Results 41 to 50 of about 8,432 (220)
, 2009 Similarity search in high dimensional space is a nontrivial problem due to the so-called curse of dimensionality. Recent techniques such as Piecewise Aggregate Approximation (PAA), Segmented Means (SMEAN) and Mean-Standard deviation (MS) prove to be very
Cheng, Hao, Hua, Kien A., Vu, Khanh
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Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Principal Components, Sufficient Dimension Reduction, and Envelopes
, 2018 We review probabilistic principal components, principal fitted components, sufficient dimension reduction, and envelopes, arguing that at their core they are all based on variations of the conditional independence argument that Fisher used to develop ...
R. Dennis Cook
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Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Categorical, low-dimensional decomposition of human odor space with non-negative matrix factorization [PDF]
, 2014 Recent studies using Principal Components Analysis (PCA) support low-dimensional models of odor space, in which one or two dimensions - with hedonic valence featuring prominently - explain most odor variability.
Quinn, SP +7 more
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Advanced Intelligent Systems, EarlyView.HTFC gets 3D refractive index tomograms of flowing cells. Label‐free monocytes are engineered to express patterns of cytoplasmic vacuoles. From the tomogram, an efficient dimensionality reduction is operated. Interpretable features are extracted to classify the expression severity of phenotypes coexisting in each cell, visually represented by a seven ...
Marika Valentino +9 more
wiley +1 more source
Kernel Learning in Ridge Regression "Automatically" Yields Exact Low Rank Solution
, 2023 We consider kernels of the form $(x,x') \mapsto \phi(\|x-x'\|^2_\Sigma)$ parametrized by $\Sigma$. For such kernels, we study a variant of the kernel ridge regression problem which simultaneously optimizes the prediction function and the parameter ...
Liu, Keli +3 more
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Robust Representation Learning for Clean Feature Discovery in Incomplete Multi‐View Clustering
Advanced Intelligent Systems, EarlyView.Robust feature discovery in incomplete multi‐view clustering is achieved by coupling RPCA‐based clean representation recovery with neural‐network‐assisted graph learning. The resulting RIMVC framework constructs cleaner and more discriminative graph‐structured representations from incomplete and noisy multi‐view data, improving clustering robustness ...
Ping Hu +4 more
wiley +1 more source
Advanced Physics Research, EarlyView.ABSTRACT We introduce a family of bosonic quantum error‐correcting codes built as a rotation‐symmetric superposition of squeezed vacuum states, which promise protection against both loss and dephasing noise channels. The robustness of these “squeezed‐vacuum codes” arises from being arranged at evenly spaced angles in phase‐space, and simultaneously in ...
Nir Gutman +4 more
wiley +1 more source
Critical fluctuations of sums of weakly dependent random vectors
, 1994 LetS n be sums of iid random vectors taking values in a Banach space andF be a smooth function. We study the fluctuations ofS n under the transformed measureP n given byd P n/d P=exp (nF(S n/n))/Z n.
Wang, K
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