Oral
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
Friso Kingma · Pieter Abbeel · Jonathan Ho
The "bits back" argument (Wallace, 1990; Hinton & Van Camp, 1993) suggests lossless compression schemes with latent variable models. However, how to translate the "bits back" argument into efficient and practical lossless compression schemes is still largely an open problem. Bits-Back with Asymmetric Numeral Systems (Townsend et al., 2018) makes "bits back" coding practically feasible, yet when executed on hierarchical latent variable models, their algorithm becomes substantially inefficient. In this paper we propose Bit-Swap, a compression scheme that generalizes existing lossless compression techniques and results in strictly better compression rates for hierarchical latent variable models. Through experiments we verify that the proposed technique results in lossless compression rates that are empirically superior to existing techniques.
Author Information
Friso Kingma (UC Berkeley)
Pieter Abbeel (OpenAI / UC Berkeley)
Jonathan Ho (UC Berkeley)
Related Events (a corresponding poster, oral, or spotlight)
-
2019 Poster: Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables »
Thu Jun 13th 06:30 -- 09:00 PM Room Pacific Ballroom
More from the Same Authors
-
2019 Workshop: Workshop on Self-Supervised Learning »
Aaron van den Oord · Yusuf Aytar · Carl Doersch · Carl Vondrick · Alec Radford · Pierre Sermanet · Amir Zamir · Pieter Abbeel -
2019 Poster: On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference »
Rohin Shah · Noah Gundotra · Pieter Abbeel · EECS Anca Dragan -
2019 Oral: On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference »
Rohin Shah · Noah Gundotra · Pieter Abbeel · EECS Anca Dragan -
2019 Poster: Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design »
Jonathan Ho · Peter Chen · Aravind Srinivas · Rocky Duan · Pieter Abbeel -
2019 Poster: SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning »
Marvin Zhang · Sharad Vikram · Laura Smith · Pieter Abbeel · Matthew Johnson · Sergey Levine -
2019 Oral: Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design »
Jonathan Ho · Peter Chen · Aravind Srinivas · Rocky Duan · Pieter Abbeel -
2019 Oral: SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning »
Marvin Zhang · Sharad Vikram · Laura Smith · Pieter Abbeel · Matthew Johnson · Sergey Levine -
2018 Poster: Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor »
Tuomas Haarnoja · Aurick Zhou · Pieter Abbeel · Sergey Levine -
2018 Poster: PixelSNAIL: An Improved Autoregressive Generative Model »
Xi Chen · Nikhil Mishra · Mostafa Rohaninejad · Pieter Abbeel -
2018 Oral: Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor »
Tuomas Haarnoja · Aurick Zhou · Pieter Abbeel · Sergey Levine -
2018 Oral: PixelSNAIL: An Improved Autoregressive Generative Model »
Xi Chen · Nikhil Mishra · Mostafa Rohaninejad · Pieter Abbeel -
2018 Poster: Automatic Goal Generation for Reinforcement Learning Agents »
Carlos Florensa · David Held · Xinyang Geng · Pieter Abbeel -
2018 Poster: Latent Space Policies for Hierarchical Reinforcement Learning »
Tuomas Haarnoja · Kristian Hartikainen · Pieter Abbeel · Sergey Levine -
2018 Poster: Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings »
John Co-Reyes · Yu Xuan Liu · Abhishek Gupta · Benjamin Eysenbach · Pieter Abbeel · Sergey Levine -
2018 Poster: Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control »
Aravind Srinivas · Allan Jabri · Pieter Abbeel · Sergey Levine · Chelsea Finn -
2018 Oral: Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control »
Aravind Srinivas · Allan Jabri · Pieter Abbeel · Sergey Levine · Chelsea Finn -
2018 Oral: Automatic Goal Generation for Reinforcement Learning Agents »
Carlos Florensa · David Held · Xinyang Geng · Pieter Abbeel -
2018 Oral: Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings »
John Co-Reyes · Yu Xuan Liu · Abhishek Gupta · Benjamin Eysenbach · Pieter Abbeel · Sergey Levine -
2018 Oral: Latent Space Policies for Hierarchical Reinforcement Learning »
Tuomas Haarnoja · Kristian Hartikainen · Pieter Abbeel · Sergey Levine -
2017 Poster: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks »
Chelsea Finn · Pieter Abbeel · Sergey Levine -
2017 Poster: Prediction and Control with Temporal Segment Models »
Nikhil Mishra · Pieter Abbeel · Igor Mordatch -
2017 Poster: Reinforcement Learning with Deep Energy-Based Policies »
Tuomas Haarnoja · Haoran Tang · Pieter Abbeel · Sergey Levine -
2017 Poster: Constrained Policy Optimization »
Joshua Achiam · David Held · Aviv Tamar · Pieter Abbeel -
2017 Talk: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks »
Chelsea Finn · Pieter Abbeel · Sergey Levine -
2017 Talk: Prediction and Control with Temporal Segment Models »
Nikhil Mishra · Pieter Abbeel · Igor Mordatch -
2017 Talk: Reinforcement Learning with Deep Energy-Based Policies »
Tuomas Haarnoja · Haoran Tang · Pieter Abbeel · Sergey Levine -
2017 Talk: Constrained Policy Optimization »
Joshua Achiam · David Held · Aviv Tamar · Pieter Abbeel
