Amnon Shashua

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 53

Top Venues

CoRR

ICLR

ICLR (Poster)

ICML

Publications

Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham
Generating Benchmarks for Factuality Evaluation of Language Models. EACL (1) (2024)
Yotam Wolf, Noam Wies, Dorin Shteyman, Binyamin Rothberg, Yoav Levine, Amnon Shashua
Tradeoffs Between Alignment and Helpfulness in Language Models. CoRR (2024)
Eliya Segev, Maya Alroy, Ronen Katsir, Noam Wies, Ayana Shenhav, Yael Ben-Oren, David Zar, Oren Tadmor, Jacob Bitterman, Amnon Shashua, Tal Rosenwein
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework. ICLR (2024)
Noam Wies, Yoav Levine, Amnon Shashua
Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks. ICLR (2023)
Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham
Generating Benchmarks for Factuality Evaluation of Language Models. CoRR (2023)
Noam Wies, Yoav Levine, Amnon Shashua
The Learnability of In-Context Learning. NeurIPS (2023)
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
In-Context Retrieval-Augmented Language Models. CoRR (2023)
Yotam Wolf, Noam Wies, Yoav Levine, Amnon Shashua
Fundamental Limitations of Alignment in Large Language Models. CoRR (2023)
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
In-Context Retrieval-Augmented Language Models. Trans. Assoc. Comput. Linguistics 11 (2023)
Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Inbal Magar, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
Parallel Context Windows for Large Language Models. ACL (1) (2023)
Noam Wies, Yoav Levine, Amnon Shashua
The Learnability of In-Context Learning. CoRR (2023)
Eliya Segev, Maya Alroy, Ronen Katsir, Noam Wies, Ayana Shenhav, Yael Ben-Oren, David Zar, Oren Tadmor, Jacob Bitterman, Amnon Shashua, Tal Rosenwein
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework. CoRR (2023)
Yoav Levine, Itay Dalmedigos, Ori Ram, Yoel Zeldes, Daniel Jannai, Dor Muhlgay, Yoni Osin, Opher Lieber, Barak Lenz, Shai Shalev-Shwartz, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
Standing on the Shoulders of Giant Frozen Language Models. CoRR (2022)
Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design. ICLR (2022)
Ehud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, Dor Muhlgay, Noam Rozen, Erez Schwartz, Gal Shachaf, Shai Shalev-Shwartz, Amnon Shashua, Moshe Tennenholtz
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning. CoRR (2022)
Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
Parallel Context Windows Improve In-Context Learning of Large Language Models. CoRR (2022)
Noam Wies, Yoav Levine, Amnon Shashua
Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks. CoRR (2022)
Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design. CoRR (2021)
Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention. ICML (2021)
Or Sharir, Amnon Shashua, Giuseppe Carleo
Neural tensor contractions and the expressive power of deep neural quantum states. CoRR (2021)
Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention. CoRR (2021)
Shai Shalev-Shwartz, Shaked Shammah, Amnon Shashua
On the Ethics of Building AI in a Responsible Manner. CoRR (2020)
Yoav Levine, Noam Wies, Or Sharir, Hofit Bata, Amnon Shashua
Limits to Depth Efficiencies of Self-Attention. NeurIPS (2020)
Yoav Levine, Barak Lenz, Or Dagan, Ori Ram, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, Yoav Shoham
SenseBERT: Driving Some Sense into BERT. ACL (2020)
Yoav Levine, Noam Wies, Or Sharir, Hofit Bata, Amnon Shashua
Limits to Depth Efficiencies of Self-Attention. CoRR (2020)
Shai Shalev-Shwartz, Shaked Shammah, Amnon Shashua
Vision Zero: on a Provable Method for Eliminating Roadway Accidents without Compromising Traffic Throughput. CoRR (2019)
Yoav Levine, Barak Lenz, Or Dagan, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, Yoav Shoham
SenseBERT: Driving Some Sense into BERT. CoRR (2019)
Or Sharir, Yoav Levine, Noam Wies, Giuseppe Carleo, Amnon Shashua
Deep autoregressive models for the efficient variational simulation of many-body quantum systems. CoRR (2019)
Nadav Cohen, Ronen Tamari, Amnon Shashua
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions. ICLR (2018)
Or Sharir, Amnon Shashua
