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2020 – today
- 2024
[j13]Ofek Ophir, Orit Shefi, Ofir Lindenbaum:
Classifying Neuronal Cell Types Based on Shared Electrophysiological Information from Humans and Mice. Neuroinformatics 22(4): 473-486 (2024)- [j12]Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum:
Domain-Generalizable Multiple-Domain Clustering. Trans. Mach. Learn. Res. 2024 (2024) - [c19]Barak Battash, Lior Wolf, Ofir Lindenbaum:
Revisiting the Noise Model of Stochastic Gradient Descent. AISTATS 2024: 4780-4788 - [c18]Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum:
Knowledge Editing in Language Models via Adapted Direct Preference Optimization. EMNLP (Findings) 2024: 4761-4774 - [c17]Amit Rozner, Barak Battash, Ofir Lindenbaum, Lior Wolf:
Efficient Verification-Based Face Identification. FG 2024: 1-10 - [c16]Idan Cohen, Sharon Gannot, Ofir Lindenbaum:
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction. ICASSP 2024: 386-390 - [c15]Ram Dyuthi Sristi, Ofir Lindenbaum, Shira Lifshitz, Maria Lavzin, Jackie Schiller, Gal Mishne, Hadas Benisty:
Contextual Feature Selection with Conditional Stochastic Gates. ICML 2024 - [c14]Jonathan Svirsky, Ofir Lindenbaum:
Interpretable Deep Clustering for Tabular Data. ICML 2024 - [i39]Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum:
Self Supervised Correlation-based Permutations for Multi-View Clustering. CoRR abs/2402.16383 (2024) - [i38]Barak Battash, Amit Rozner, Lior Wolf, Ofir Lindenbaum:
Obtaining Favorable Layouts for Multiple Object Generation. CoRR abs/2405.00791 (2024) - [i37]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 abs/2405.12265 (2024) - [i36]Jonathan Svirsky, Uri Shaham, Ofir Lindenbaum:
Sparse Binarization for Fast Keyword Spotting. CoRR abs/2406.06634 (2024) - [i35]Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum:
Knowledge Editing in Language Models via Adapted Direct Preference Optimization. CoRR abs/2406.09920 (2024) - [i34]Kobi Rahimi, Tom Tirer, Ofir Lindenbaum:
Multiple Descents in Unsupervised Learning: The Role of Noise, Domain Shift and Anomalies. CoRR abs/2406.11703 (2024) - [i33]Daniel Segal, Ofir Lindenbaum, Ariel Jaffe:
Spectral Self-supervised Feature Selection. CoRR abs/2407.09061 (2024) - [i32]Yehonathan Refael, Jonathan Svirsky, Boris Shustin, Wasim Huleihel, Ofir Lindenbaum:
AdaRankGrad: Adaptive Gradient-Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning. CoRR abs/2410.17881 (2024) - [i31]Iftach Arbel, Yehonathan Refael, Ofir Lindenbaum:
TransformLLM: Adapting Large Language Models via LLM-Transformed Reading Comprehension Text. CoRR abs/2410.21479 (2024) - 2023
- [j11]Soham Jana
, Henry Li, Yutaro Yamada, Ofir Lindenbaum:
Support recovery with Projected Stochastic Gates: Theory and application for linear models. Signal Process. 213: 109193 (2023) - [c13]Tamir Baruch Yampolsky, Ronen Talmon, Ofir Lindenbaum:
Domain and Modality Adaptation Using Multi-Kernel Matching. EUSIPCO 2023: 1285-1289 - [c12]Ofek Ophir, Orit Shefi, Ofir Lindenbaum:
Neuronal Cell Type Classification Using Locally Sparse Networks. ICASSP Workshops 2023: 1-5 - [c11]Jonathan Svirsky, Ofir Lindenbaum:
SG-VAD: Stochastic Gates Based Speech Activity Detection. ICASSP 2023: 1-5 - [c10]Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe:
Multi-modal differentiable unsupervised feature selection. UAI 2023: 2400-2410 - [i30]Idan Cohen, Ofir Lindenbaum, Sharon Gannot:
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction. CoRR abs/2301.00448 (2023) - [i29]Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum:
