Timezone: »
Importance weighted variational inference (Burda et al., 2015) uses multiple i.i.d. samples to have a tighter variational lower bound. We believe a joint proposal has the potential of reducing the number of redundant samples, and introduce a hierarchical structure to induce correlation. The hope is that the proposals would coordinate to make up for the error made by one another to reduce the variance of the importance estimator. Theoretically, we analyze the condition under which convergence of the estimator variance can be connected to convergence of the lower bound. Empirically, we confirm that maximization of the lower bound does implicitly minimize variance. Further analysis shows that this is a result of negative correlation induced by the proposed hierarchical meta sampling scheme, and performance of inference also improves when the number of samples increases.
Author Information
Chin-Wei Huang (MILA)
Kris Sankaran (Mila)
Eeshan Dhekane (MILA, Université de Montréal)
Alexandre Lacoste (Element AI)
Aaron Courville (Université de Montréal)
Related Events (a corresponding poster, oral, or spotlight)
-
2019 Oral: Hierarchical Importance Weighted Autoencoders »
Fri. Jun 14th 12:05 -- 12:10 AM Room Grand Ballroom
More from the Same Authors
-
2021 : A Variational Perspective on Diffusion-Based Generative Models and Score Matching »
Chin-Wei Huang -
2021 : Variational Causal Networks: Approximate Bayesian Inference over Causal Structures »
Yashas Annadani · Jonas Rothfuss · Alexandre Lacoste · Nino Scherrer · Anirudh Goyal · Yoshua Bengio · Stefan Bauer -
2022 : Unsupervised Model-based Pre-training for Data-efficient Reinforcement Learning from Pixels »
Sai Rajeswar · Pietro Mazzaglia · Tim Verbelen · Alex Piche · Bart Dhoedt · Aaron Courville · Alexandre Lacoste -
2023 Oral: Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels »
Sai Rajeswar · Pietro Mazzaglia · Tim Verbelen · Alex Piche · Bart Dhoedt · Aaron Courville · Alexandre Lacoste -
2023 Poster: Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels »
Sai Rajeswar · Pietro Mazzaglia · Tim Verbelen · Alex Piche · Bart Dhoedt · Aaron Courville · Alexandre Lacoste -
2022 Poster: Building Robust Ensembles via Margin Boosting »
Dinghuai Zhang · Hongyang Zhang · Aaron Courville · Yoshua Bengio · Pradeep Ravikumar · Arun Sai Suggala -
2022 Spotlight: Building Robust Ensembles via Margin Boosting »
Dinghuai Zhang · Hongyang Zhang · Aaron Courville · Yoshua Bengio · Pradeep Ravikumar · Arun Sai Suggala -
2022 Poster: Generative Flow Networks for Discrete Probabilistic Modeling »
Dinghuai Zhang · Nikolay Malkin · Zhen Liu · Alexandra Volokhova · Aaron Courville · Yoshua Bengio -
2022 Poster: The Primacy Bias in Deep Reinforcement Learning »
Evgenii Nikishin · Max Schwarzer · Pierluca D'Oro · Pierre-Luc Bacon · Aaron Courville -
2022 Spotlight: Generative Flow Networks for Discrete Probabilistic Modeling »
Dinghuai Zhang · Nikolay Malkin · Zhen Liu · Alexandra Volokhova · Aaron Courville · Yoshua Bengio -
2022 Spotlight: The Primacy Bias in Deep Reinforcement Learning »
Evgenii Nikishin · Max Schwarzer · Pierluca D'Oro · Pierre-Luc Bacon · Aaron Courville -
2021 Workshop: INNF+: Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models »
Chin-Wei Huang · David Krueger · Rianne Van den Berg · George Papamakarios · Ricky T. Q. Chen · Danilo J. Rezende -
2021 Poster: Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? »
Dinghuai Zhang · Kartik Ahuja · Yilun Xu · Yisen Wang · Aaron Courville -
2021 Oral: Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? »
Dinghuai Zhang · Kartik Ahuja · Yilun Xu · Yisen Wang · Aaron Courville -
2021 Poster: Continuous Coordination As a Realistic Scenario for Lifelong Learning »
Hadi Nekoei · Akilesh Badrinaaraayanan · Aaron Courville · Sarath Chandar -
2021 Spotlight: Continuous Coordination As a Realistic Scenario for Lifelong Learning »
Hadi Nekoei · Akilesh Badrinaaraayanan · Aaron Courville · Sarath Chandar -
2021 Poster: Out-of-Distribution Generalization via Risk Extrapolation (REx) »