On the Expressive Power of Overlapping Architectures of Deep Learning. ICLR (Poster) (2018)
Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. ICLR (Poster) (2018)
Yoav Levine, Or Sharir, Amnon Shashua
Benefits of Depth for Long-Term Memory of Recurrent Networks. ICLR (Workshop) (2018)
Or Sharir, Amnon Shashua
Sum-Product-Quotient Networks. AISTATS (2018)
Yoav Levine, Or Sharir, Nadav Cohen, Amnon Shashua
Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks. CoRR (2018)
Shai Shalev-Shwartz, Shaked Shammah, Amnon Shashua
On a Formal Model of Safe and Scalable Self-driving Cars. CoRR (2017)
Nadav Cohen, Amnon Shashua
Inductive Bias of Deep Convolutional Networks through Pooling Geometry. ICLR (Poster) (2017)
Nadav Cohen, Or Sharir, Yoav Levine, Ronen Tamari, David Yakira, Amnon Shashua
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions. CoRR (2017)
Yoav Levine, Or Sharir, Amnon Shashua
Benefits of Depth for Long-Term Memory of Recurrent Networks. CoRR (2017)
Or Sharir, Amnon Shashua
Sum-Product-Quotient Networks. CoRR (2017)
Nadav Cohen, Ronen Tamari, Amnon Shashua
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions. CoRR (2017)
Or Sharir, Amnon Shashua
On the Expressive Power of Overlapping Operations of Deep Networks. CoRR (2017)
Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. CoRR (2017)
Shai Shalev-Shwartz, Shaked Shammah, Amnon Shashua
Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving. CoRR (2016)
Shai Shalev-Shwartz, Amnon Shashua
On the Sample Complexity of End-to-end Training vs. Semantic Abstraction Training. CoRR (2016)
Nadav Cohen, Amnon Shashua
Inductive Bias of Deep Convolutional Networks through Pooling Geometry. CoRR (2016)
Oren Tadmor, Yonatan Wexler, Tal Rosenwein, Shai Shalev-Shwartz, Amnon Shashua
Learning a Metric Embedding for Face Recognition using the Multibatch Method. CoRR (2016)
Nadav Cohen, Or Sharir, Amnon Shashua
Deep SimNets. CVPR (2016)
Shai Shalev-Shwartz, Nir Ben-Zrihem, Aviad Cohen, Amnon Shashua
Long-term Planning by Short-term Prediction. CoRR (2016)
Nadav Cohen, Or Sharir, Amnon Shashua
On the Expressive Power of Deep Learning: A Tensor Analysis. COLT (2016)
Nadav Cohen, Amnon Shashua
Convolutional Rectifier Networks as Generalized Tensor Decompositions. CoRR (2016)
Oren Tadmor, Tal Rosenwein, Shai Shalev-Shwartz, Yonatan Wexler, Amnon Shashua
Learning a Metric Embedding for Face Recognition using the Multibatch Method. NIPS (2016)
Nadav Cohen, Amnon Shashua
Convolutional Rectifier Networks as Generalized Tensor Decompositions. ICML (2016)
Or Sharir, Ronen Tamari, Nadav Cohen, Amnon Shashua
Tensorial Mixture Models. CoRR (2016)
Nadav Cohen, Or Sharir, Amnon Shashua
Deep SimNets. CoRR (2015)
Nadav Cohen, Or Sharir, Amnon Shashua
On the Expressive Power of Deep Learning: A Tensor Analysis. CoRR (2015)
Nadav Cohen, Amnon Shashua
SimNets: A Generalization of Convolutional Networks. CoRR (2014)
Tamir Hazan, Jian Peng, Amnon Shashua
Tightening Fractional Covering Upper Bounds on the Partition Function for High-Order Region Graphs. UAI (2012)
Tamir Hazan, Amnon Shashua
Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies CoRR (2012)
Tamir Hazan, Jian Peng, Amnon Shashua
Tightening Fractional Covering Upper Bounds on the Partition Function for High-Order Region Graphs CoRR (2012)
Shai Shalev-Shwartz, Yonatan Wexler, Amnon Shashua
ShareBoost: Efficient Multiclass Learning with Feature Sharing CoRR (2011)
Shai Shalev-Shwartz, Yonatan Wexler, Amnon Shashua
ShareBoost: Efficient multiclass learning with feature sharing. NIPS (2011)
Tamir Hazan, Amnon Shashua
Norm-Product Belief Propagation: Primal-Dual Message-Passing for Approximate Inference. IEEE Trans. Inf. Theory 56 (12) (2010)
Simon Polak, Amnon Shashua
The Semi-explicit Shape Model for Multi-object Detection and Classification. ECCV (2) (2010)
Amnon Shashua, Gabi Pragier
The Latent Bernoulli-Gauss Model for Data Analysis CoRR (2010)
Gideon P. Stein, Yoram Gdalyahu, Amnon Shashua
Stereo-Assist: Top-down stereo for driver assistance systems. Intelligent Vehicles Symposium (2010)
Amnon Shashua
Introduction to Machine Learning: Class Notes 67577 CoRR (2009)
Tamir Hazan, Amnon Shashua
Norm-Product Belief Propagation: Primal-Dual Message-Passing for Approximate Inference CoRR (2009)
