Gal Chechik

According to our database, Gal Chechik authored at least 149 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Improved Generalization of Weight Space Networks via Augmentations.

Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron

CoRR, 2024

Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning.

Idan Achituve, Idit Diamant, Arnon Netzer, Gal Chechik, Ethan Fetaya

CoRR, 2024

Training-Free Consistent Text-to-Image Generation.

Yoad Tewel, Omri Kaduri, Rinon Gal, Yoni Kasten, Lior Wolf, Gal Chechik, Yuval Atzmon

CoRR, 2024

Late to the party? On-demand unlabeled personalized federated learning.

Ohad Amosy, Gal Eyal, Gal Chechik

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Generating Images of Rare Concepts Using Pre-trained Diffusion Models.

Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, Gal Chechik

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models.

Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or

ACM Trans. Graph., August, 2023

Fixed-point Inversion for Text-to-image diffusion models.

Barak Meiri, Dvir Samuel, Nir Darshan, Gal Chechik, Shai Avidan, Rami Ben-Ari

CoRR, 2023

Breathing Life Into Sketches Using Text-to-Video Priors.

Rinon Gal, Yael Vinker, Yuval Alaluf, Amit H. Bermano, Daniel Cohen-Or, Ariel Shamir, Gal Chechik

CoRR, 2023

Data Augmentations in Deep Weight Spaces.

Aviv Shamsian, David W. Zhang, Aviv Navon, Yan Zhang, Miltiadis Kofinas, Idan Achituve, Riccardo Valperga, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, Ethan Fetaya, Gal Chechik, Haggai Maron

CoRR, 2023

Equivariant Deep Weight Space Alignment.

Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron

CoRR, 2023

It is all about where you start: Text-to-image generation with seed selection.

Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, Gal Chechik

CoRR, 2023

Designing an Encoder for Fast Personalization of Text-to-Image Models.

Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or

CoRR, 2023

SoftTreeMax: Exponential Variance Reduction in Policy Gradient via Tree Search.

Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik

CoRR, 2023

Guided Deep Kernel Learning.

Idan Achituve, Gal Chechik, Ethan Fetaya

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models.

Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik, Daniel Cohen-Or, Ariel Shamir, Amit H. Bermano

Proceedings of the SIGGRAPH Asia 2023 Conference Papers, 2023

Key-Locked Rank One Editing for Text-to-Image Personalization.

Yoad Tewel, Rinon Gal, Gal Chechik, Yuval Atzmon

Proceedings of the ACM SIGGRAPH 2023 Conference Proceedings, 2023

CALM: Conditional Adversarial Latent Models for Directable Virtual Characters.

Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng

Proceedings of the ACM SIGGRAPH 2023 Conference Proceedings, 2023

Norm-guided latent space exploration for text-to-image generation.

Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment.

Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Point Cloud Completion with Pretrained Text-to-Image Diffusion Models.

Yoni Kasten, Ohad Rahamim, Gal Chechik

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Train Hard, Fight Easy: Robust Meta Reinforcement Learning.

Ido Greenberg, Shie Mannor, Gal Chechik, Eli A. Meirom

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Auxiliary Learning as an Asymmetric Bargaining Game.

Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya

Proceedings of the International Conference on Machine Learning, 2023

Equivariant Architectures for Learning in Deep Weight Spaces.

Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron

Proceedings of the International Conference on Machine Learning, 2023

Graph Positional Encoding via Random Feature Propagation.

Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

Proceedings of the International Conference on Machine Learning, 2023

Learning to Initiate and Reason in Event-Driven Cascading Processes.

Yuval Atzmon, Eli A. Meirom, Shie Mannor, Gal Chechik

Proceedings of the International Conference on Machine Learning, 2023

Personalized Federated Learning for Medical Segmentation using Hypernetworks.

Hilit Segev, Gal Chechik

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit Haim Bermano, Gal Chechik, Daniel Cohen-Or

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Example-based Hypernetworks for Multi-source Adaptation to Unseen Domains.

Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs.

Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

DisCLIP: Open-Vocabulary Referring Expression Generation.

