Ofir Lindenbaum

99 papers A* 11A 6B 1Misc 3Journal 71Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Lorenza: Enhancing Generalization in Low-Rank Gradient LLM Training via Efficient Zeroth-Order Adaptive SAM. Trans. Mach. Learn. Res. Yehonathan Refael, Iftach Arbel, Ofir Lindenbaum, Tom Tirer
2026	J	`jnl`	Train Less, Infer Faster: Efficient Model Finetuning and Compression via Structured Sparsity. CoRR Jonathan Svirsky, Yehonathan Refael, Ofir Lindenbaum
2026	J	`jnl`	Uncovering a Winning Lottery Ticket with Continuously Relaxed Bernoulli Gates. CoRR Itamar Tsayag, Ofir Lindenbaum
2026	A*	`conf`	Unsupervised Feature Selection Through Group Discovery. AAAI Shira Lifshitz, Ofir Lindenbaum, Gal Mishne, Ron Meir, Hadas Benisty
2025	A*	`conf`	AdaRankGrad: Adaptive Gradient Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning. ICLR Yehonathan Refael, Jonathan Svirsky, Boris Shustin, Wasim Huleihel, Ofir Lindenbaum
2025	A*	`conf`	COPER: Correlation-based Permutations for Multi-View Clustering. ICLR Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum
2025	Misc	`conf`	Conditional Deep Canonical Time Warping. ICASSP Ran Eisenberg, Afek Steinberg, Ofir Lindenbaum
2025	J	`jnl`	Detect and Correct: A Selective Noise Correction Method for Learning with Noisy Labels. CoRR Yuval Grinberg, Nimrod Harel, Jacob Goldberger, Ofir Lindenbaum
2025	J	`jnl`	From Segments to Concepts: Interpretable Image Classification via Concept-Guided Segmentation. CoRR Ran Eisenberg, Amit Rozner, Ethan Fetaya, Ofir Lindenbaum
2025	J	`jnl`	Generalizable and Robust Spectral Method for Multi-view Representation Learning. Trans. Mach. Learn. Res. Amitai Yacobi, Ofir Lindenbaum, Uri Shaham
2025	J	`jnl`	Gradient Free Deep Reinforcement Learning With TabPFN. CoRR David Schiff, Ofir Lindenbaum, Yonathan Efroni
2025	J	`jnl`	Hybrid Autoencoders for Tabular Data: Leveraging Model-Based Augmentation in Low-Label Settings. CoRR Erel Naor, Ofir Lindenbaum
2025	J	`jnl`	LORENZA: Enhancing Generalization in Low-Rank Gradient LLM Training via Efficient Zeroth-Order Adaptive SAM. CoRR Yehonathan Refael, Iftach Arbel, Ofir Lindenbaum, Tom Tirer
2025	J	`jnl`	No Prior, No Leakage: Revisiting Reconstruction Attacks in Trained Neural Networks. CoRR Yehonathan Refael, Guy Smorodinsky, Ofir Lindenbaum, Itay Safran
2025	A*	`conf`	Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data. ICML Erez Peterfreund, Ofir Lindenbaum, Yuval Kluger, Boris Landa
2025	J	`jnl`	Provable Speech Attributes Conversion via Latent Independence. CoRR Jonathan Svirsky, Ofir Lindenbaum, Uri Shaham
2025	J	`jnl`	SUMO: Subspace-Aware Moment-Orthogonalization for Accelerating Memory-Efficient LLM Training. CoRR Yehonathan Refael, Guy Smorodinsky, Tom Tirer, Ofir Lindenbaum
2025	A	`conf`	Supervised Embedded Methods for Hyperspectral Band Selection. ECAI Yaniv Zimmer, Ofir Lindenbaum, Oren Glickman
2025	J	`jnl`	TempoControl: Temporal Attention Guidance for Text-to-Video Models. CoRR Shira Schiber, Ofir Lindenbaum, Idan Schwartz
2025	J	`jnl`	Unsupervised Feature Selection Through Group Discovery. CoRR Shira Lifshitz, Ofir Lindenbaum, Gal Mishne, Ron Meir, Hadas Benisty
2025	J	`jnl`	Unveiling Multiple Descents in Unsupervised Autoencoders. Trans. Mach. Learn. Res. Kobi Rahimi, Yehonathan Refael, Tom Tirer, Ofir Lindenbaum
2024	J	`jnl`	AdaRankGrad: Adaptive Gradient-Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning. CoRR Yehonathan Refael, Jonathan Svirsky, Boris Shustin, Wasim Huleihel, Ofir Lindenbaum