Ron Zass, Amnon Shashua
Probabilistic graph and hypergraph matching. CVPR (2008)
Tamir Hazan, Amnon Shashua
Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies. UAI (2008)
Tamir Hazan, Amit Man, Amnon Shashua
A Parallel Decomposition Solver for SVM: Distributed dual ascend using Fenchel Duality. CVPR (2008)
Tamir Hazan, Roee Hardoon, Amnon Shashua
pLSA for Sparse Arrays With Tsallis Pseudo-Additive Divergence: Noise Robustness and Algorithm. ICCV (2007)
Simon Polak, Amnon Shashua
Latent Model Clustering and Applications to Visual Recognition. ICCV (2007)
Ron Zass, Amnon Shashua
Doubly Stochastic Normalization for Spectral Clustering. NIPS (2006)
Amnon Shashua, Ron Zass, Tamir Hazan
Multi-way Clustering Using Super-Symmetric Non-negative Tensor Factorization. ECCV (4) (2006)
Yaniv Alon, Andras Ferencz, Amnon Shashua
Off-road Path Following using Region Classification and Geometric Projection Constraints. CVPR (1) (2006)
Ron Zass, Amnon Shashua
Nonnegative Sparse PCA. NIPS (2006)
Richard Mason, Jim Radford, Deepak Kumar, Robert Walters, Brian Fulkerson, Eagle Jones, David Caldwell, Jason Meltzer, Yaniv Alon, Amnon Shashua, Hiroshi Hattori, Emilio Frazzoli, Stefano Soatto
The Golem Group/University of California at Los Angeles autonomous ground vehicle in the DARPA grand challenge. J. Field Robotics 23 (8) (2006)
Gideon P. Stein, Elchanan Rushinek, Gaby Hayun, Amnon Shashua
A Computer Vision System on a Chip: a case study from the automotive domain. CVPR Workshops (2005)
Ron Zass, Amnon Shashua
A Unifying Approach to Hard and Probabilistic Clustering. ICCV (2005)
Tamir Hazan, Simon Polak, Amnon Shashua
Sparse Image Coding Using a 3D Non-Negative Tensor Factorization. ICCV (2005)
Amnon Shashua, Tamir Hazan
Non-negative tensor factorization with applications to statistics and computer vision. ICML (2005)
Lior Wolf, Amnon Shashua
Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach. J. Mach. Learn. Res. 6 (2005)
Amnon Shashua, Tamir Hazan
Algebraic Set Kernels with Application to Inference Over Local Image Representations. NIPS (2004)
Jeremy Yermiyahou Kaminski, Amnon Shashua
Multiple View Geometry of General Algebraic Curves. Int. J. Comput. Vis. 56 (3) (2004)
Amnon Shashua, Lior Wolf
Kernel Feature Selection with Side Data Using a Spectral Approach. ECCV (3) (2004)
Lior Wolf, Amnon Shashua
Learning over Sets using Kernel Principal Angles. J. Mach. Learn. Res. 4 (2003)
Lior Wolf, Amnon Shashua
Kernel Principal Angles for Classification Machines with Applications to Image Sequence Interpretation. CVPR (1) (2003)
Lior Wolf, Amnon Shashua
Feature Selection for Unsupervised and Supervised Inference: the Emergence of Sparsity in a Weighted-based Approach. ICCV (2003)
Amnon Shashua, Anat Levin, Shai Avidan
Manifold Pursuit: A New Approach to Appearance Based Recognition. ICPR (3) (2002)
Anat Levin, Amnon Shashua
Revisiting Single-View Shape Tensors: Theory and Applications. ECCV (2) (2002)
Lior Wolf, Amnon Shashua
k=3, ..., 6, and their Applications in Computer Vision. Int. J. Comput. Vis. 48 (1) (2002)
Anat Levin, Amnon Shashua
Principal Component Analysis over Continuous Subspaces and Intersection of Half-Spaces. ECCV (3) (2002)
Amnon Shashua, Anat Levin
Ranking with Large Margin Principle: Two Approaches. NIPS (2002)
Kiriakos N. Kutulakos, Amnon Shashua
Guest Editorial. Int. J. Comput. Vis. 49 (2-3) (2002)
Anat Levin, Lior Wolf, Amnon Shashua
Time-varying Shape Tensors for Scenes with Multiply Moving Points. CVPR (1) (2001)
Amnon Shashua, Anat Levin
Linear Image Coding for Regression and Classification using the Tensor-rank Principle. CVPR (1) (2001)
Lior Wolf, Amnon Shashua
Two-body Segmentation from Two Perspective Views. CVPR (1) (2001)
Lior Wolf, Amnon Shashua
On Projection Matrices and their Applications in Computer Vision. ICCV (2001)
Jeremy Yermiyahou Kaminski, Michael Fryers, Amnon Shashua, Mina Teicher
Multiple View Geometry of Non-planar Algebraic Curves. ICCV (2001)
Amnon Shashua, Yonatan Wexler
Q-Warping: Direct Computation of Quadratic Reference Surfaces. IEEE Trans. Pattern Anal. Mach. Intell. 23 (8) (2001)

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Publication Activity (10 Years)

Top Topics

Top Venues

Amnon Shashua