A. Globerson

发表

SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data pdf

Shai Shalev-Shwartz, Amir Globerson, Eran Malach, 2017, ICLR.

Nightmare at test time: robust learning by feature deletion

Amir Globerson, Sam T. Roweis, S. Roweis, 2006, ICML.

Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks

Peter L. Bartlett, Xavier Carreras, Michael Collins, 2008, J. Mach. Learn. Res..

Past-future information bottleneck in dynamical systems.

Naftali Tishby, A. Globerson, F. Creutzig, 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

Approximate inference using planar graph decomposition

Tommi S. Jaakkola, Amir Globerson, T. Jaakkola, 2006, NIPS.

Metric Learning by Collapsing Classes

Amir Globerson, Sam T. Roweis, S. Roweis, 2005, NIPS.

Euclidean Embedding of Co-occurrence Data

Gal Chechik, Naftali Tishby, Amir Globerson, 2004, J. Mach. Learn. Res..

Draft version for NIPS 2004 Euclidean Embedding of Co-occurrence Data

Naftali Tishby, A. Globerson, Fernando C Pereira, 2022 .

Clusters and Coarse Partitions in LP Relaxations

Tommi S. Jaakkola, Amir Globerson, David Sontag, 2008, NIPS.

Learning Efficiently with Approximate Inference via Dual Losses

Tommi S. Jaakkola, Ofer Meshi, Amir Globerson, 2010, ICML.

Convergent Propagation Algorithms via Oriented Trees

Tommi S. Jaakkola, Amir Globerson, T. Jaakkola, 2007, UAI.

Convergence Rate Analysis of MAP Coordinate Minimization Algorithms

Tommi S. Jaakkola, Ofer Meshi, Amir Globerson, 2012, NIPS.

Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations

Tommi S. Jaakkola, Amir Globerson, T. Jaakkola, 2007, NIPS.

Distributed Latent Variable Models of Lexical Co-occurrences

John Blitzer, Amir Globerson, Fernando Pereira, 2005, AISTATS.

Information Bottleneck for Gaussian Variables

Gal Chechik, Naftali Tishby, Amir Globerson, 2003, J. Mach. Learn. Res..

Convex Learning with Invariances

Alexander J. Smola, Choon Hui Teo, Amir Globerson, 2007, NIPS.

Sufficient Dimensionality Reduction - A novel Analysis Method

Naftali Tishby, Amir Globerson, Naftali Tishby, 2002, ICML.

Convergent message passing algorithms - a unifying view

Amir Globerson, Yair Weiss, Talya Meltzer, 2009, UAI.

Sufficient Dimensionality Reduction

Naftali Tishby, Amir Globerson, Naftali Tishby, 2003, J. Mach. Learn. Res..

An Adversarial View of Covariate Shift and A Minimax Approach

S. Roweis, Alex Smola, A. Globerson, 2009 .

Introduction to dual composition for inference

Tommi S. Jaakkola, Amir Globerson, David Sontag, 2011 .

How Hard is Inference for Structured Prediction?

Tim Roughgarden, Amir Globerson, David Sontag, 2015, ICML.

Structured Prediction Models via the Matrix-Tree Theorem

Xavier Carreras, Michael Collins, Amir Globerson, 2007, EMNLP.

Reinforcement Learning-Policy Gradient Methods

A. Globerson, 2017 .

Learning Canonical Representations for Scene Graph to Image Generation

Trevor Darrell, Gal Chechik, Amir Globerson, 2019, ECCV.

UvA-DARE Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias

J. Mooij, A. Globerson, R. Silva, 2019 .

Effective Semi-supervised Learning on Manifolds

S. Shalev-Shwartz, A. Globerson, 2017 .

Selective Sharing for Multilingual Dependency Parsing Citation

R. Barzilay, A. Globerson, Tahira Naseem, 2012 .

Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders

A. Globerson, R. Silva, 2018 .

UvA-DARE (Digital Academic Repository) From Deterministic ODEs to Dynamic Structural Causal Models

A. Globerson, R. Silva, 2018 .

Learning Object Permanence from Video pdf

Gal Chechik, Amir Globerson, Aviv Shamsian, 2020, ECCV.

