Timezone: »
Learning-based binary hashing has become a powerful paradigm for fast search and retrieval in massive databases. However, due to the requirement of discrete outputs for the hash functions, learning such functions is known to be very challenging. In addition, the objective functions adopted by existing hashing techniques are mostly chosen heuristically. In this paper, we propose a novel generative approach to learn hash functions through Minimum Description Length principle such that the learned hash codes maximally compress the dataset and can also be used to regenerate the inputs. We also develop an efficient learning algorithm based on the stochastic distributional gradient, which avoids the notorious difficulty caused by binary output constraints, to jointly optimize the parameters of the hash function and the associated generative model. Extensive experiments on a variety of large-scale datasets show that the proposed method achieves better retrieval results than the existing state-of-the-art methods.
Author Information
Bo Dai (Georgia Tech)
Ruiqi Guo (Google Research)
Sanjiv Kumar (Google Research, NY)
Niao He (UIUC)
Le Song (Georgia Institute of Technology)
Related Events (a corresponding poster, oral, or spotlight)
-
2017 Talk: Stochastic Generative Hashing »
Wed. Aug 9th 05:48 -- 06:06 AM Room C4.4
More from the Same Authors
-
2022 : SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition »
Dylan Slack · Yinlam Chow · Bo Dai · Nevan Wichers -
2023 : SpecTr: Fast Speculative Decoding via Optimal Transport »
Ziteng Sun · Ananda Suresh · Jae Ro · Ahmad Beirami · Himanshu Jain · Felix Xinnan Yu · Michael Riley · Sanjiv Kumar -
2023 Poster: Stochastic Gradient Succeeds for Bandits »
Jincheng Mei · Zixin Zhong · Bo Dai · Alekh Agarwal · Csaba Szepesvari · Dale Schuurmans -
2023 Poster: Efficient Training of Language Models using Few-Shot Learning »
Sashank Jakkam Reddi · Sobhan Miryoosefi · Stefani Karp · Shankar Krishnan · Satyen Kale · Seungyeon Kim · Sanjiv Kumar -
2022 Poster: In defense of dual-encoders for neural ranking »
Aditya Menon · Sadeep Jayasumana · Ankit Singh Rawat · Seungyeon Kim · Sashank Jakkam Reddi · Sanjiv Kumar -
2022 Poster: Model Selection in Batch Policy Optimization »
Jonathan Lee · George Tucker · Ofir Nachum · Bo Dai -
2022 Poster: Making Linear MDPs Practical via Contrastive Representation Learning »
Tianjun Zhang · Tongzheng Ren · Mengjiao Yang · Joseph E Gonzalez · Dale Schuurmans · Bo Dai -
2022 Spotlight: Making Linear MDPs Practical via Contrastive Representation Learning »
Tianjun Zhang · Tongzheng Ren · Mengjiao Yang · Joseph E Gonzalez · Dale Schuurmans · Bo Dai -
2022 Spotlight: Model Selection in Batch Policy Optimization »
Jonathan Lee · George Tucker · Ofir Nachum · Bo Dai -
2022 Spotlight: In defense of dual-encoders for neural ranking »
Aditya Menon · Sadeep Jayasumana · Ankit Singh Rawat · Seungyeon Kim · Sashank Jakkam Reddi · Sanjiv Kumar -
2022 Poster: Robust Training of Neural Networks Using Scale Invariant Architectures »
Zhiyuan Li · Srinadh Bhojanapalli · Manzil Zaheer · Sashank Jakkam Reddi · Sanjiv Kumar -
2022 Oral: Robust Training of Neural Networks Using Scale Invariant Architectures »
Zhiyuan Li · Srinadh Bhojanapalli · Manzil Zaheer · Sashank Jakkam Reddi · Sanjiv Kumar -
2022 Poster: Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization »
Hanjun Dai · Mengjiao Yang · Yuan Xue · Dale Schuurmans · Bo Dai -
2022 Spotlight: Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization »
Hanjun Dai · Mengjiao Yang · Yuan Xue · Dale Schuurmans · Bo Dai -
2021 : Invited Speaker: Bo Dai: Leveraging Non-uniformity in Policy Gradient »
Bo Dai -
2021 Poster: Overcoming Catastrophic Forgetting by Bayesian Generative Regularization »
PEI-HUNG Chen · Wei Wei · Cho-Jui Hsieh · Bo Dai -
2021 Spotlight: Overcoming Catastrophic Forgetting by Bayesian Generative Regularization »
PEI-HUNG Chen · Wei Wei · Cho-Jui Hsieh · Bo Dai -
