SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network
T. Galanti, Z. Siegel, A. Gupte, T. Poggio
Conference on Parsimony and Learning, CPAL, 2025
NeurIPS Workshop on Mathematics of Modern Machine Learning, M3L, 2024
Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
N. Timor, J. Mamou, D. Korat, M. Berchansky, O. Pereg, M. Wasserblat, T. Galanti, M. Gordon, D. Harel
International Conference on Learning Representations, ICLR, 2025
Formation of Representations in Neural Networks
L. Ziyin, I. L. Chuang, T. Galanti, T. Poggio
International Conference on Learning Representations, ICLR, 2025
Spotlight presentation (5% acceptance)
On the Power of Decision Trees in Auto-Regressive Language Modeling
Y. Gan, T. Galanti, T. Poggio, E. Malach
Neural Information Processing Systems, NeurIPS, 2024
Distributed Speculative Inference of Large Language Models is Provably Faster
N. Timor, J. Mamou, D. Korat, M. Berchansky, O. Pereg, M. Wasserblat, T. Galanti, M. Gordon, D. Harel
NeurIPS Workshop on Efficient Natural Language and Speech Processing (ENLSP), 2024 (published at PMLR).
Norm-Based Generalization Bounds for Sparse Neural Networks
T. Galanti, M. Xu, L. Galanti, T. Poggio
Neural Information Processing Systems, NeurIPS, 2023
Reverse Engineering Self-Supervised Learning
I. Ben-Shaul, R. Shwartz-Ziv*, T. Galanti*, S. Dekel, Y. LeCun
Neural Information Processing Systems, NeurIPS, 2023
Comparative Generalization Bounds for Deep Neural Networks
T. Galanti, L. Galanti, I. Ben-Shaul
Transactions in Machine Learning Research, TMLR, 2023
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions
I. Ben-Shaul, T. Galanti, S. Dekel
Transactions in Machine Learning Research, TMLR, 2023
Feature Learning in Deep Classifiers Through Intermediate Neural Collapse
A. Rangamani, M. Lindegaard, T. Galanti, T. Poggio
International Conference on Machine Learning, ICML, 2023
Dynamics of Deep Classifiers Trained with the Square Loss: Normalization, Low Rank, Neural Collapse and Generalization Bounds
M. Xu, A. Rangamani, Q. Liao, T. Galanti, T. Poggio
Research (a Science partner journal), 2023
Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models
C. Xu, S. Yang, T. Galanti, B. Wu, X. Yue, B. Zhai, W. Zhan, P. Vajda, K. Keutzer, M. Tomizuka
IEEE European Conference on Computer Vision, ECCV, 2022
Improved Generalization Bounds for Transfer Learning via Neural Collapse
T. Galanti, A. Gyorgy, M. Hutter
ICML Workshop on Pretraining: Perspectives, Pitfalls and Paths Forward, 2022
On the Implicit Bias Towards Depth Minimization in Deep Neural Networks
T. Galanti, L. Galanti, I. Ben-Shaul
Conference on the Mathematical Theory of Deep Neural Networks, DEEPMATH, 2022
Workshop on the Theory of Overparameterized Machine Learning, TOPML, 2022
On the Role of Neural Collapse in Transfer Learning
T. Galanti, A. Gyorgy, M. Hutter
International Conference on Learning Representations, ICLR, 2022
Weakly Supervised Discovery of Semantic Attributes
A. A. Ali, T. Galanti, E. Zheltonozhskii, C. Baskin, L. Wolf
Causal Learning and Reasoning, CLeaR, 2022
Meta Internal Learning
R. Ben Sadoun, S. Gur, T. Galanti, L. Wolf
Neural Information Processing Systems, NeurIPS, 2021
On Random Kernels of Residual Architectures
E. Littwin*, T. Galanti*, L. Wolf
Uncertainty in Artificial Intelligence, UAI, 2021
Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs
T. Galanti, S. Benaim, L. Wolf
Journal of Machine Learning Research, JMLR, 2021
Evaluation Metrics for Conditional Image Generation
Y. Benny, T. Galanti, S. Benaim, L. Wolf
International Journal of Computer Vision, IJCV, 2021
On the Modularity of Hypernetworks
T. Galanti, L. Wolf
Neural Information Processing Systems, NeurIPS, 2020
Oral presentation (1% acceptance)
On Infinite-Width Hypernetworks
E. Littwin*, T. Galanti*, L. Wolf
Neural Information Processing Systems, NeurIPS, 2020
Domain Intersection and Domain Difference
S. Benaim, M. Khaitov, T. Galanti, L. Wolf
IEEE International Conference on Computer Vision, ICCV, 2019
Unsuperivsed Learning of the Set of Local Maxima
L. Wolf, S. Benaim, T. Galanti
International Conference on Learning Representations, ICLR, 2019
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer
O. Press, T. Galanti, S. Benaim, L. Wolf
International Conference on Learning Representations, ICLR, 2019
A Formal Approach to Explainability
L. Wolf, T. Galanti, T. Hazan
Artificial Intelligence, Ethics and Society, AIES, 2019
Generalization Bounds for Cross-Domain Mapping with WGANs
T. Galanti, S. Benaim, L. Wolf
NeurIPS Workshop on Integration of Deep Learning Theories, 2018
Estimating the Success of Unsupervised Image to Image Translation
S. Benaim*, T. Galanti*, L. Wolf
IEEE European Conference on Computer Vision, ECCV, 2018
The Role of Minimal Complexity in Unsupervised Learning of Semantic Mappings
T. Galanti, L. Wolf, S. Benaim
International Conference on Learning Representations, ICLR, 2018
A Theoretical Framework for Deep Transfer Learning
T. Galanti, T. Hazan, L. Wolf
Information and Inference: A Journal of the IMA, IMAIAI, 2016