Evidence-based roads to the promotion of health in old age

A. Globerson, A. Reznick, P. Ljubuncic, 2008, The journal of nutrition, health & aging.

Effective Semisupervised Learning on Manifolds

Roi Livni, Shai Shalev-Shwartz, Amir Globerson, 2017, COLT.

Learning and Inference with Expectations

Amir Globerson, A. Globerson, 2017, UAI.

On the Optimization Landscape of Maximum Mean Discrepancy pdf

Ami Wiesel, Alon Itai, Amir Globerson, 2021, ArXiv.

Label Propagation Networks

Amir Globerson, Kojin Oshiba, Nir Rosenfeld, 2018 .

The Minimum Information Principlein Learning and Neural DataAnalysis

Amir Globerson, A. Globerson, 2005 .

Correction for: The minimum information principle and its application to neural code analysis, by Amir Globerson, et al

Naftali Tishby, Amir Globerson, Eran Stark, 2009 .

Learning to Retrieve Passages without Supervision

Omer Levy, A. Globerson, Jonathan Berant, 2021, NAACL.

DETReg: Unsupervised Pretraining with Region Priors for Object Detection

Trevor Darrell, A. Globerson, Gal Chechik, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens

Trevor Darrell, A. Globerson, Anna Rohrbach, 2022, ArXiv.

Graph Trees with Attention

Ran Gilad-Bachrach, A. Globerson, Maya Bechler-Speicher, 2022, ArXiv.

Graph Trees with Attention

Ran Gilad-Bachrach, A. Globerson, Maya Bechler-Speicher, 2022, ArXiv.

Visual Prompting via Image Inpainting

Alexei A. Efros, Trevor Darrell, A. Globerson, 2022, NeurIPS.

On the inductive bias of neural networks for learning read-once DNFs

Alon Brutzkus, A. Globerson, I. Bronstein, 2022, UAI.

Active Learning with Label Comparisons

A. Globerson, G. Elidan, S. Moran, 2022, UAI.

Active Learning with Label Comparisons: Supplementary Material

A. Globerson, G. Elidan, S. Moran, 2022 .

Text-Only Training for Image Captioning using Noise-Injected CLIP

A. Globerson, David Nukrai, R. Mokady, 2022, EMNLP.

Object-Region Video Transformers

Trevor Darrell, A. Globerson, Gal Chechik, 2021, Computer Vision and Pattern Recognition.

Efficient Learning of CNNs using Patch Based Features

S. Shalev-Shwartz, Alon Brutzkus, A. Globerson, 2022, ICML.

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network

A. Globerson, R. Giryes, Nadav Cohen, 2022, ArXiv.

Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens

Trevor Darrell, A. Globerson, Anna Rohrbach, 2022, 2206.06346.

What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary

A. Globerson, Jonathan Berant, Ori Ram, 2022, ArXiv.

PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data

Trevor Darrell, Ariel Shamir, A. Globerson, 2022, ArXiv.

Lifted Message Passing as Reparametrization of Graphical Models

Kristian Kersting, Amir Globerson, Martin Mladenov, 2014, UAI.

Efficient Lifting of MAP LP Relaxations Using k-Locality

Kristian Kersting, Amir Globerson, Martin Mladenov, 2014, AISTATS.

On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent

Nathan Srebro, Daniel Soudry, Amir Globerson, 2021, ICML.

Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs pdf

Amir Globerson, Alon Brutzkus, Alon Brutzkus, 2017, ICML.

BERTese: Learning to Speak to BERT

A. Globerson, Jonathan Berant, Adi Haviv, 2021, EACL.

Rich cell-type-specific network topology in neocortical microcircuitry

Henry Markram, Idan Segev, Eilif Muller, 2017, Nature Neuroscience.