Lior Bracha, Eitan Shaar, Aviv Shamsian, Ethan Fetaya, Gal Chechik

Proceedings of the 34th British Machine Vision Conference 2023, 2023

Planning and Learning with Adaptive Lookahead.

Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

StyleGAN-NADA: CLIP-guided domain adaptation of image generators.

Rinon Gal, Or Patashnik, Haggai Maron, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or

ACM Trans. Graph., 2022

Reinforcement Learning for Datacenter Congestion Control.

Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor

SIGMETRICS Perform. Evaluation Rev., 2022

Text2Model: Model Induction for Zero-shot Generalization Using Task Descriptions.

Ohad Amosy, Tomer Volk, Eyal Ben-David, Roi Reichart, Gal Chechik

CoRR, 2022

SoftTreeMax: Policy Gradient with Tree Search.

Gal Dalal, Assaf Hallak, Shie Mannor, Gal Chechik

CoRR, 2022

Example-based Hypernetworks for Out-of-Distribution Generalization.

Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart

CoRR, 2022

Learning to reason about and to act on physical cascading events.

Yuval Atzmon, Eli A. Meirom, Shie Mannor, Gal Chechik

CoRR, 2022

Federated Learning with Heterogeneous Architectures using Graph HyperNetworks.

Or Litany, Haggai Maron, David Acuna, Jan Kautz, Gal Chechik, Sanja Fidler

CoRR, 2022

Coupled Training for Multi-Source Domain Adaptation.

Ohad Amosy, Gal Chechik

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Reinforcement Learning with a Terminator.

Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-Task Learning as a Bargaining Game.

Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya

Proceedings of the International Conference on Machine Learning, 2022

Optimizing Tensor Network Contraction Using Reinforcement Learning.

Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik

Proceedings of the International Conference on Machine Learning, 2022

On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning.

Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit

Proceedings of the Tenth International Conference on Learning Representations, 2022

"This Is My Unicorn, Fluffy": Personalizing Frozen Vision-Language Representations.

Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon

Proceedings of the Computer Vision - ECCV 2022, 2022

Object-Region Video Transformers.

Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam, Amir Bar, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

DETReg: Unsupervised Pretraining with Region Priors for Object Detection.

Amir Bar, Xin Wang, Vadim Kantorov, Colorado J. Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Inference-Time Personalized Federated Learning.

Ohad Amosy, Gal Eyal, Gal Chechik

CoRR, 2021

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators.

Rinon Gal, Or Patashnik, Haggai Maron, Gal Chechik, Daniel Cohen-Or

CoRR, 2021

Automatic Curation of Large-Scale Datasets for Audio-Visual Representation Learning.

Sangho Lee, Jiwan Chung, Youngjae Yu, Gunhee Kim, Thomas M. Breuel, Gal Chechik, Yale Song

CoRR, 2021

From generalized zero-shot learning to long-tail with class descriptors.

Dvir Samuel, Yuval Atzmon, Gal Chechik

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Self-Supervised Learning for Domain Adaptation on Point Clouds.

Idan Achituve, Haggai Maron, Gal Chechik

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Known unknowns: Learning novel concepts using reasoning-by-elimination.

Harsh Agrawal, Eli A. Meirom, Yuval Atzmon, Shie Mannor, Gal Chechik

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction.

Gal Dalal, Assaf Hallak, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Personalized Federated Learning With Gaussian Processes.

Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Learning Sets of Symmetric Elements (Extended Abstract).

Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

From Local Structures to Size Generalization in Graph Neural Networks.

Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron

Proceedings of the 38th International Conference on Machine Learning, 2021

Personalized Federated Learning using Hypernetworks.

Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik

Proceedings of the 38th International Conference on Machine Learning, 2021

Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks.

Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik

Proceedings of the 38th International Conference on Machine Learning, 2021

Compositional Video Synthesis with Action Graphs.

Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson

Proceedings of the 38th International Conference on Machine Learning, 2021

GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning.

Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning the Pareto Front with Hypernetworks.

Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik

Proceedings of the 9th International Conference on Learning Representations, 2021

Auxiliary Learning by Implicit Differentiation.

Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya

Proceedings of the 9th International Conference on Learning Representations, 2021

Distributional Robustness Loss for Long-tail Learning.

Dvir Samuel, Gal Chechik

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

ACAV100M: Automatic Curation of Large-Scale Datasets for Audio-Visual Video Representation Learning.

Sangho Lee, Jiwan Chung, Youngjae Yu, Gunhee Kim, Thomas M. Breuel, Gal Chechik, Yale Song

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Deep Ranking-Based DOA Tracking Algorithm.

Renana Opochinsky, Gal Chechik, Sharon Gannot

Proceedings of the 29th European Signal Processing Conference, 2021

2020

Teacher-Student Consistency For Multi-Source Domain Adaptation.

Ohad Amosy, Gal Chechik

CoRR, 2020

On Size Generalization in Graph Neural Networks.

Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron

CoRR, 2020

How to Stop Epidemics: Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks.

Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik

CoRR, 2020

Learning Object Detection from Captions via Textual Scene Attributes.

Achiya Jerbi, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson

CoRR, 2020

Compositional Video Synthesis with Action Graphs.

Amir Bar, Roei Herzig, Xiaolong Wang, Gal Chechik, Trevor Darrell, Amir Globerson

CoRR, 2020

Long-tail learning with attributes.

Dvir Samuel, Yuval Atzmon, Gal Chechik

CoRR, 2020

Differentiable Scene Graphs.

Moshiko Raboh, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

A causal view of compositional zero-shot recognition.

Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On Learning Sets of Symmetric Elements.

Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

Proceedings of the 37th International Conference on Machine Learning, 2020

ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization.

Tzuf Paz-Argaman, Reut Tsarfaty, Gal Chechik, Yuval Atzmon

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Learning Object Permanence from Video.

Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik

Proceedings of the Computer Vision - ECCV 2020, 2020

Learning Canonical Representations for Scene Graph to Image Generation.

Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson

Proceedings of the Computer Vision - ECCV 2020, 2020

Contrastive Learning for Weakly Supervised Phrase Grounding.

Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Cooperative image captioning.

Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik

CoRR, 2019

Few-Shot Learning with Per-Sample Rich Supervision.

Roman Visotsky, Yuval Atzmon, Gal Chechik

CoRR, 2019

Learning Latent Scene-Graph Representations for Referring Relationships.

Moshiko Raboh, Roei Herzig, Gal Chechik, Jonathan Berant, Amir Globerson

CoRR, 2019

Deep Ranking-Based Sound Source Localization.

Renana Opochinsky, Bracha Laufer-Goldshtein, Sharon Gannot, Gal Chechik

Proceedings of the 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2019

Joint Optimization for Cooperative Image Captioning.

Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Network Adaptation Strategies for Learning New Classes without Forgetting the Original Ones.

Hagai Taitelbaum, Gal Chechik, Jacob Goldberger

Proceedings of the IEEE International Conference on Acoustics, 2019

A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation.

Hagai Taitelbaum, Gal Chechik, Jacob Goldberger

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Multilingual word translation using auxiliary languages.

Hagai Taitelbaum, Gal Chechik, Jacob Goldberger

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Informative Object Annotations: Tell Me Something I Don't Know.

Lior Bracha, Gal Chechik

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Adaptive Confidence Smoothing for Generalized Zero-Shot Learning.

Yuval Atzmon, Gal Chechik

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Learning with Per-Sample Side Information.

Roman Visotsky, Yuval Atzmon, Gal Chechik

Proceedings of the Artificial General Intelligence - 12th International Conference, 2019

2018

Domain-Aware Generalized Zero-Shot Learning.

Yuval Atzmon, Gal Chechik

CoRR, 2018

Metric Learning for Phoneme Perception.

Yair Lakretz, Gal Chechik, Evan-Gary Cohen, Alessandro Treves, Naama Friedmann

CoRR, 2018

Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning.

Yuval Atzmon, Gal Chechik

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction.

