Ofir Lindenbaum

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 60

Top Topics

Unsupervised Learning

Dimensionality Reduction

Feature Selection

Top Venues

Signal Process.

Publications

Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum
Self Supervised Correlation-based Permutations for Multi-View Clustering. CoRR (2024)
Shir Barzel, Moshe Salhov, Ofir Lindenbaum, Amir Averbuch
SEL-CIE: Knowledge-Guided Self-Supervised Learning Framework for CIE-XYZ Reconstruction from Non-Linear sRGB Images. CoRR (2024)
Amit Rozner, Barak Battash, Ofir Lindenbaum, Lior Wolf
Efficient Verification-Based Face Identification. FG (2024)
Idan Cohen, Sharon Gannot, Ofir Lindenbaum
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction. ICASSP (2024)
Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum
Domain-Generalizable Multiple-Domain Clustering. Trans. Mach. Learn. Res. 2024 (2024)
Jonathan Svirsky, Uri Shaham, Ofir Lindenbaum
Sparse Binarization for Fast Keyword Spotting. CoRR (2024)
Barak Battash, Amit Rozner, Lior Wolf, Ofir Lindenbaum
Obtaining Favorable Layouts for Multiple Object Generation. CoRR (2024)
Daniel Segal, Ofir Lindenbaum, Ariel Jaffe
Spectral Self-supervised Feature Selection. CoRR (2024)
Barak Battash, Lior Wolf, Ofir Lindenbaum
Revisiting the Noise Model of Stochastic Gradient Descent. AISTATS (2024)
Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum
Knowledge Editing in Language Models via Adapted Direct Preference Optimization. CoRR (2024)
Kobi Rahimi, Tom Tirer, Ofir Lindenbaum
Multiple Descents in Unsupervised Learning: The Role of Noise, Domain Shift and Anomalies. CoRR (2024)
Soham Jana, Henry Li, Yutaro Yamada, Ofir Lindenbaum
Support recovery with Projected Stochastic Gates: Theory and application for linear models. Signal Process. 213 (2023)
Amit Rozner, Barak Battash, Ofir Lindenbaum, Lior Wolf
Efficient Verification-Based Face Identification. CoRR (2023)
Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum
Domain-Generalizable Multiple-Domain Clustering. CoRR (2023)
Ofek Ophir, Orit Shefi, Ofir Lindenbaum
Neuronal Cell Type Classification using Deep Learning. CoRR (2023)
Ofek Ophir, Orit Shefi, Ofir Lindenbaum
Neuronal Cell Type Classification Using Locally Sparse Networks. ICASSP Workshops (2023)
Barak Battash, Ofir Lindenbaum
Revisiting the Noise Model of Stochastic Gradient Descent. CoRR (2023)
Jonathan Svirsky, Ofir Lindenbaum
Interpretable Deep Clustering. CoRR (2023)
Tamir Baruch Yampolsky, Ronen Talmon, Ofir Lindenbaum
Domain and Modality Adaptation Using Multi-Kernel Matching. EUSIPCO (2023)
Erez Peterfreund, Iryna Burak, Ofir Lindenbaum, Jim Gimlett, Felix Dietrich, Ronald R. Coifman, Ioannis G. Kevrekidis
Gappy local conformal auto-encoders for heterogeneous data fusion: in praise of rigidity. CoRR (2023)
Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe
Multi-modal Differentiable Unsupervised Feature Selection. CoRR (2023)
Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe
Multi-modal differentiable unsupervised feature selection. UAI (2023)
Amit Rozner, Barak Battash, Henry Li, Lior Wolf, Ofir Lindenbaum
Anomaly Detection with Variance Stabilized Density Estimation. CoRR (2023)
Ram Dyuthi Sristi, Ofir Lindenbaum, Maria Lavzin, Jackie Schiller, Gal Mishne, Hadas Benisty
Contextual Feature Selection with Conditional Stochastic Gates. CoRR (2023)
Jonathan Svirsky, Ofir Lindenbaum
SG-VAD: Stochastic Gates Based Speech Activity Detection. ICASSP (2023)
Guy Zamberg, Moshe Salhov, Ofir Lindenbaum, Amir Averbuch
TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models. CoRR (2023)
Idan Cohen, Ofir Lindenbaum, Sharon Gannot
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction. CoRR (2023)
Junchen Yang, Ofir Lindenbaum, Yuval Kluger
Locally Sparse Neural Networks for Tabular Biomedical Data. ICML (2022)
Jonathan Svirsky, Ofir Lindenbaum
SG-VAD: Stochastic Gates Based Speech Activity Detection. CoRR (2022)
Ofir Lindenbaum, Stefan Steinerberger
Refined least squares for support recovery. Signal Process. 195 (2022)
Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger
L0-Sparse Canonical Correlation Analysis. ICLR (2022)
Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger
Deep unsupervised feature selection by discarding nuisance and correlated features. Neural Networks 152 (2022)
Jonathan Gradstein, Moshe Salhov, Yoav Tulpan, Ofir Lindenbaum, Amir Averbuch