2024	A	`conf`	Anomaly Detection with Variance Stabilized Density Estimation. UAI Amit Rozner, Barak Battash, Henry Li, Lior Wolf, Ofir Lindenbaum
2024	J	`jnl`	Classifying Neuronal Cell Types Based on Shared Electrophysiological Information from Humans and Mice. Neuroinformatics Ofek Ophir, Orit Shefi, Ofir Lindenbaum
2024	J	`jnl`	Conditional Deep Canonical Time Warping. CoRR Afek Steinberg, Ran Eisenberg, Ofir Lindenbaum
2024	A*	`conf`	Contextual Feature Selection with Conditional Stochastic Gates. ICML Ram Dyuthi Sristi, Ofir Lindenbaum, Shira Lifshitz, Maria Lavzin, Jackie Schiller, Gal Mishne, Hadas Benisty
2024	J	`jnl`	Domain-Generalizable Multiple-Domain Clustering. Trans. Mach. Learn. Res. Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum
2024	B	`conf`	Efficient Verification-Based Face Identification. FG Amit Rozner, Barak Battash, Ofir Lindenbaum, Lior Wolf
2024	J	`jnl`	FineGates: LLMs Finetuning with Compression using Stochastic Gates. CoRR Jonathan Svirsky, Yehonathan Refael, Ofir Lindenbaum
2024	A*	`conf`	Interpretable Deep Clustering for Tabular Data. ICML Jonathan Svirsky, Ofir Lindenbaum
2024	—	`conf`	Knowledge Editing in Language Models via Adapted Direct Preference Optimization. EMNLP (Findings) Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum
2024	J	`jnl`	Knowledge Editing in Language Models via Adapted Direct Preference Optimization. CoRR Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum
2024	J	`jnl`	Multiple Descents in Unsupervised Learning: The Role of Noise, Domain Shift and Anomalies. CoRR Kobi Rahimi, Tom Tirer, Ofir Lindenbaum
2024	J	`jnl`	Obtaining Favorable Layouts for Multiple Object Generation. CoRR Barak Battash, Amit Rozner, Lior Wolf, Ofir Lindenbaum
2024	A	`conf`	Revisiting the Noise Model of Stochastic Gradient Descent. AISTATS Barak Battash, Lior Wolf, Ofir Lindenbaum
2024	J	`jnl`	SEL-CIE: Knowledge-Guided Self-Supervised Learning Framework for CIE-XYZ Reconstruction from Non-Linear sRGB Images. CoRR Shir Barzel, Moshe Salhov, Ofir Lindenbaum, Amir Averbuch
2024	J	`jnl`	Self Supervised Correlation-based Permutations for Multi-View Clustering. CoRR Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum
2024	A	`conf`	Sparse Binarization for Fast Keyword Spotting. INTERSPEECH Jonathan Svirsky, Uri Shaham, Ofir Lindenbaum
2024	J	`jnl`	Sparse Binarization for Fast Keyword Spotting. CoRR Jonathan Svirsky, Uri Shaham, Ofir Lindenbaum
2024	J	`jnl`	SpecRaGE: Robust and Generalizable Multi-view Spectral Representation Learning. CoRR Amitai Yacobi, Ofir Lindenbaum, Uri Shaham
2024	J	`jnl`	Spectral Self-supervised Feature Selection. CoRR Daniel Segal, Ofir Lindenbaum, Ariel Jaffe
2024	J	`jnl`	Spectral Self-supervised Feature Selection. Trans. Mach. Learn. Res. Daniel Segal, Ofir Lindenbaum, Ariel Jaffe
2024	A	`conf`	Transductive and Inductive Outlier Detection with Robust Autoencoders. UAI Ofir Lindenbaum, Yariv Aizenbud, Yuval Kluger
2024	J	`jnl`	TransformLLM: Adapting Large Language Models via LLM-Transformed Reading Comprehension Text. CoRR Iftach Arbel, Yehonathan Refael, Ofir Lindenbaum
2024	Misc	`conf`	Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction. ICASSP Idan Cohen, Sharon Gannot, Ofir Lindenbaum
2023	J	`jnl`	Anomaly Detection with Variance Stabilized Density Estimation. CoRR Amit Rozner, Barak Battash, Henry Li, Lior Wolf, Ofir Lindenbaum
2023	J	`jnl`	Contextual Feature Selection with Conditional Stochastic Gates. CoRR Ram Dyuthi Sristi, Ofir Lindenbaum, Maria Lavzin, Jackie Schiller, Gal Mishne, Hadas Benisty
