Timezone: »
Poster
Superposition of many models into one
Brian Cheung · Alexander Terekhov · Yubei Chen · Pulkit Agrawal · Bruno Olshausen
Thu Dec 12 05:00 PM -- 07:00 PM (PST) @ East Exhibition Hall B + C #26
We present a method for storing multiple models within a single set of parameters. Models can coexist in superposition and still be retrieved individually. In experiments with neural networks, we show that a surprisingly large number of models can be effectively stored within a single parameter instance. Furthermore, each of these models can undergo thousands of training steps without significantly interfering with other models within the superposition. This approach may be viewed as the online complement of compression: rather than reducing the size of a network after training, we make use of the unrealized capacity of a network during training.
Author Information
Brian Cheung (UC Berkeley)
Alexander Terekhov (Awecom, Inc)
Yubei Chen (Berkeley AI Research UC Berkeley)
Pulkit Agrawal (UC Berkeley)
Bruno Olshausen (Redwood Center/UC Berkeley)
More from the Same Authors
-
2021 : 3D Neural Scene Representations for Visuomotor Control »
Yunzhu Li · Shuang Li · Vincent Sitzmann · Pulkit Agrawal · Antonio Torralba -
2021 : 3D Neural Scene Representations for Visuomotor Control »
Yunzhu Li · Shuang Li · Vincent Sitzmann · Pulkit Agrawal · Antonio Torralba -
2022 : Is Conditional Generative Modeling all you need for Decision-Making? »
Anurag Ajay · Yilun Du · Abhi Gupta · Josh Tenenbaum · Tommi Jaakkola · Pulkit Agrawal -
2022 : Learning to Extrapolate: A Transductive Approach »
Aviv Netanyahu · Abhishek Gupta · Max Simchowitz · Kaiqing Zhang · Pulkit Agrawal -
2022 : Neuromorphic Visual Scene Understanding with Resonator Networks (in brief) »
Alpha Renner · Giacomo Indiveri · Lazar Supic · Andreea Danielescu · Bruno Olshausen · Fritz Sommer · Yulia Sandamirskaya · Edward Frady -
2022 : Disentangling Images with Lie Group Transformations and Sparse Coding »
Ho Yin Chau · Frank Qiu · Yubei Chen · Bruno Olshausen -
2022 : System identification of neural systems: If we got it right, would we know? »
Yena Han · Tomaso Poggio · Brian Cheung -
2022 : Fast Adaptation via Human Diagnosis of Task Distribution Shift »
Andi Peng · Mark Ho · Aviv Netanyahu · Julie A Shah · Pulkit Agrawal -
2022 : Aligning Robot Representations with Humans »
Andreea Bobu · Andi Peng · Pulkit Agrawal · Julie A Shah · Anca Dragan -
2023 Poster: Self-Supervised Reinforcement Learning that Transfers using Random Features »
Boyuan Chen · Chuning Zhu · Pulkit Agrawal · Kaiqing Zhang · Abhishek Gupta -
2023 Poster: Breadcrumbs to the Goal: Supervised Goal Selection from Human-in-the-Loop Feedback »
Marcel Torne Villasevil · Max Balsells I Pamies · Zihan Wang · Samedh Desai · Tao Chen · Pulkit Agrawal · Abhishek Gupta -
2023 Poster: Human-Guided Complexity-Controlled Abstractions »
Andi Peng · Mycal Tucker · Eoin Kenny · Noga Zaslavsky · Pulkit Agrawal · Julie A Shah -
2023 Poster: Hierarchical Planning with Foundation Models »
Anurag Ajay · Seungwook Han · Yilun Du · Shuang Li · Abhi Gupta · Tommi Jaakkola · Josh Tenenbaum · Leslie Kaelbling · Akash Srivastava · Pulkit Agrawal -