Decision Trees with Dynamic Graph Features

Ran Gilad-Bachrach, A. Globerson, Maya Bechler-Speicher, 2022, 2207.02760.

Tight Error Bounds for Structured Prediction pdf

Tim Roughgarden, Amir Globerson, David Sontag, 2014, ArXiv.

Learning the Rules

Amit Daniely, Amir Globerson, Deborah Cohen, 1999, Science.

Tightening LP Relaxations for MAP using Message Passing

Tommi S. Jaakkola, Amir Globerson, Yair Weiss, 2008, UAI.

Gaussian Information Bottleneck 1 Information Bottleneck for Gaussian Variables

Gal Chechik, Amir Globerson, A. Globerson, 2022 .

Towards Understanding Learning in Neural Networks with Linear Teachers pdf

Amir Globerson, Alon Brutzkus, Roei Sarussi, 2021, ICML.

A Simple Geometric Interpretation of SVM using Stochastic Adversaries

Koby Crammer, Roi Livni, Amir Globerson, 2012, AISTATS.

Exponentiated gradient algorithms for log-linear structured prediction

Xavier Carreras, Michael Collins, Amir Globerson, 2007, ICML '07.

Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing

Regina Barzilay, Amir Globerson, Tal Schuster, 2019, NAACL.

Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction

Jonathan Berant, Gal Chechik, Amir Globerson, 2018, NeurIPS.

Learning Bayesian Network Structure using LP Relaxations

Tommi S. Jaakkola, Marina Meila, Amir Globerson, 2010, AISTATS.

Correlations between Groups of Premotor Neurons Carry Information about Prehension

Amir Globerson, Eran Stark, Itay Asher, 2008, The Journal of Neuroscience.

Learning to Optimize Combinatorial Functions

Eric Balkanski, Amir Globerson, Yaron Singer, 2018, ICML.

Classifying Collisions with Spatio-Temporal Action Graph Networks pdf

Trevor Darrell, Amir Globerson, Huijuan Xu, 2018, ArXiv.

Explaining in Style: Training a GAN to explain a classifier in StyleSpace pdf

Avinatan Hassidim, William T. Freeman, Michal Irani, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs

Trevor Darrell, A. Globerson, R. Feris, 2023, ArXiv.

Selective Sharing for Multilingual Dependency Parsing

Regina Barzilay, Amir Globerson, Tahira Naseem, 2012, ACL.

Spatio-Temporal Action Graph Networks

Trevor Darrell, Xiaolong Wang, Amir Globerson, 2018, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).

Weakly Supervised Semantic Parsing with Abstract Examples pdf

Jonathan Berant, Amir Globerson, Omer Goldman, 2017, ACL.

Compositional Video Synthesis with Action Graphs

Trevor Darrell, Gal Chechik, Xiaolong Wang, 2020, ICML.

LM vs LM: Detecting Factual Errors via Cross Examination

A. Globerson, Mor Geva, Roi Cohen, 2023, ArXiv.

Few-Shot Question Answering by Pretraining Span Selection

Omer Levy, A. Globerson, Jonathan Berant, 2021, ACL.

Dissecting Recall of Factual Associations in Auto-Regressive Language Models

A. Globerson, Katja Filippova, Mor Geva, 2023, ArXiv.

Crawling The Internal Knowledge-Base of Language Models

A. Globerson, Jonathan Berant, Mor Geva, 2023, FINDINGS.

Differentiable Scene Graphs

Jonathan Berant, Gal Chechik, Amir Globerson, 2019, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

Learning to generalize to new compositions in image understanding pdf

Jonathan Berant, Gal Chechik, Amir Globerson, 2016, ArXiv.

Maximin Optimization for Binary Regression

A. Globerson, A. Wiesel, Nisan Chiprut, 2020, ArXiv.

PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data

Trevor Darrell, Ariel Shamir, A. Globerson, 2022, 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary

A. Globerson, Jonathan Berant, Ori Ram, 2022, ACL.

Learning Object Detection from Captions via Textual Scene Attributes pdf

Jonathan Berant, Gal Chechik, Amir Globerson, 2020, ArXiv.

