Name
Affiliation
Papers
AMIR GLOBERSON
School of Computer Science and Engineering and The Interdisciplinary Center for Neural Computation, The Hebrew University, Jerusalem 91904, Israel
100
Collaborators
Citations 
PageRank 
140
1515
117.72
Referers 
Referees 
References 
2514
1658
1160
Search Limit
1001000
Title
Citations
PageRank
Year
Object-Region Video Transformers00.342022
DETReg: Unsupervised Pretraining with Region Priors for Object Detection00.342022
On the inductive bias of neural networks for learning read-once DNFs.00.342022
Learning to Retrieve Passages without Supervision00.342022
Efficient Learning of CNNs using Patch Based Features.00.342022
Active learning with label comparisons.00.342022
On the Implicit Bias of Gradient Descent for Temporal Extrapolation00.342022
Compositional Video Synthesis With Action Graphs00.342021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace00.342021
On The Implicit Bias Of Initialization Shape: Beyond Infinitesimal Mirror Descent00.342021
An optimization and generalization analysis for max-pooling networks.00.342021
Towards Understanding Learning in Neural Networks with Linear Teachers00.342021
Optimal Strategies Against Generative Attacks00.342020
A Simple and Effective Model for Answering Multi-span Questions.00.342020
Regularizing Towards Permutation Invariance In Recurrent Models00.342020
Pre-training Mention Representations in Coreference Models.00.342020
Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing.10.352019
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem10.342019
Learning Latent Scene-Graph Representations for Referring Relationships.00.342019
Classifying Collisions with Spatio-Temporal Action Graph Networks.20.382018
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction.10.352018
Learning to Optimize Combinatorial Functions.10.362018
Over-parameterization Improves Generalization in the XOR Detection Problem.00.342018
Explaining Queries over Web Tables to Non-Experts.00.342018
Learning with Rules.00.342018
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction.100.502018
Weakly Supervised Semantic Parsing with Abstract Examples.50.422018
Learning Infinite Layer Networks Without the Kernel Trick.00.342017
Robust Conditional Probabilities.00.342017
SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data.310.862017
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs.541.712017
Effective Semisupervised Learning on Manifolds.00.342017
Learning and Inference with Expectations.00.342017
Discriminative Learning of Infection Models.10.352016
Improper Deep Kernels.30.392016
Optimal Tagging with Markov Chain Optimization.30.382016
Learning to generalize to new compositions in image understanding.60.452016
Learning Infinite-Layer Networks: Beyond the Kernel Trick.00.342016
Collective Entity Resolution With Multi-Focal Attention140.562016
Template Kernels for Dependency Parsing.30.422015
How Hard is Inference for Structured Prediction?50.402015
Efficient Lifting of MAP LP Relaxations Using k-Locality.90.512014
Lifted Message Passing As Reparametrization Of Graphical Models60.442014
Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment.80.472014
Discrete Chebyshev Classifiers.50.512014
Inferning with High Girth Graphical Models.30.472014
Tightness Results For Local Consistency Relaxations In Continuous Mrfs20.372014
Spectral Regularization for Max-Margin Sequence Tagging.60.442014
Steps To Excellence: Simple Inference With Refined Scoring Of Dependency Trees00.342014
Learning Structured Models with the AUC Loss and Its Generalizations.110.532014
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