2.1k citations · 4.3k across the 48 of their papers we have counts for
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Local Two-Sample Testing over Graphs and Point-Clouds by Random-Walk Distributions
Boris Landa, Rihao Qu, Joseph Chang +1
Rejecting the null hypothesis in two-sample testing is a fundamental tool for scientific discovery. Yet, aside from concluding that two samples do not come from the same probabilit…
-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…
Differentiable Unsupervised Feature Selection based on a Gated Laplacian
Ofir Lindenbaum, Uri Shaham, Jonathan Svirsky +2
Scientific observations may consist of a large number of variables (features). Identifying a subset of meaningful features is often ignored in unsupervised learning, despite its po…
Doubly-Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise
Boris Landa, Ronald R. Coifman, Yuval Kluger
A fundamental step in many data-analysis techniques is the construction of an affinity matrix describing similarities between data points. When the data points reside in Euclidean…
Spectral neighbor joining for reconstruction of latent tree models
Ariel Jaffe, Noah Amsel, Yariv Aizenbud +3
A common assumption in multiple scientific applications is that the distribution of observed data can be modeled by a latent tree graphical model. An important example is phylogene…
The Spectral Underpinning of word2vec
Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum +3
word2vec due to Mikolov \textit{et al.} (2013) is a word embedding method that is widely used in natural language processing. Despite its great success and frequent use, theoretica…