2023 Poster: Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets »
Zhang-Wei Hong · Aviral Kumar · Sathwik Karnik · Abhishek Bhandwaldar · Akash Srivastava · Joni Pajarinen · Romain Laroche · Abhishek Gupta · Pulkit Agrawal -
2022 : Panel Discussion II: Geometric and topological principles for representations in the brain »
Bruno Olshausen · Kristopher Jensen · Gabriel Kreiman · Manu Madhav · Christian A Shewmake -
2022 : In search of invariance in brains and machines »
Bruno Olshausen -
2022 : Visual Pre-training for Navigation: What Can We Learn from Noise? »
Felix Yanwei Wang · Ching-Yun Ko · Pulkit Agrawal -
2022 Poster: Redeeming intrinsic rewards via constrained optimization »
Eric Chen · Zhang-Wei Hong · Joni Pajarinen · Pulkit Agrawal -
2022 Poster: Distributionally Adaptive Meta Reinforcement Learning »
Anurag Ajay · Abhishek Gupta · Dibya Ghosh · Sergey Levine · Pulkit Agrawal -
2021 : 3D Neural Scene Representations for Visuomotor Control »
Yunzhu Li · Shuang Li · Vincent Sitzmann · Pulkit Agrawal · Antonio Torralba -
2021 Workshop: 2nd Workshop on Self-Supervised Learning: Theory and Practice »
Pengtao Xie · Ishan Misra · Pulkit Agrawal · Abdelrahman Mohamed · Shentong Mo · Youwei Liang · Jeannette Bohg · Kristina N Toutanova -
2020 Workshop: Self-Supervised Learning -- Theory and Practice »
Pengtao Xie · Shanghang Zhang · Pulkit Agrawal · Ishan Misra · Cynthia Rudin · Abdelrahman Mohamed · Wenzhen Yuan · Barret Zoph · Laurens van der Maaten · Xingyi Yang · Eric Xing -
2020 Session: Orals & Spotlights Track 09: Reinforcement Learning »
Pulkit Agrawal · Mohammad Ghavamzadeh -
2018 Poster: The Sparse Manifold Transform »
Yubei Chen · Dylan Paiton · Bruno Olshausen -
2018 Poster: Adversarial Examples that Fool both Computer Vision and Time-Limited Humans »
Gamaleldin Elsayed · Shreya Shankar · Brian Cheung · Nicolas Papernot · Alexey Kurakin · Ian Goodfellow · Jascha Sohl-Dickstein -
2016 : What makes ImageNet good for Transfer Learning? »
Jacob MY Huh · Pulkit Agrawal · Alexei Efros -
2016 : Jitendra Malik and Pulkit Agrawal »
Jitendra Malik · Pulkit Agrawal -
2016 Poster: Learning to Poke by Poking: Experiential Learning of Intuitive Physics »
Pulkit Agrawal · Ashvin Nair · Pieter Abbeel · Jitendra Malik · Sergey Levine -
2016 Oral: Learning to Poke by Poking: Experiential Learning of Intuitive Physics »
Pulkit Agrawal · Ashvin Nair · Pieter Abbeel · Jitendra Malik · Sergey Levine -
2010 Poster: Group Sparse Coding with a Laplacian Scale Mixture Prior »
Pierre J Garrigues · Bruno Olshausen -
2009 Workshop: Manifolds, sparsity, and structured models: When can low-dimensional geometry really help? »
Richard Baraniuk · Volkan Cevher · Mark A Davenport · Piotr Indyk · Bruno Olshausen · Michael B Wakin -
2009 Poster: Learning transport operators for image manifolds »
Jack Culpepper · Bruno Olshausen -
2008 Poster: Learning Transformational Invariants from Time-Varying Natural Images »
Charles Cadieu · Bruno Olshausen -
2008 Spotlight: Learning Transformational Invariants from Time-Varying Natural Images »
Charles Cadieu · Bruno Olshausen -
2007 Poster: Learning Horizontal Connections in a Sparse Coding Model of Natural Images »
Pierre Garrigues · Bruno Olshausen