Results 111 to 120 of about 1,338,246 (278)

Convergence of Stochastic Gradient Descent for PCA

CoRR, 2015
We consider the problem of principal component analysis (PCA) in a streaming stochastic setting, where our goal is to find a direction of approximate maximal variance, based on a stream of i.i.d. data points in $\reals^d$. A simple and computationally cheap algorithm for this is stochastic gradient descent (SGD), which incrementally updates its ...
openaire   +3 more sources

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

Stochastic gradient descent with finite samples sizes

, 2016
The minimization of empirical risks over finite sample sizes is an important problem in large-scale machine learning. A variety of algorithms has been proposed in the literature to alleviate the computational burden per iteration at the expense of ...
Ali H. Sayed, Bicheng Ying, Ying, Bicheng, Kun Yuan, Yuan, Kun, Sayed, Ali H, Stefan Vlaski, Vlaski, Stefan   +7 more
core   +2 more sources

Path‐Decoupled Cation‐Eutaxy III–V van der Waals Memristive Semiconductors for Mitigating the Neuromorphic Accuracy‐Energy Trade‐off

Advanced Materials, EarlyView.
Path‐decoupled III–V van der Waals memtransistors spatially separate ionic and electronic transport to overcome the conventional trade‐off between accuracy and energy in neuromorphic hardware. Mobile K+ ions in the vdW gaps set a wide conductance window, Gmax/Gmin, while gate‐tunable hole conduction lowers programming energy, enabling reliable ...
Jihong Bae, Ji Hoon Han, Taeyoung Kim, Jongbum Won, Seokmin Park, Gyu Won Kim, Sungsoon Kim, Hong Choi, Taehoon Kim, Hong‐Sub Lee, Jae‐Hyun Lee, Young Jin Choi, Jinwoo Cheon, Wooyoung Shim   +13 more
wiley   +1 more source

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source

Mixing of Stochastic Accelerated Gradient Descent

CoRR, 2019
We study the mixing properties for stochastic accelerated gradient descent (SAGD) on least-squares regression. First, we show that stochastic gradient descent (SGD) and SAGD are simulating the same invariant distribution. Motivated by this, we then establish mixing rate for SAGD-iterates and compare it with those of SGD-iterates.
Peiyuan Zhang, Hadi Daneshmand, Thomas Hofmann 0001   +2 more
openaire   +3 more sources

Flax Composites With Improved Interfacial Strength Through Microbially Induced Mineral Precipitation

Advanced Materials, EarlyView.
A bio‐inspired biomineralization strategy introduces an additional hierarchy to flax fiber composites. By controlling microbe‐mediated mineral particle deposition through tuned salt concentrations, stress transfer within the natural fiber composite is enhanced.
Deniz Sayinbas, Ingo Nettersheim, Jeong‐Joo Oh, Marie‐Eve Aubin‐Tam, Julie Teuwen, Kunal Masania   +5 more
wiley   +1 more source

A note on diffusion limits for stochastic gradient descent

, 2022
In the machine learning literature stochastic gradient descent has recently been widely discussed for its purported implicit regularization properties. Much of the theory, that attempts to clarify the role of noise in stochastic gradient algorithms, has ...
Lanconelli, Alberto, Lauria, Christopher S. A.   +1 more
core  

Atomic‐Scale Detection of Néel Vector Switching in the Single‐Layer A‐Type Antiferromagnet Cr2S3‐2D

Advanced Materials, EarlyView.
Interfacial electron donation from graphene redistributes charge within single‐layer Cr2S3‐2D, preferentially accumulating at the lower Cr/S plane. The resulting minute magnetic imbalance lifts the equivalence of the two magnetic sublayers, enabling atomic‐resolution identification and field‐induced control of Néel‐vector states in a two‐dimensional A ...
Affan Safeer, Calisa Dias, Mahdi Ghorbani‐Asl, Abdallah Karaka, Pradyumna Bawankule, Weibin Li, Pierluigi Gargiani, Wouter Jolie, Arkady V. Krasheninnikov, Amilcar Bedoya‐Pinto, Thomas Michely, Jeison Fischer   +11 more
wiley   +1 more source

Asynchronous parallel stochastic gradient descent

, 2022
The implementation of a vast majority of machine learning (ML) algorithms boils down to solving a numerical optimization problem. In this context, Stochastic Gradient Descent (SGD) methods have long proven to provide good results, both in terms of ...
Pfreundt, Franz-Josef, Keuper, Janis
core   +1 more source