Tomer Galanti

According to our database, Tomer Galanti authored at least 44 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning.

Achleshwar Luthra, Tianbao Yang, Tomer Galanti

CoRR, June, 2025

DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization.

Gang Li, Ming Lin, Tomer Galanti, Zhengzhong Tu, Tianbao Yang

CoRR, May, 2025

Centered Self-attention Layers.

Ameen Ali, Tomer Galanti, Lior Wolf

Proceedings of the Image Analysis - 23rd Scandinavian Conference, 2025

Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference.

Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg, Moshe Wasserblat, Tomer Galanti, Michal Gordon-Kiwkowitz, David Harel

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Formation of Representations in Neural Networks.

Liu Ziyin, Isaac L. Chuang, Tomer Galanti, Tomaso A. Poggio

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

SGD with Weight Decay Secretly Minimizes the Ranks of Your Neural Networks.

Tomer Galanti, Zachary S. Siegel, Aparna Gupte, Tomaso A. Poggio

Proceedings of the Conference on Parsimony and Learning, 2025

2024

The Fair Language Model Paradox.

Andrea Pinto, Tomer Galanti, Randall Balestriero

CoRR, 2024

Distributed Speculative Inference of Large Language Models.

Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg, Moshe Wasserblat, Tomer Galanti, Michal Gordon, David Harel

CoRR, 2024

On the Power of Decision Trees in Auto-Regressive Language Modeling.

Yulu Gan, Tomer Galanti, Tomaso A. Poggio, Eran Malach

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Distributed Speculative Inference of Large Language Models is Provably Faster.

Nadav Timor, Jonathan Mamou, Oren Pereg, Moshe Berchansky, Daniel Korat, Moshe Wasserblat, Tomer Galanti, Michal Gordon, David Harel

Proceedings of the NeurIPS Efficient Natural Language and Speech Processing Workshop, 2024

2023

Comparative Generalization Bounds for Deep Neural Networks.

Tomer Galanti, Liane Galanti, Ido Ben-Shaul

Trans. Mach. Learn. Res., 2023

Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions.

Ido Ben-Shaul, Tomer Galanti, Shai Dekel

Trans. Mach. Learn. Res., 2023

The Probabilistic Stability of Stochastic Gradient Descent.

Liu Ziyin, Botao Li, Tomer Galanti, Masahito Ueda

CoRR, 2023

Norm-based Generalization Bounds for Compositionally Sparse Neural Networks.

Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio

CoRR, 2023

Norm-based Generalization Bounds for Sparse Neural Networks.

Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reverse Engineering Self-Supervised Learning.

Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Feature learning in deep classifiers through Intermediate Neural Collapse.

Akshay Rangamani, Marius Lindegaard, Tomer Galanti, Tomaso A. Poggio

Proceedings of the International Conference on Machine Learning, 2023

2022

Generalization Bounds for Transfer Learning with Pretrained Classifiers.

Tomer Galanti, András György, Marcus Hutter

CoRR, 2022

SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks.

Tomer Galanti, Tomaso A. Poggio

CoRR, 2022

A Note on the Implicit Bias Towards Minimal Depth of Deep Neural Networks.

Tomer Galanti

CoRR, 2022

On the Role of Neural Collapse in Transfer Learning.

Tomer Galanti, András György, Marcus Hutter

Proceedings of the Tenth International Conference on Learning Representations, 2022

Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models.

Chenfeng Xu, Shijia Yang, Tomer Galanti, Bichen Wu, Xiangyu Yue, Bohan Zhai, Wei Zhan, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka

Proceedings of the Computer Vision - ECCV 2022, 2022

Weakly Supervised Discovery of Semantic Attributes.

Ameen Ali, Tomer Galanti, Evgenii Zheltonozhskii, Chaim Baskin, Lior Wolf

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

On the Emergence of Semantic Structure in Deep Learning

Tomer Galanti

PhD thesis, 2021

Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs.

Tomer Galanti, Sagie Benaim, Lior Wolf

J. Mach. Learn. Res., 2021

Evaluation Metrics for Conditional Image Generation.

Yaniv Benny, Tomer Galanti, Sagie Benaim, Lior Wolf

Int. J. Comput. Vis., 2021

Intersection Regularization for Extracting Semantic Attributes.

Ameen Ali, Tomer Galanti, Evgeniy Zheltonozhskiy, Chaim Baskin, Lior Wolf

CoRR, 2021

On random kernels of residual architectures.

Etai Littwin, Tomer Galanti, Lior Wolf

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Meta Internal Learning.

Raphael Bensadoun, Shir Gur, Tomer Galanti, Lior Wolf

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

On the Optimization Dynamics of Wide Hypernetworks.

Etai Littwin, Tomer Galanti, Lior Wolf

CoRR, 2020

A Critical View of the Structural Causal Model.

Tomer Galanti, Ofir Nabati, Lior Wolf

CoRR, 2020

Comparing the Parameter Complexity of Hypernetworks and the Embedding-Based Alternative.

Tomer Galanti, Lior Wolf

CoRR, 2020

On Infinite-Width Hypernetworks.

Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Modularity of Hypernetworks.

Tomer Galanti, Lior Wolf

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Unsupervised Learning of the Set of Local Maxima.

Lior Wolf, Sagie Benaim, Tomer Galanti

Proceedings of the 7th International Conference on Learning Representations, 2019

Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer.

Ori Press, Tomer Galanti, Sagie Benaim, Lior Wolf

Proceedings of the 7th International Conference on Learning Representations, 2019

Domain Intersection and Domain Difference.

Sagie Benaim, Michael Khaitov, Tomer Galanti, Lior Wolf

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

A Formal Approach to Explainability.

Lior Wolf, Tomer Galanti, Tamir Hazan

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs.

Tomer Galanti, Sagie Benaim, Lior Wolf

CoRR, 2018

The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings.

Tomer Galanti, Lior Wolf, Sagie Benaim

Proceedings of the 6th International Conference on Learning Representations, 2018

Estimating the Success of Unsupervised Image to Image Translation.

Sagie Benaim, Tomer Galanti, Lior Wolf

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

Maximally Distant Cross Domain Generators for Estimating Per-Sample Error.

Sagie Benaim, Tomer Galanti, Lior Wolf

CoRR, 2017

Unsupervised Learning of Semantic Mappings.

Tomer Galanti, Lior Wolf

CoRR, 2017

A Theory of Output-Side Unsupervised Domain Adaptation.

Tomer Galanti, Lior Wolf

CoRR, 2017