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Session
Oral Session 3
Amir Globerson
Tue Dec 13 03:00 AM -- 03:40 AM (PST) @
Author Information
Amir Globerson (Tel Aviv University, Google)
Amir Globerson is senior lecturer at the School of Engineering and Computer Science at the Hebrew University. He received a PhD in computational neuroscience from the Hebrew University, and was a Rothschild postdoctoral fellow at MIT. He joined the Hebrew University in 2008. His research interests include graphical models and probabilistic inference, convex optimization, robust learning and natural language processing.
More from the Same Authors
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2022 Poster: Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens »
Elad Ben Avraham · Roei Herzig · Karttikeya Mangalam · Amir Bar · Anna Rohrbach · Leonid Karlinsky · Trevor Darrell · Amir Globerson -
2022 Poster: Visual Prompting via Image Inpainting »
Amir Bar · Yossi Gandelsman · Trevor Darrell · Amir Globerson · Alexei Efros -
2021 Poster: A Theoretical Analysis of Fine-tuning with Linear Teachers »
Gal Shachaf · Alon Brutzkus · Amir Globerson -
2020 Poster: Regularizing Towards Permutation Invariance In Recurrent Models »
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2018 Poster: Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction »
Roei Herzig · Moshiko Raboh · Gal Chechik · Jonathan Berant · Amir Globerson -
2017 Poster: Robust Conditional Probabilities »
Yoav Wald · Amir Globerson -
2016 Poster: Optimal Tagging with Markov Chain Optimization »
Nir Rosenfeld · Amir Globerson -
2012 Poster: Convergence Rate Analysis of MAP Coordinate Minimization Algorithms »
Ofer Meshi · Tommi Jaakkola · Amir Globerson -
2011 Session: Spotlight Session 3 »
Amir Globerson -
2011 Tutorial: Linear Programming Relaxations for Graphical Models »
Amir Globerson · Tommi Jaakkola -
2010 Spotlight: More data means less inference: A pseudo-max approach to structured learning »
David Sontag · Ofer Meshi · Tommi Jaakkola · Amir Globerson -
2010 Poster: More data means less inference: A pseudo-max approach to structured learning »
David Sontag · Ofer Meshi · Tommi Jaakkola · Amir Globerson -
2009 Workshop: Approximate Learning of Large Scale Graphical Models »
Russ Salakhutdinov · Amir Globerson · David Sontag -
2009 Poster: An LP View of the M-best MAP problem »
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2009 Oral: An LP View of the M-Best MAP Problem »
Menachem Fromer · Amir Globerson -
2008 Workshop: Approximate inference - how far have we come? »
Amir Globerson · David Sontag · Tommi Jaakkola -
2008 Poster: Clusters and Coarse Partitions in LP Relaxations »
David Sontag · Amir Globerson · Tommi Jaakkola -
2008 Spotlight: Clusters and Coarse Partitions in LP Relaxations »
David Sontag · Amir Globerson · Tommi Jaakkola -
2007 Poster: Convex Learning with Invariances »
Choon Hui Teo · Amir Globerson · Sam T Roweis · Alexander Smola -
2007 Spotlight: Convex Learning with Invariances »
Choon Hui Teo · Amir Globerson · Sam T Roweis · Alexander Smola -
2007 Poster: Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations »
Amir Globerson · Tommi Jaakkola -
2006 Talk: Approximate inference using planar graph decomposition »
Amir Globerson · Tommi Jaakkola -
2006 Poster: Approximate inference using planar graph decomposition »
Amir Globerson · Tommi Jaakkola