Sufficient Dimensionality Reduction with Irrelevance Statistics

Gal Chechik, Naftali Tishby, Amir Globerson, 2002, UAI.

On the Inductive Bias of a CNN for Orthogonal Patterns Distributions

Alon Brutzkus, A. Globerson, 2020, ArXiv.

An optimization and generalization analysis for max-pooling networks

Alon Brutzkus, A. Globerson, 2021, UAI.

Vanishing Component Analysis

Roi Livni, Shai Shalev-Shwartz, Amir Globerson, 2013, ICML.

Approximate inference using conditional entropy decompositions

Tommi S. Jaakkola, Amir Globerson, T. Jaakkola, 2007, AISTATS.

An Alternating Direction Method for Dual MAP LP Relaxation

Ofer Meshi, Amir Globerson, A. Globerson, 2011, ECML/PKDD.

Correction for Globerson et al., The minimum information principle and its application to neural code analysis

Naftali Tishby, A. Globerson, E. Stark, 2009, Proceedings of the National Academy of Sciences.

The minimum information principle and its application to neural code analysis

Naftali Tishby, Amir Globerson, Eran Stark, 2009, Proceedings of the National Academy of Sciences.

Learning Object Permanence from Video

A. Globerson, Gal Chechik, Aviv Shamsian, 2020, ECCV.

DETReg: Unsupervised Pretraining with Region Priors for Object Detection

Trevor Darrell, A. Globerson, Gal Chechik, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Coreference Resolution with Entity Equalization

Amir Globerson, Ben Kantor, A. Globerson, 2019, ACL.

A Simple and Effective Model for Answering Multi-span Questions

Jonathan Berant, Amir Globerson, Avia Efrat, 2019, EMNLP.

A Theoretical Analysis of Fine-tuning with Linear Teachers pdf

Amir Globerson, Alon Brutzkus, Gal Shachaf, 2021, NeurIPS.

Robust Conditional Probabilities

Amir Globerson, Yoav Wald, A. Globerson, 2017, NIPS.

An LP View of the M-best MAP problem

Amir Globerson, Menachem Fromer, A. Globerson, 2009, NIPS.

On the Implicit Bias of Gradient Descent for Temporal Extrapolation

Avichai Ben David, A. Globerson, Nadav Cohen, 2022, AISTATS.

Holdout SGD: Byzantine Tolerant Federated Learning.

Yehuda Afek, Amir Globerson, Tomer Koren, 2020, 2008.04612.

Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem

Amir Globerson, Alon Brutzkus, Alon Brutzkus, 2018, ICML.

Generalization to new compositions of known entities in image understanding

Jonathan Berant, Gal Chechik, Amir Globerson, 2017 .

Pre-training of Mention Representations in Coreference Models

Amir Globerson, Yuval Varkel, A. Globerson, 2020, EMNLP.

Quantification of Osteoclasts in Culture, Powered by Machine Learning

Y. Mansour, A. Globerson, Y. Gabet, 2021, Frontiers in Cell and Developmental Biology.

The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification

Ben Taskar, Michael Werman, Amir Globerson, 2013, ICML.

Gaussian Robust Classification pdf

Amir Globerson, Ido Ginodi, A. Globerson, 2011, ArXiv.

Learning Latent Scene-Graph Representations for Referring Relationships pdf

Jonathan Berant, Gal Chechik, Amir Globerson, 2019, ArXiv.

Explaining Queries Over Web Tables to Non-experts

Daniel Deutch, Tova Milo, Jonathan Berant, 2018, 2019 IEEE 35th International Conference on Data Engineering (ICDE).

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network

A. Globerson, R. Giryes, Nadav Cohen, 2022, International Conference on Learning Representations.

Regularizing Towards Permutation Invariance in Recurrent Models pdf

Amir Globerson, Edo Cohen-Karlik, Avichai Ben David, 2020, NeurIPS.

