Tomer Galanti - RankMe

61 papers A* 11A 1C 1Journal 38Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Directional Neural Collapse Explains Few-Shot Transfer in Self-Supervised Learning. CoRR Achleshwar Luthra, Yash Salunkhe, Tomer Galanti
2026	J	`jnl`	Tool Building as a Path to "Superintelligence". CoRR David Koplow, Tomer Galanti, Tomaso A. Poggio
2025	—	`conf`	Centered Self-attention Layers. SCIA (1) Ameen Ali, Tomer Galanti, Lior Wolf
2025	J	`jnl`	DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization. CoRR Gang Li, Ming Lin, Tomer Galanti, Zhengzhong Tu, Tianbao Yang
2025	A*	`conf`	Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference. ICLR Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg, Moshe Wasserblat, Tomer Galanti, Michal Gordon-Kiwkowitz, David Harel
2025	A*	`conf`	Formation of Representations in Neural Networks. ICLR Liu Ziyin, Isaac L. Chuang, Tomer Galanti, Tomaso A. Poggio
2025	J	`jnl`	LLM-ERM: Sample-Efficient Program Learning via LLM-Guided Search. CoRR Shivam Singhal, Eran Malach, Tomaso A. Poggio, Tomer Galanti
2025	J	`jnl`	On the Alignment Between Supervised and Self-Supervised Contrastive Learning. CoRR Achleshwar Luthra, Priyadarsi Mishra, Tomer Galanti
2025	—	`conf`	SGD with Weight Decay Secretly Minimizes the Ranks of Your Neural Networks. CPAL Tomer Galanti, Zachary S. Siegel, Aparna Gupte, Tomaso A. Poggio
2025	J	`jnl`	Scalable Principal-Agent Contract Design via Gradient-Based Optimization. CoRR Tomer Galanti, Aarya Bookseller, Korok Ray
2025	J	`jnl`	Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning. CoRR Achleshwar Luthra, Tianbao Yang, Tomer Galanti
2024	—	`conf`	Distributed Speculative Inference of Large Language Models is Provably Faster. ENLSP Nadav Timor, Jonathan Mamou, Oren Pereg, Moshe Berchansky, Daniel Korat, Moshe Wasserblat, Tomer Galanti, Michal Gordon, David Harel
2024	J	`jnl`	Distributed Speculative Inference of Large Language Models. CoRR Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg, Moshe Wasserblat, Tomer Galanti, Michal Gordon, David Harel
2024	J	`jnl`	Formation of Representations in Neural Networks. CoRR Liu Ziyin, Isaac L. Chuang, Tomer Galanti, Tomaso A. Poggio
2024	A*	`conf`	On the Power of Decision Trees in Auto-Regressive Language Modeling. NeurIPS Yulu Gan, Tomer Galanti, Tomaso A. Poggio, Eran Malach
2024	J	`jnl`	On the Power of Decision Trees in Auto-Regressive Language Modeling. CoRR Yulu Gan, Tomer Galanti, Tomaso A. Poggio, Eran Malach
2024	J	`jnl`	The Fair Language Model Paradox. CoRR Andrea Pinto, Tomer Galanti, Randall Balestriero
2023	J	`jnl`	Centered Self-Attention Layers. CoRR Ameen Ali, Tomer Galanti, Lior Wolf
2023	J	`jnl`	Comparative Generalization Bounds for Deep Neural Networks. Trans. Mach. Learn. Res. Tomer Galanti, Liane Galanti, Ido Ben-Shaul
2023	J	`jnl`	Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions. CoRR Ido Ben-Shaul, Tomer Galanti, Shai Dekel
2023	J	`jnl`	Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions. Trans. Mach. Learn. Res. Ido Ben-Shaul, Tomer Galanti, Shai Dekel
2023	A*	`conf`	Feature learning in deep classifiers through Intermediate Neural Collapse. ICML Akshay Rangamani, Marius Lindegaard, Tomer Galanti, Tomaso A. Poggio
2023	J	`jnl`	Norm-based Generalization Bounds for Compositionally Sparse Neural Networks. CoRR Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio
2023	A*	`conf`	Norm-based Generalization Bounds for Sparse Neural Networks. NeurIPS Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio
2023	A*	`conf`	Reverse Engineering Self-Supervised Learning. NeurIPS Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun
2023	J	`jnl`	Reverse Engineering Self-Supervised Learning. CoRR Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun
2023	J	`jnl`	The Probabilistic Stability of Stochastic Gradient Descent. CoRR Liu Ziyin, Botao Li, Tomer Galanti, Masahito Ueda
2022	J	`jnl`	A Note on the Implicit Bias Towards Minimal Depth of Deep Neural Networks. CoRR Tomer Galanti