2023	—	`conf`	Domain and Modality Adaptation Using Multi-Kernel Matching. EUSIPCO Tamir Baruch Yampolsky, Ronen Talmon, Ofir Lindenbaum
2023	J	`jnl`	Domain-Generalizable Multiple-Domain Clustering. CoRR Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum
2023	J	`jnl`	Efficient Verification-Based Face Identification. CoRR Amit Rozner, Barak Battash, Ofir Lindenbaum, Lior Wolf
2023	J	`jnl`	Gappy local conformal auto-encoders for heterogeneous data fusion: in praise of rigidity. CoRR Erez Peterfreund, Iryna Burak, Ofir Lindenbaum, Jim Gimlett, Felix Dietrich, Ronald R. Coifman, Ioannis G. Kevrekidis
2023	J	`jnl`	Interpretable Deep Clustering. CoRR Jonathan Svirsky, Ofir Lindenbaum
2023	J	`jnl`	Multi-modal Differentiable Unsupervised Feature Selection. CoRR Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe
2023	A	`conf`	Multi-modal differentiable unsupervised feature selection. UAI Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe
2023	—	`conf`	Neuronal Cell Type Classification Using Locally Sparse Networks. ICASSP Workshops Ofek Ophir, Orit Shefi, Ofir Lindenbaum
2023	J	`jnl`	Neuronal Cell Type Classification using Deep Learning. CoRR Ofek Ophir, Orit Shefi, Ofir Lindenbaum
2023	J	`jnl`	Revisiting the Noise Model of Stochastic Gradient Descent. CoRR Barak Battash, Ofir Lindenbaum
2023	Misc	`conf`	SG-VAD: Stochastic Gates Based Speech Activity Detection. ICASSP Jonathan Svirsky, Ofir Lindenbaum
2023	J	`jnl`	Support recovery with Projected Stochastic Gates: Theory and application for linear models. Signal Process. Soham Jana, Henry Li, Yutaro Yamada, Ofir Lindenbaum
2023	J	`jnl`	TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models. CoRR Guy Zamberg, Moshe Salhov, Ofir Lindenbaum, Amir Averbuch
2023	J	`jnl`	Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction. CoRR Idan Cohen, Ofir Lindenbaum, Sharon Gannot
2022	J	`jnl`	Deep unsupervised feature selection by discarding nuisance and correlated features. Neural Networks Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger
2022	J	`jnl`	Imbalanced Classification via a Tabular Translation GAN. CoRR Jonathan Gradstein, Moshe Salhov, Yoav Tulpan, Ofir Lindenbaum, Amir Averbuch
2022	A*	`conf`	L0-Sparse Canonical Correlation Analysis. ICLR Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger
2022	A*	`conf`	Locally Sparse Neural Networks for Tabular Biomedical Data. ICML Junchen Yang, Ofir Lindenbaum, Yuval Kluger
2022	J	`jnl`	Refined least squares for support recovery. Signal Process. Ofir Lindenbaum, Stefan Steinerberger
2022	J	`jnl`	SG-VAD: Stochastic Gates Based Speech Activity Detection. CoRR Jonathan Svirsky, Ofir Lindenbaum
2021	J	`jnl`	Deep Unsupervised Feature Selection by Discarding Nuisance and Correlated Features. CoRR Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger
2021	A*	`conf`	Differentiable Unsupervised Feature Selection based on a Gated Laplacian. NeurIPS Ofir Lindenbaum, Uri Shaham, Erez Peterfreund, Jonathan Svirsky, Nicolas Casey, Yuval Kluger
2021	J	`jnl`	Locally Sparse Networks for Interpretable Predictions. CoRR Junchen Yang, Ofir Lindenbaum, Yuval Kluger
2021	J	`jnl`	Probabilistic Robust Autoencoders for Anomaly Detection. CoRR Yariv Aizenbud, Ofir Lindenbaum, Yuval Kluger
2021	J	`jnl`	Randomly aggregated least squares for support recovery. Signal Process. Ofir Lindenbaum, Stefan Steinerberger
2021	J	`jnl`	Support Recovery with Stochastic Gates: Theory and Application for Linear Models. CoRR Soham Jana, Henry Li, Yutaro Yamada, Ofir Lindenbaum
2020	J	`jnl`	Deep Gated Canonical Correlation Analysis. CoRR Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger
2020	A*	`conf`	Feature Selection using Stochastic Gates. ICML Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
2020	J	`jnl`	Gaussian bandwidth selection for manifold learning and classification. Data Min. Knowl. Discov. Ofir Lindenbaum, Moshe Salhov, Arie Yeredor, Amir Averbuch
2020	J	`jnl`	Kernel-based parameter estimation of dynamical systems with unknown observation functions. CoRR Ofir Lindenbaum, Amir Sagiv, Gal Mishne, Ronen Talmon
2020	J	`jnl`	LOCA: LOcal Conformal Autoencoder for standardized data coordinates. CoRR Erez Peterfreund, Ofir Lindenbaum, Felix Dietrich, Tom Bertalan, Matan Gavish, Ioannis G. Kevrekidis, Ronald R. Coifman
2020	J	`jnl`	Let the Data Choose its Features: Differentiable Unsupervised Feature Selection. CoRR Ofir Lindenbaum, Uri Shaham, Jonathan Svirsky, Erez Peterfreund, Yuval Kluger
2020	J	`jnl`	Multi-view diffusion maps. Inf. Fusion Ofir Lindenbaum, Arie Yeredor, Moshe Salhov, Amir Averbuch
2020	J	`jnl`	Randomly Aggregated Least Squares for Support Recovery. CoRR Ofir Lindenbaum, Stefan Steinerberger
2020	J	`jnl`	Seismic Event Discrimination Using Deep CCA. IEEE Geosci. Remote. Sens. Lett. Ofir Lindenbaum, Neta Rabin, Yuri Bregman, Amir Averbuch
2020	J	`jnl`	The Spectral Underpinning of word2vec. CoRR Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger
2020	J	`jnl`	The Spectral Underpinning of word2vec. Frontiers Appl. Math. Stat. Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger
2020	—	`conf`	Variational Diffusion Autoencoders with Random Walk Sampling. ECCV (23) Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger
2019	J	`jnl`	Diffusion Variational Autoencoders. CoRR Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger
2018	J	`jnl`	Deep supervised feature selection using Stochastic Gates. CoRR Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
2018	A*	`conf`	Geometry Based Data Generation. NeurIPS Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy
2018	J	`jnl`	Geometry-Based Data Generation. CoRR Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy
2018	J	`jnl`	Multiview Kernels for Low-Dimensional Modeling of Seismic Events. IEEE Trans. Geosci. Remote. Sens. Ofir Lindenbaum, Yuri Bregman, Neta Rabin, Amir Averbuch
2017	J	`jnl`	Kernel Scaling for Manifold Learning and Classification. CoRR Ofir Lindenbaum, Moshe Salhov, Arie Yeredor, Amir Averbuch
2017	J	`jnl`	Multi-View Kernels for Low-Dimensional Modeling of Seismic Events. CoRR Ofir Lindenbaum, Yuri Bregman, Neta Rabin, Amir Averbuch
2016	—	`conf`	Clustering Based on MultiView Diffusion Maps. ICDM Workshops Ofir Lindenbaum, Arie Yeredor, Amir Averbuch
2016	J	`jnl`	Multi-View Kernel Consensus For Data Analysis and Signal Processing. CoRR Moshe Salhov, Ofir Lindenbaum, Avi Silberschatz, Yoel Shkolnisky, Amir Averbuch
2015	J	`jnl`	Blind Separation of Orthogonal Mixtures of Spatially-Sparse Sources with Unknown Sparsity Levels and with Temporal Blocks. J. Signal Process. Syst. Ofir Lindenbaum, Arie Yeredor, Ran Vitek, Moshe Mishali
2015	—	`conf`	Learning Coupled Embedding Using MultiView Diffusion Maps. LVA/ICA Ofir Lindenbaum, Arie Yeredor, Moshe Salhov
2015	J	`jnl`	MultiView Diffusion Maps. CoRR Ofir Lindenbaum, Arie Yeredor, Moshe Salhov, Amir Averbuch
2015	J	`jnl`	Musical key extraction using diffusion maps. Signal Process. Ofir Lindenbaum, Arie Yeredor, Israel Cohen
2013	—	`conf`	Blind separation of spatially-block-sparse sources from orthogonal mixtures. MLSP Ofir Lindenbaum, Arie Yeredor, Ran Vitek, Moshe Mishali