Roei Herzig, Moshiko Raboh, Gal Chechik, Jonathan Berant, Amir Globerson

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Group online adaptive learning.

Alon Zweig, Gal Chechik

Mach. Learn., 2017

Instance-Level Label Propagation with Multi-Instance Learning.

Qifan Wang, Gal Chechik, Chen Sun, Bin Shen

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders.

Ido Cohen, Eli (Omid) David, Nathan S. Netanyahu, Noa Liscovitch, Gal Chechik

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

Learning from Noisy Large-Scale Datasets with Minimal Supervision.

Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge J. Belongie

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Context-Aware Captions from Context-Agnostic Supervision.

Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

On Expression Patterns and Developmental Origin of Human Brain Regions.

Lior Kirsch, Gal Chechik

PLoS Comput. Biol., 2016

Learning to generalize to new compositions in image understanding.

Yuval Atzmon, Jonathan Berant, Vahid Kezami, Amir Globerson, Gal Chechik

CoRR, 2016

2015

Gene Expression Switching of Receptor Subunits in Human Brain Development.

Ossnat Bar-Shira, Ronnie Maor, Gal Chechik

PLoS Comput. Biol., 2015

Gradual Training Method for Denoising Auto Encoders.

Alexander Kalmanovich, Gal Chechik

Proceedings of the 3rd International Conference on Learning Representations, 2015

Learning Sparse Metrics, One Feature at a Time.

Yuval Atzmon, Uri Shalit, Gal Chechik

Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015

Probabilistic Graphical Models of Dyslexia.

Yair Lakretz, Gal Chechik, Naama Friedmann, Michal Rosen-Zvi

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

Learning semantic representations of objects and their parts.

Grégoire Mesnil, Antoine Bordes, Jason Weston, Gal Chechik, Yoshua Bengio

Mach. Learn., 2014

Gradual training of deep denoising auto encoders.

Alexander Kalmanovich, Gal Chechik

CoRR, 2014

Coordinate-descent for learning orthogonal matrices through Givens rotations.

Uri Shalit, Gal Chechik

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Specialization of Gene Expression during Mouse Brain Development.

Noa Liscovitch, Gal Chechik

PLoS Comput. Biol., 2013

Efficient coordinate-descent for orthogonal matrices through Givens rotations.

Uri Shalit, Gal Chechik

CoRR, 2013

FuncISH: learning a functional representation of neural ISH images.

Noa Liscovitch, Uri Shalit, Gal Chechik

Bioinform., 2013

Modeling Musical Influence with Topic Models.

Uri Shalit, Daphna Weinshall, Gal Chechik

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Localizing Genes to Cerebellar Layers by Classifying ISH Images.

Lior Kirsch, Noa Liscovitch, Gal Chechik

PLoS Comput. Biol., 2012

Online Learning in the Embedded Manifold of Low-rank Matrices.

Uri Shalit, Daphna Weinshall, Gal Chechik

J. Mach. Learn. Res., 2012

Sufficient Dimensionality Reduction with Irrelevant Statistics

Amir Globerson, Gal Chechik, Naftali Tishby

CoRR, 2012

Adaptive Regularization for Weight Matrices

Koby Crammer, Gal Chechik

CoRR, 2012

Adaptive Regularization for Similarity Measures.

Koby Crammer, Gal Chechik

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Sparse coding of auditory features for machine hearing in interference.

Richard F. Lyon, Jay Ponte, Gal Chechik

Proceedings of the IEEE International Conference on Acoustics, 2011

2010

Sound Retrieval and Ranking Using Sparse Auditory Representations.

Richard F. Lyon, Martin Rehn, Samy Bengio, Thomas C. Walters, Gal Chechik

Neural Comput., 2010

Large Scale Online Learning of Image Similarity Through Ranking.

Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio

J. Mach. Learn. Res., 2010

Online Learning in The Manifold of Low-Rank Matrices.

Uri Shalit, Daphna Weinshall, Gal Chechik

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Object separation in x-ray image sets.