David Krueger · Ethan Caballero · Joern-Henrik Jacobsen · Amy Zhang · Jonathan Binas · Dinghuai Zhang · Remi Le Priol · Aaron Courville -
2021 Oral: Out-of-Distribution Generalization via Risk Extrapolation (REx) »
David Krueger · Ethan Caballero · Joern-Henrik Jacobsen · Amy Zhang · Jonathan Binas · Dinghuai Zhang · Remi Le Priol · Aaron Courville -
2020 Workshop: INNF+: Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models »
Chin-Wei Huang · David Krueger · Rianne Van den Berg · George Papamakarios · Chris Cremer · Ricky T. Q. Chen · Danilo J. Rezende -
2020 Poster: AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation »
Jae Hyun Lim · Aaron Courville · Christopher Pal · Chin-Wei Huang -
2020 Poster: Countering Language Drift with Seeded Iterated Learning »
Yuchen Lu · Soumye Singhal · Florian Strub · Aaron Courville · Olivier Pietquin -
2019 : Detecting Waterborne Debris with Sim2Real and Randomization »
Kris Sankaran -
2019 Workshop: AI For Social Good (AISG) »
Margaux Luck · Kris Sankaran · Tristan Sylvain · Sean McGregor · Jonnie Penn · Girmaw Abebe Tadesse · Virgile Sylvain · Myriam Côté · Lester Mackey · Rayid Ghani · Yoshua Bengio -
2019 Workshop: Invertible Neural Networks and Normalizing Flows »
Chin-Wei Huang · David Krueger · Rianne Van den Berg · George Papamakarios · Aidan Gomez · Chris Cremer · Aaron Courville · Ricky T. Q. Chen · Danilo J. Rezende -
2019 : Poster discussion »
Roman Novak · Maxime Gabella · Frederic Dreyer · Siavash Golkar · Anh Tong · Irina Higgins · Mirco Milletari · Joe Antognini · Sebastian Goldt · Adín Ramírez Rivera · Roberto Bondesan · Ryo Karakida · Remi Tachet des Combes · Michael Mahoney · Nicholas Walker · Stanislav Fort · Samuel Smith · Rohan Ghosh · Aristide Baratin · Diego Granziol · Stephen Roberts · Dmitry Vetrov · Andrew Wilson · César Laurent · Valentin Thomas · Simon Lacoste-Julien · Dar Gilboa · Daniel Soudry · Anupam Gupta · Anirudh Goyal · Yoshua Bengio · Erich Elsen · Soham De · Stanislaw Jastrzebski · Charles H Martin · Samira Shabanian · Aaron Courville · Shorato Akaho · Lenka Zdeborova · Ethan Dyer · Maurice Weiler · Pim de Haan · Taco Cohen · Max Welling · Ping Luo · zhanglin peng · Nasim Rahaman · Loic Matthey · Danilo J. Rezende · Jaesik Choi · Kyle Cranmer · Lechao Xiao · Jaehoon Lee · Yasaman Bahri · Jeffrey Pennington · Greg Yang · Jiri Hron · Jascha Sohl-Dickstein · Guy Gur-Ari -
2019 : Networking Lunch (provided) + Poster Session »
Abraham Stanway · Alex Robson · Aneesh Rangnekar · Ashesh Chattopadhyay · Ashley Pilipiszyn · Benjamin LeRoy · Bolong Cheng · Ce Zhang · Chaopeng Shen · Christian Schroeder · Christian Clough · Clement DUHART · Clement Fung · Cozmin Ududec · Dali Wang · David Dao · di wu · Dimitrios Giannakis · Dino Sejdinovic · Doina Precup · Duncan Watson-Parris · Gege Wen · George Chen · Gopal Erinjippurath · Haifeng Li · Han Zou · Herke van Hoof · Hillary A Scannell · Hiroshi Mamitsuka · Hongbao Zhang · Jaegul Choo · James Wang · James Requeima · Jessica Hwang · Jinfan Xu · Johan Mathe · Jonathan Binas · Joonseok Lee · Kalai Ramea · Kate Duffy · Kevin McCloskey · Kris Sankaran · Lester Mackey · Letif Mones · Loubna Benabbou · Lynn Kaack · Matthew Hoffman · Mayur Mudigonda · Mehrdad Mahdavi · Michael McCourt · Mingchao Jiang · Mohammad Mahdi Kamani · Neel Guha · Niccolo Dalmasso · Nick Pawlowski · Nikola Milojevic-Dupont · Paulo Orenstein · Pedram Hassanzadeh · Pekka Marttinen · Ramesh Nair · Sadegh Farhang · Samuel Kaski · Sandeep Manjanna · Sasha Luccioni · Shuby Deshpande · Soo Kim · Soukayna Mouatadid · Sunghyun Park · Tao Lin · Telmo Felgueira · Thomas Hornigold · Tianle Yuan · Tom Beucler · Tracy Cui · Volodymyr Kuleshov · Wei Yu · yang song · Ydo Wexler · Yoshua Bengio · Zhecheng Wang · Zhuangfang Yi · Zouheir Malki -
2019 Workshop: Climate Change: How Can AI Help? »
David Rolnick · Alexandre Lacoste · Tegan Maharaj · Jennifer Chayes · Yoshua Bengio -
2018 Poster: Neural Autoregressive Flows »
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville -
2018 Oral: Neural Autoregressive Flows »
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville