3 citations · 15 across the 12 of their papers we have counts for
14 papers
SEL-CIE: Knowledge-Guided Self-Supervised Learning Framework for CIE-XYZ Reconstruction from Non-Linear sRGB Images
Shir Barzel, Moshe Salhov, Ofir Lindenbaum +1
Modern cameras typically offer two types of image states: a minimally processed linear raw RGB image representing the raw sensor data, and a highly-processed non-linear image state…
TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models
Guy Zamberg, Moshe Salhov, Ofir Lindenbaum +1
Tables are an abundant form of data with use cases across all scientific fields. Real-world datasets often contain anomalous samples that can negatively affect downstream analysis.…
Cross-boosting of WNNM Image Denoising method by Directional Wavelet Packets
Amir Averbuch, Pekka Neittaanmäki, Valery Zheludev +2
The paper presents an image denoising scheme by combining a method that is based on directional quasi-analytic wavelet packets (qWPs) with the state-of-the-art Weighted Nuclear Nor…
Imbalanced Classification via a Tabular Translation GAN
Jonathan Gradstein, Moshe Salhov, Yoav Tulpan +2
When presented with a binary classification problem where the data exhibits severe class imbalance, most standard predictive methods may fail to accurately model the minority class…
Search and Score-based Waterfall Auction Optimization
Dan Halbersberg, Matan Halevi, Moshe Salhov
Online advertising is a major source of income for many online companies. One common approach is to sell online advertisements via waterfall auctions, through which a publisher mak…
-based Sparse Canonical Correlation Analysis
Ofir Lindenbaum, Moshe Salhov, Amir Averbuch +1
Canonical Correlation Analysis (CCA) models are powerful for studying the associations between two sets of variables. The canonically correlated representations, termed \textit{can…
Coupling BM3D with directional wavelet packets for image denoising
Amir Averbuch, Pekka Neittaanmaki, Valery Zheludev +2
The paper presents an image denoising algorithm by combining a method that is based on directional quasi-analytic wavelet packets (qWPs) with the popular BM3D algorithm. The qWPs a…
Majority Voting and the Condorcet's Jury Theorem
Hanan Shteingart, Eran Marom, Igor Itkin +4
There is a striking relationship between a three hundred years old Political Science theorem named "Condorcet's jury theorem" (1785), which states that majorities are more likely t…
Image inpainting using directional wavelet packets originating from polynomial splines
Amir Averbuch, Pekka Neittaanmaki, Valery Zheludev +2
The paper presents a new algorithm for the image inpainting problem. The algorithm is using a recently designed versatile library of quasi-analytic complex-valued wavelet packets (…
Kernel Scaling for Manifold Learning and Classification
Ofir Lindenbaum, Moshe Salhov, Arie Yeredor +1
Kernel methods play a critical role in many machine learning algorithms. They are useful in manifold learning, classification, clustering and other data analysis tasks. Setting the…
Incomplete Pivoted QR-based Dimensionality Reduction
Amit Bermanis, Aviv Rotbart, Moshe Salhov +1
High-dimensional big data appears in many research fields such as image recognition, biology and collaborative filtering. Often, the exploration of such data by classic algorithms…
Multi-View Kernel Consensus For Data Analysis
Moshe Salhov, Ofir Lindenbaum, Yariv Aizenbud +3
The input data features set for many data driven tasks is high-dimensional while the intrinsic dimension of the data is low. Data analysis methods aim to uncover the underlying low…
Diffusion Representations
Moshe Salhov, Amit Bermanis, Guy Wolf +1
Diffusion Maps framework is a kernel based method for manifold learning and data analysis that defines diffusion similarities by imposing a Markovian process on the given dataset.…
MultiView Diffusion Maps
Ofir Lindenbaum, Arie Yeredor, Moshe Salhov +1
In this paper, we address the challenging task of achieving multi-view dimensionality reduction. The goal is to effectively use the availability of multiple views for extracting a…