Imbalanced Classification via a Tabular Translation GAN. CoRR (2022)
Ofir Lindenbaum, Stefan Steinerberger
Randomly aggregated least squares for support recovery. Signal Process. 180 (2021)
Soham Jana, Henry Li, Yutaro Yamada, Ofir Lindenbaum
Support Recovery with Stochastic Gates: Theory and Application for Linear Models. CoRR (2021)
Junchen Yang, Ofir Lindenbaum, Yuval Kluger
Locally Sparse Networks for Interpretable Predictions. CoRR (2021)
Ofir Lindenbaum, Uri Shaham, Erez Peterfreund, Jonathan Svirsky, Nicolas Casey, Yuval Kluger
Differentiable Unsupervised Feature Selection based on a Gated Laplacian. NeurIPS (2021)
Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger
Deep Unsupervised Feature Selection by Discarding Nuisance and Correlated Features. CoRR (2021)
Yariv Aizenbud, Ofir Lindenbaum, Yuval Kluger
Probabilistic Robust Autoencoders for Anomaly Detection. CoRR (2021)
Erez Peterfreund, Ofir Lindenbaum, Felix Dietrich, Tom Bertalan, Matan Gavish, Ioannis G. Kevrekidis, Ronald R. Coifman
LOCA: LOcal Conformal Autoencoder for standardized data coordinates. CoRR (2020)
Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger
The Spectral Underpinning of word2vec. CoRR (2020)
Ofir Lindenbaum, Amir Sagiv, Gal Mishne, Ronen Talmon
Kernel-based parameter estimation of dynamical systems with unknown observation functions. CoRR (2020)
Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger
Variational Diffusion Autoencoders with Random Walk Sampling. ECCV (23) (2020)
Ofir Lindenbaum, Neta Rabin, Yuri Bregman, Amir Averbuch
Seismic Event Discrimination Using Deep CCA. IEEE Geosci. Remote. Sens. Lett. 17 (11) (2020)
Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
Feature Selection using Stochastic Gates. ICML (2020)
Ofir Lindenbaum, Stefan Steinerberger
Randomly Aggregated Least Squares for Support Recovery. CoRR (2020)
Ofir Lindenbaum, Arie Yeredor, Moshe Salhov, Amir Averbuch
Multi-view diffusion maps. Inf. Fusion 55 (2020)
Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger
Deep Gated Canonical Correlation Analysis. CoRR (2020)
Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger
The Spectral Underpinning of word2vec. Frontiers Appl. Math. Stat. 6 (2020)
Ofir Lindenbaum, Uri Shaham, Jonathan Svirsky, Erez Peterfreund, Yuval Kluger
Let the Data Choose its Features: Differentiable Unsupervised Feature Selection. CoRR (2020)
Ofir Lindenbaum, Moshe Salhov, Arie Yeredor, Amir Averbuch
Gaussian bandwidth selection for manifold learning and classification. Data Min. Knowl. Discov. 34 (6) (2020)
Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger
Diffusion Variational Autoencoders. CoRR (2019)
Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy
Geometry Based Data Generation. NeurIPS (2018)
Ofir Lindenbaum, Yuri Bregman, Neta Rabin, Amir Averbuch
Multiview Kernels for Low-Dimensional Modeling of Seismic Events. IEEE Trans. Geosci. Remote. Sens. 56 (6) (2018)
Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy
Geometry-Based Data Generation. CoRR (2018)
Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
Deep supervised feature selection using Stochastic Gates. CoRR (2018)
Ofir Lindenbaum, Moshe Salhov, Arie Yeredor, Amir Averbuch
Kernel Scaling for Manifold Learning and Classification. CoRR (2017)
Ofir Lindenbaum, Yuri Bregman, Neta Rabin, Amir Averbuch
Multi-View Kernels for Low-Dimensional Modeling of Seismic Events. CoRR (2017)
Ofir Lindenbaum, Arie Yeredor, Amir Averbuch
Clustering Based on MultiView Diffusion Maps. ICDM Workshops (2016)
Moshe Salhov, Ofir Lindenbaum, Avi Silberschatz, Yoel Shkolnisky, Amir Averbuch
Multi-View Kernel Consensus For Data Analysis and Signal Processing. CoRR (2016)
Ofir Lindenbaum, Arie Yeredor, Ran Vitek, Moshe Mishali
Blind Separation of Orthogonal Mixtures of Spatially-Sparse Sources with Unknown Sparsity Levels and with Temporal Blocks. J. Signal Process. Syst. 79 (2) (2015)
Ofir Lindenbaum, Arie Yeredor, Israel Cohen
Musical key extraction using diffusion maps. Signal Process. 117 (2015)
Ofir Lindenbaum, Arie Yeredor, Moshe Salhov
Learning Coupled Embedding Using MultiView Diffusion Maps. LVA/ICA (2015)
Ofir Lindenbaum, Arie Yeredor, Moshe Salhov, Amir Averbuch
MultiView Diffusion Maps. CoRR (2015)
Ofir Lindenbaum, Arie Yeredor, Ran Vitek, Moshe Mishali
Blind separation of spatially-block-sparse sources from orthogonal mixtures. MLSP (2013)