Domain-Generalizable Multiple-Domain Clustering. CoRR abs/2301.13530 (2023) - [i28]Barak Battash, Ofir Lindenbaum:
Revisiting the Noise Model of Stochastic Gradient Descent. CoRR abs/2303.02749 (2023) - [i27]Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe:
Multi-modal Differentiable Unsupervised Feature Selection. CoRR abs/2303.09381 (2023) - [i26]Ofek Ophir, Orit Shefi, Ofir Lindenbaum:
Neuronal Cell Type Classification using Deep Learning. CoRR abs/2306.00528 (2023) - [i25]Amit Rozner, Barak Battash, Henry Li, Lior Wolf, Ofir Lindenbaum:
Anomaly Detection with Variance Stabilized Density Estimation. CoRR abs/2306.00582 (2023) - [i24]Jonathan Svirsky, Ofir Lindenbaum:
Interpretable Deep Clustering. CoRR abs/2306.04785 (2023) - [i23]Guy Zamberg, Moshe Salhov, Ofir Lindenbaum, Amir Averbuch:
TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models. CoRR abs/2307.12336 (2023) - [i22]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 abs/2312.13155 (2023) - [i21]Amit Rozner, Barak Battash, Ofir Lindenbaum, Lior Wolf:
Efficient Verification-Based Face Identification. CoRR abs/2312.13240 (2023) - [i20]Ram Dyuthi Sristi, Ofir Lindenbaum, Maria Lavzin, Jackie Schiller, Gal Mishne, Hadas Benisty:
Contextual Feature Selection with Conditional Stochastic Gates. CoRR abs/2312.14254 (2023) - 2022
- [j10]Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger:
Deep unsupervised feature selection by discarding nuisance and correlated features. Neural Networks 152: 34-43 (2022) - [j9]Ofir Lindenbaum, Stefan Steinerberger:
Refined least squares for support recovery. Signal Process. 195: 108493 (2022) - [c9]Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger:
L0-Sparse Canonical Correlation Analysis. ICLR 2022 - [c8]Junchen Yang, Ofir Lindenbaum, Yuval Kluger:
Locally Sparse Neural Networks for Tabular Biomedical Data. ICML 2022: 25123-25153 - [i19]Jonathan Gradstein, Moshe Salhov, Yoav Tulpan, Ofir Lindenbaum, Amir Averbuch:
Imbalanced Classification via a Tabular Translation GAN. CoRR abs/2204.08683 (2022) - [i18]Jonathan Svirsky, Ofir Lindenbaum:
SG-VAD: Stochastic Gates Based Speech Activity Detection. CoRR abs/2210.16022 (2022) - 2021
- [j8]Ofir Lindenbaum, Stefan Steinerberger:
Randomly aggregated least squares for support recovery. Signal Process. 180: 107858 (2021) - [c7]Ofir Lindenbaum, Uri Shaham, Erez Peterfreund, Jonathan Svirsky, Nicolas Casey, Yuval Kluger:
Differentiable Unsupervised Feature Selection based on a Gated Laplacian. NeurIPS 2021: 1530-1542 - [i17]Junchen Yang, Ofir Lindenbaum, Yuval Kluger:
Locally Sparse Networks for Interpretable Predictions. CoRR abs/2106.06468 (2021) - [i16]Yariv Aizenbud, Ofir Lindenbaum, Yuval Kluger:
Probabilistic Robust Autoencoders for Anomaly Detection. CoRR abs/2110.00494 (2021) - [i15]Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger:
Deep Unsupervised Feature Selection by Discarding Nuisance and Correlated Features. CoRR abs/2110.05306 (2021) - [i14]Soham Jana, Henry Li, Yutaro Yamada, Ofir Lindenbaum:
Support Recovery with Stochastic Gates: Theory and Application for Linear Models. CoRR abs/2110.15960 (2021) - 2020
- [j7]Ofir Lindenbaum, Moshe Salhov, Arie Yeredor, Amir Averbuch:
Gaussian bandwidth selection for manifold learning and classification. Data Min. Knowl. Discov. 34(6): 1676-1712 (2020) - [j6]Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger:
The Spectral Underpinning of word2vec. Frontiers Appl. Math. Stat. 6: 593406 (2020) - [j5]Ofir Lindenbaum, Arie Yeredor, Moshe Salhov, Amir Averbuch:
