, Whiting, Wes, Xin, Jack
core   +1 more source

Flexoelectricity in Photoconversion: Fundamentals, Materials, and Outlooks

Advanced Science, EarlyView.
Mechanical bending of a flexible cantilever induces a strain gradient in the photoactive material. The resulting flexoelectric field couples with photovoltaic and photoconductive effects, modulating charge generation, separation, and collection. A comparative analysis of oxide perovskites, halide perovskites, and two‐dimensional materials is presented,
Xiang Huang, Feng Li, Rongkun Zheng
wiley   +1 more source

Nonparametric budgeted stochastic gradient descent

, 2016
One of the most challenging problems in kernel online learning is to bound the model size. Budgeted kernel online learning addresses this issue by bounding the model size to a predefined budget.
V Nguyen (9860309), TD Nguyen (9887741), T Le (13415748), D Phung (13323141)   +3 more
core  

Single‐Cell RNA Editing Identifies T Cell ADAR1 as a Key Regulator of Immune Exhaustion and Anti‐PD‐1 Resistance in Colorectal Cancer

Advanced Science, EarlyView.
Single‐cell RNA editing analysis identifies ADAR1 as a regulator of dysfunctional T cell states in colorectal cancer. Elevated ADAR1 activity promotes T cell exhaustion and impairs antitumor immunity partly through TGF‐β‐SMAD signaling, contributing to anti‐PD‐1 resistance and highlighting T cell ADAR1 as a potential therapeutic target and biomarker ...
Da Kang, Song‐Zuo Xie, Yong‐Zhou Luo, Xin‐Pei Deng, Xi‐Rong Tan, Ze‐Geng Chen, Ling‐Xing Zeng, Gong Chen, Pei‐Rong Ding, Zhi‐Zhong Pan, Rong‐Xin Zhang   +10 more
wiley   +1 more source

Tighter privacy auditing of differentially private stochastic gradient descent in the hidden state threat model. [PDF]

Sci Rep
Bhuekar A.
europepmc   +1 more source

SSGD: SPARSITY-PROMOTING STOCHASTIC GRADIENT DESCENT ALGORITHM FOR UNBIASED DNN PRUNING. [PDF]

Proc IEEE Int Conf Acoust Speech Signal Process, 2020
Lee CH, Fedorov I, Rao BD, Garudadri H.
europepmc   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Mutual Information Based Learning Rate Decay for Stochastic Gradient Descent Training of Deep Neural Networks. [PDF]

Entropy (Basel), 2020
Vasudevan S.
europepmc   +1 more source