Geremy Heitz, Gal Chechik

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009

Timing of Gene Expression Responses to Environmental Changes.

Gal Chechik, Daphne Koller

J. Comput. Biol., 2009

An Online Algorithm for Large Scale Image Similarity Learning.

Gal Chechik, Uri Shalit, Varun Sharma, Samy Bengio

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008

Max-margin Classification of Data with Absent Features.

Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

J. Mach. Learn. Res., 2008

Large-scale content-based audio retrieval from text queries.

Gal Chechik, Eugene Ie, Martin Rehn, Samy Bengio, Dick Lyon

Proceedings of the 1st ACM SIGMM International Conference on Multimedia Information Retrieval, 2008

2007

Euclidean Embedding of Co-occurrence Data.

Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby

J. Mach. Learn. Res., 2007

NIPS workshop on New Problems and Methods in Computational Biology.

Gal Chechik, Christina S. Leslie, William Stafford Noble, Gunnar Rätsch, Quaid Morris, Koji Tsuda

BMC Bioinform., 2007

2006

Discrete profile comparison using information bottleneck.

Sean O'Rourke, Gal Chechik, Robin Friedman, Eleazar Eskin

BMC Bioinform., 2006

Max-margin classification of incomplete data.

Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks.

Alexis J. Battle, Gal Chechik, Daphne Koller

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Embedding Heterogeneous Data Using Statistical Models.

Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby

Proceedings of the Proceedings, 2006

2005

Information Bottleneck for Gaussian Variables.

Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss

J. Mach. Learn. Res., 2005

Encoding Stimulus Information by Spike Numbers and Mean Response Time in Primary Auditory Cortex.

Israel Nelken, Gal Chechik, Thomas D. Mrsic-Flogel, Andrew J. King, Jan W. H. Schnupp

J. Comput. Neurosci., 2005

2004

Discrete profile alignment via constrained information bottleneck.

Sean O'Rourke, Gal Chechik, Robin Friedman, Eleazar Eskin

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

A needle in a haystack: local one-class optimization.

Koby Crammer, Gal Chechik

Proceedings of the Machine Learning, 2004

2003

Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization.

Gal Chechik

Neural Comput., 2003

Sufficient Dimensionality Reduction with Irrelevance Statistics.

Amir Globerson, Gal Chechik, Naftali Tishby

Proceedings of the UAI '03, 2003

Are There Representations in Embodied Evolved Agents? Taking Measures.

Hezi Avraham, Gal Chechik, Eytan Ruppin

Proceedings of the Advances in Artificial Life, 7th European Conference, 2003

2002

Extracting Relevant Structures with Side Information.

Gal Chechik, Naftali Tishby

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001

Effective Neuronal Learning with Ineffective Hebbian Learning Rules.

Gal Chechik, Isaac Meilijson, Eytan Ruppin

Neural Comput., 2001

Spike timing dependent plasticity and mutual information in spiking neurons.

Gal Chechik

Neurocomputing, 2001

Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway.

Gal Chechik, Amir Globerson, Michael J. Anderson, Eric D. Young, Israel Nelken, Naftali Tishby

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

2000

Neuronal normalization provides effective learning through ineffective synaptic learning rules.

Gal Chechik, Isaac Meilijson, Eytan Ruppin

Neurocomputing, 2000

Temporally Dependent Plasticity: An Information Theoretic Account.

Gal Chechik, Naftali Tishby

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999

Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation.

Gal Chechik, Isaac Meilijson, Eytan Ruppin

Neural Comput., 1999

Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development.

Gal Chechik, Isaac Meilijson, Eytan Ruppin

Neurocomputing, 1999

Effective Learning Requires Neuronal Remodeling of Hebbian Synapses.

Gal Chechik, Isaac Meilijson, Eytan Ruppin

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998

Synaptic Pruning In Development: A Computational Account.

Gal Chechik, Isaac Meilijson, Eytan Ruppin

Neural Comput., 1998

Neuronal Regulation Implements Efficient Synaptic Pruning.

Gal Chechik, Isaac Meilijson, Eytan Ruppin

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998