Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Minden, Victor"'
Inverse design coupled with adjoint optimization is a powerful method to design on-chip nanophotonic devices with multi-wavelength and multi-mode optical functionalities. Although only two simulations are required in each iteration of this optimizati
Externí odkaz:
http://arxiv.org/abs/2307.05388
Autor:
Gullapally, Sai Chowdary, Zhang, Yibo, Mittal, Nitin Kumar, Kartik, Deeksha, Srinivasan, Sandhya, Rose, Kevin, Shenker, Daniel, Juyal, Dinkar, Padigela, Harshith, Biju, Raymond, Minden, Victor, Maheshwari, Chirag, Thibault, Marc, Goldstein, Zvi, Novak, Luke, Chandra, Nidhi, Lee, Justin, Prakash, Aaditya, Shah, Chintan, Abel, John, Fahy, Darren, Taylor-Weiner, Amaro, Sampat, Anand
Machine learning algorithms have the potential to improve patient outcomes in digital pathology. However, generalization of these tools is currently limited by sensitivity to variations in tissue preparation, staining procedures and scanning equipmen
Externí odkaz:
http://arxiv.org/abs/2305.02401
Artificial neural networks that learn to perform Principal Component Analysis (PCA) and related tasks using strictly local learning rules have been previously derived based on the principle of similarity matching: similar pairs of inputs should map t
Externí odkaz:
http://arxiv.org/abs/1810.06966
Big data problems frequently require processing datasets in a streaming fashion, either because all data are available at once but collectively are larger than available memory or because the data intrinsically arrive one data point at a time and mus
Externí odkaz:
http://arxiv.org/abs/1808.02083
Autor:
Minden, Victor, Ying, Lexing
We present a simple discretization scheme for the hypersingular integral representation of the fractional Laplace operator and solver for the corresponding fractional Laplacian problem. Through singularity subtraction, we obtain a regularized integra
Externí odkaz:
http://arxiv.org/abs/1802.03770
Canonical correlation analysis was proposed by Hotelling [6] and it measures linear relationship between two multidimensional variables. In high dimensional setting, the classical canonical correlation analysis breaks down. We propose a sparse canoni
Externí odkaz:
http://arxiv.org/abs/1705.10865
We introduce the strong recursive skeletonization factorization (RS-S), a new approximate matrix factorization based on recursive skeletonization for solving discretizations of linear integral equations associated with elliptic partial differential e
Externí odkaz:
http://arxiv.org/abs/1609.08130
We present a new algorithm for spectral clustering based on a column-pivoted QR factorization that may be directly used for cluster assignment or to provide an initial guess for k-means. Our algorithm is simple to implement, direct, and requires no i
Externí odkaz:
http://arxiv.org/abs/1609.08251
Maximum likelihood estimation for parameter-fitting given observations from a Gaussian process in space is a computationally-demanding task that restricts the use of such methods to moderately-sized datasets. We present a framework for unstructured o
Externí odkaz:
http://arxiv.org/abs/1603.08057
We present a method for updating certain hierarchical factorizations for solving linear integral equations with elliptic kernels. In particular, given a factorization corresponding to some initial geometry or material parameters, we can locally pertu
Externí odkaz:
http://arxiv.org/abs/1411.5706