Discriminative Learning of Infection Models

Amir Globerson, Nir Rosenfeld, Mor Nitzan, 2016, WSDM.

Evaluating the Ripple Effects of Knowledge Editing in Language Models

A. Globerson, Mor Geva, Ori Yoran, 2023, TACL.

Covariance estimation in time varying ARMA processes

Ami Wiesel, Amir Globerson, A. Globerson, 2012, 2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM).

Time Varying Autoregressive Moving Average Models for Covariance Estimation

Ami Wiesel, Amir Globerson, Ofir Bibi, 2013, IEEE Transactions on Signal Processing.

Predict and Constrain: Modeling Cardinality in Deep Structured Prediction pdf

Amir Globerson, Nataly Brukhim, A. Globerson, 2018, ICML.

Correlations between Groups of Premotor Neurons Carry Information about Prehension

A. Globerson, E. Stark, M. Abeles, 2008, The Journal of Neuroscience.

Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway

Gal Chechik, Naftali Tishby, Amir Globerson, 2001, NIPS.

Rich cell-type-specific network topology in neocortical microcircuitry

Michael W. Reimann, Idan Segev, H. Markram, 2017, Nature Neuroscience.

Learning the Experts for Online Sequence Prediction pdf

Elad Eban, Shai Shalev-Shwartz, Amir Globerson, 2012, ICML.

The minimum information principle and its application to neural code analysis

Naftali Tishby, A. Globerson, E. Stark, 2009, Proceedings of the National Academy of Sciences.

Dissecting Recall of Factual Associations in Auto-Regressive Language Models

A. Globerson, Katja Filippova, Mor Geva, 2023, EMNLP.

Discrete Chebyshev Classifiers

Elad Eban, Amir Globerson, Elad Mezuman, 2014, ICML.

The Minimum Information Principle for Discriminative Learning pdf

Naftali Tishby, Amir Globerson, Naftali Tishby, 2004, UAI.

Predicting masked tokens in stochastic locations improves masked image modeling

Yann LeCun, Trevor Darrell, Nicolas Ballas, 2023, ArXiv.

LM vs LM: Detecting Factual Errors via Cross Examination

A. Globerson, Mor Geva, Roi Cohen, 2023, EMNLP.

Inferning with High Girth Graphical Models

Amir Globerson, Uri Heinemann, A. Globerson, 2014, ICML.

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets

A. Globerson, R. Giryes, Nadav Cohen, 2022, ICLR.

Tag-based Multi-Span Extraction in Reading Comprehension pdf

Jonathan Berant, Amir Globerson, Avia Efrat, 2019, ArXiv.

Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs

Trevor Darrell, A. Globerson, R. Feris, 2023, EMNLP.

Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees

Regina Barzilay, Tommi S. Jaakkola, Amir Globerson, 2014, ACL.

Embedding Heterogeneous Data Using Statistical Models

Gal Chechik, Naftali Tishby, Amir Globerson, 2006, AAAI.

Higher Order Matching for Consistent Multiple Target Tracking

Amir Globerson, Chetan Arora, A. Globerson, 2013, 2013 IEEE International Conference on Computer Vision.

Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens

Trevor Darrell, A. Globerson, Anna Rohrbach, 2022, NeurIPS.

Structured Video Tokens @ Ego4D PNR Temporal Localization Challenge 2022

Trevor Darrell, A. Globerson, Anna Rohrbach, 2022, ArXiv.

Learning Infinite-Layer Networks: Beyond the Kernel Trick pdf

Roi Livni, Amir Globerson, A. Globerson, 2016, ArXiv.

Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment

A. Globerson, G. Elidan, Reut Tsarfaty, 2023, ACL.

The More the Merrier: Parameter Learning for Graphical Models with Multiple MAPs

Franziska Meier, Fei Sha, Amir Globerson, 2013 .