Multi-view diffusion maps. Inf. Fusion 55: 127-149 (2020) - [j4]Ofir Lindenbaum, Neta Rabin, Yuri Bregman, Amir Averbuch:
Seismic Event Discrimination Using Deep CCA. IEEE Geosci. Remote. Sens. Lett. 17(11): 1856-1860 (2020) - [c6]Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger:
Variational Diffusion Autoencoders with Random Walk Sampling. ECCV (23) 2020: 362-378 - [c5]Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger:
Feature Selection using Stochastic Gates. ICML 2020: 10648-10659 - [i13]Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger:
The Spectral Underpinning of word2vec. CoRR abs/2002.12317 (2020) - [i12]Ofir Lindenbaum, Stefan Steinerberger:
Randomly Aggregated Least Squares for Support Recovery. CoRR abs/2003.07331 (2020) - [i11]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 abs/2004.07234 (2020) - [i10]Ofir Lindenbaum, Uri Shaham, Jonathan Svirsky, Erez Peterfreund, Yuval Kluger:
Let the Data Choose its Features: Differentiable Unsupervised Feature Selection. CoRR abs/2007.04728 (2020) - [i9]Ofir Lindenbaum, Amir Sagiv, Gal Mishne, Ronen Talmon:
Kernel-based parameter estimation of dynamical systems with unknown observation functions. CoRR abs/2009.04142 (2020) - [i8]Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger:
Deep Gated Canonical Correlation Analysis. CoRR abs/2010.05620 (2020)
2010 – 2019
- 2019
- [i7]Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger:
Diffusion Variational Autoencoders. CoRR abs/1905.12724 (2019) - 2018
- [j3]Ofir Lindenbaum, Yuri Bregman, Neta Rabin, Amir Averbuch:
Multiview Kernels for Low-Dimensional Modeling of Seismic Events. IEEE Trans. Geosci. Remote. Sens. 56(6): 3300-3310 (2018) - [c4]Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy:
Geometry Based Data Generation. NeurIPS 2018: 1407-1418 - [i6]Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy:
Geometry-Based Data Generation. CoRR abs/1802.04927 (2018) - [i5]Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger:
Deep supervised feature selection using Stochastic Gates. CoRR abs/1810.04247 (2018) - 2017
- [i4]Ofir Lindenbaum, Yuri Bregman, Neta Rabin, Amir Averbuch:
Multi-View Kernels for Low-Dimensional Modeling of Seismic Events. CoRR abs/1706.01750 (2017) - [i3]Ofir Lindenbaum, Moshe Salhov, Arie Yeredor, Amir Averbuch:
Kernel Scaling for Manifold Learning and Classification. CoRR abs/1707.01093 (2017) - 2016
- [c3]Ofir Lindenbaum, Arie Yeredor, Amir Averbuch:
Clustering Based on MultiView Diffusion Maps. ICDM Workshops 2016: 740-747 - [i2]Moshe Salhov, Ofir Lindenbaum, Avi Silberschatz, Yoel Shkolnisky, Amir Averbuch:
Multi-View Kernel Consensus For Data Analysis and Signal Processing. CoRR abs/1606.08819 (2016) - 2015
- [j2]Ofir Lindenbaum, Arie Yeredor, Israel Cohen:
Musical key extraction using diffusion maps. Signal Process. 117: 198-207 (2015) - [j1]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): 167-178 (2015) - [c2]Ofir Lindenbaum, Arie Yeredor, Moshe Salhov:
Learning Coupled Embedding Using MultiView Diffusion Maps. LVA/ICA 2015: 127-134 - [i1]Ofir Lindenbaum, Arie Yeredor, Moshe Salhov, Amir Averbuch:
MultiView Diffusion Maps. CoRR abs/1508.05550 (2015) - 2013
- [c1]Ofir Lindenbaum, Arie Yeredor, Ran Vitek, Moshe Mishali:
Blind separation of spatially-block-sparse sources from orthogonal mixtures. MLSP 2013: 1-6
Coauthor Index
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last updated on 2024-12-10 20:47 CET by the dblp team
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