2022	J	`jnl`	Generalization Bounds for Transfer Learning with Pretrained Classifiers. CoRR Tomer Galanti, András György, Marcus Hutter
2022	—	`conf`	Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models. ECCV (37) Chenfeng Xu, Shijia Yang, Tomer Galanti, Bichen Wu, Xiangyu Yue, Bohan Zhai, Wei Zhan, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka
2022	A*	`conf`	On the Role of Neural Collapse in Transfer Learning. ICLR Tomer Galanti, András György, Marcus Hutter
2022	J	`jnl`	SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks. CoRR Tomer Galanti, Tomaso A. Poggio
2022	—	`conf`	Weakly Supervised Discovery of Semantic Attributes. CLeaR Ameen Ali, Tomer Galanti, Evgenii Zheltonozhskii, Chaim Baskin, Lior Wolf
2021	J	`jnl`	Evaluation Metrics for Conditional Image Generation. Int. J. Comput. Vis. Yaniv Benny, Tomer Galanti, Sagie Benaim, Lior Wolf
2021	J	`jnl`	Intersection Regularization for Extracting Semantic Attributes. CoRR Ameen Ali, Tomer Galanti, Evgeniy Zheltonozhskiy, Chaim Baskin, Lior Wolf
2021	A*	`conf`	Meta Internal Learning. NeurIPS Raphael Bensadoun, Shir Gur, Tomer Galanti, Lior Wolf
2021	J	`jnl`	Meta Internal Learning. CoRR Raphael Bensadoun, Shir Gur, Tomer Galanti, Lior Wolf
2021	A	`conf`	On random kernels of residual architectures. UAI Etai Littwin, Tomer Galanti, Lior Wolf
2021	—	`—`	On the Emergence of Semantic Structure in Deep Learning Tomer Galanti
2021	J	`jnl`	On the Role of Neural Collapse in Transfer Learning. CoRR Tomer Galanti, András György, Marcus Hutter
2021	J	`jnl`	Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs. J. Mach. Learn. Res. Tomer Galanti, Sagie Benaim, Lior Wolf
2020	J	`jnl`	A Critical View of the Structural Causal Model. CoRR Tomer Galanti, Ofir Nabati, Lior Wolf
2020	J	`jnl`	A Formal Approach to Explainability. CoRR Lior Wolf, Tomer Galanti, Tamir Hazan
2020	J	`jnl`	Comparing the Parameter Complexity of Hypernetworks and the Embedding-Based Alternative. CoRR Tomer Galanti, Lior Wolf
2020	J	`jnl`	Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer. CoRR Ori Press, Tomer Galanti, Sagie Benaim, Lior Wolf
2020	J	`jnl`	Evaluation Metrics for Conditional Image Generation. CoRR Yaniv Benny, Tomer Galanti, Sagie Benaim, Lior Wolf
2020	A*	`conf`	On Infinite-Width Hypernetworks. NeurIPS Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang
2020	A*	`conf`	On the Modularity of Hypernetworks. NeurIPS Tomer Galanti, Lior Wolf
2020	J	`jnl`	On the Optimization Dynamics of Wide Hypernetworks. CoRR Etai Littwin, Tomer Galanti, Lior Wolf
2020	J	`jnl`	Unsupervised Learning of the Set of Local Maxima. CoRR Lior Wolf, Sagie Benaim, Tomer Galanti
2019	C	`conf`	A Formal Approach to Explainability. AIES Lior Wolf, Tomer Galanti, Tamir Hazan
2019	A*	`conf`	Domain Intersection and Domain Difference. ICCV Sagie Benaim, Michael Khaitov, Tomer Galanti, Lior Wolf
2019	J	`jnl`	Domain Intersection and Domain Difference. CoRR Sagie Benaim, Michael Khaitov, Tomer Galanti, Lior Wolf
2019	—	`conf`	Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer. ICLR (Poster) Ori Press, Tomer Galanti, Sagie Benaim, Lior Wolf
2019	—	`conf`	Unsupervised Learning of the Set of Local Maxima. ICLR (Poster) Lior Wolf, Sagie Benaim, Tomer Galanti
2018	—	`conf`	Estimating the Success of Unsupervised Image to Image Translation. ECCV (5) Sagie Benaim, Tomer Galanti, Lior Wolf
2018	J	`jnl`	Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs. CoRR Tomer Galanti, Sagie Benaim, Lior Wolf
2018	—	`conf`	The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings. ICLR (Poster) Tomer Galanti, Lior Wolf, Sagie Benaim
2017	J	`jnl`	A Theory of Output-Side Unsupervised Domain Adaptation. CoRR Tomer Galanti, Lior Wolf
2017	J	`jnl`	Maximally Distant Cross Domain Generators for Estimating Per-Sample Error. CoRR Sagie Benaim, Tomer Galanti, Lior Wolf
2017	J	`jnl`	Unsupervised Learning of Semantic Mappings. CoRR Tomer Galanti, Lior Wolf