2021 Poster: LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs »
Hongyu Ren · Hanjun Dai · Bo Dai · Xinyun Chen · Michihiro Yasunaga · Haitian Sun · Dale Schuurmans · Jure Leskovec · Denny Zhou -
2021 Poster: Leveraging Non-uniformity in First-order Non-convex Optimization »
Jincheng Mei · Yue Gao · Bo Dai · Csaba Szepesvari · Dale Schuurmans -
2021 Spotlight: LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs »
Hongyu Ren · Hanjun Dai · Bo Dai · Xinyun Chen · Michihiro Yasunaga · Haitian Sun · Dale Schuurmans · Jure Leskovec · Denny Zhou -
2021 Spotlight: Leveraging Non-uniformity in First-order Non-convex Optimization »
Jincheng Mei · Yue Gao · Bo Dai · Csaba Szepesvari · Dale Schuurmans -
2021 Poster: A statistical perspective on distillation »
Aditya Menon · Ankit Singh Rawat · Sashank Jakkam Reddi · Seungyeon Kim · Sanjiv Kumar -
2021 Poster: Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces »
Ankit Singh Rawat · Aditya Menon · Wittawat Jitkrittum · Sadeep Jayasumana · Felix Xinnan Yu · Sashank Jakkam Reddi · Sanjiv Kumar -
2021 Spotlight: A statistical perspective on distillation »
Aditya Menon · Ankit Singh Rawat · Sashank Jakkam Reddi · Seungyeon Kim · Sanjiv Kumar -
2021 Spotlight: Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces »
Ankit Singh Rawat · Aditya Menon · Wittawat Jitkrittum · Sadeep Jayasumana · Felix Xinnan Yu · Sashank Jakkam Reddi · Sanjiv Kumar -
2021 Town Hall: Town Hall »
John Langford · Marina Meila · Tong Zhang · Le Song · Stefanie Jegelka · Csaba Szepesvari -
2021 Poster: On the Optimality of Batch Policy Optimization Algorithms »
Chenjun Xiao · Yifan Wu · Jincheng Mei · Bo Dai · Tor Lattimore · Lihong Li · Csaba Szepesvari · Dale Schuurmans -
2021 Spotlight: On the Optimality of Batch Policy Optimization Algorithms »
Chenjun Xiao · Yifan Wu · Jincheng Mei · Bo Dai · Tor Lattimore · Lihong Li · Csaba Szepesvari · Dale Schuurmans -
2020 Workshop: Bridge Between Perception and Reasoning: Graph Neural Networks & Beyond »
Jian Tang · Le Song · Jure Leskovec · Renjie Liao · Yujia Li · Sanja Fidler · Richard Zemel · Ruslan Salakhutdinov -
2020 : Opening Remarks: Jian Tang & Le Song »
Jian Tang · Le Song -
2020 Poster: Energy-Based Processes for Exchangeable Data »
Mengjiao Yang · Bo Dai · Hanjun Dai · Dale Schuurmans -
2020 Poster: Does label smoothing mitigate label noise? »
Michal Lukasik · Srinadh Bhojanapalli · Aditya Menon · Sanjiv Kumar -
2020 Poster: Low-Rank Bottleneck in Multi-head Attention Models »
Srinadh Bhojanapalli · Chulhee Yun · Ankit Singh Rawat · Sashank Jakkam Reddi · Sanjiv Kumar -
2020 Poster: Batch Stationary Distribution Estimation »
Junfeng Wen · Bo Dai · Lihong Li · Dale Schuurmans -
2020 Poster: Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search »
Binghong Chen · Chengtao Li · Hanjun Dai · Le Song -
2020 Poster: Accelerating Large-Scale Inference with Anisotropic Vector Quantization »
Ruiqi Guo · Philip Sun · Erik Lindgren · Quan Geng · David Simcha · Felix Chern · Sanjiv Kumar -
2020 Poster: Temporal Logic Point Processes »
Shuang Li · Lu Wang · Ruizhi Zhang · xiaofu Chang · Xuqin Liu · Yao Xie · Yuan Qi · Le Song -
2020 Poster: Learning To Stop While Learning To Predict »
Xinshi Chen · Hanjun Dai · Yu Li · Xin Gao · Le Song -
2020 Poster: Federated Learning with Only Positive Labels »
Felix Xinnan Yu · Ankit Singh Rawat · Aditya Menon · Sanjiv Kumar -
2020 Poster: Scalable Deep Generative Modeling for Sparse Graphs »
Hanjun Dai · Azade Nova · Yujia Li · Bo Dai · Dale Schuurmans -
2019 : Structured matrices for efficient deep learning »
Sanjiv Kumar -
2019 Poster: Escaping Saddle Points with Adaptive Gradient Methods »
Matthew Staib · Sashank Jakkam Reddi · Satyen Kale · Sanjiv Kumar · Suvrit Sra -
2019 Poster: Target-Based Temporal-Difference Learning »
Donghwan Lee · Niao He -
2019 Oral: Escaping Saddle Points with Adaptive Gradient Methods »
Matthew Staib · Sashank Jakkam Reddi · Satyen Kale · Sanjiv Kumar · Suvrit Sra -
2019 Oral: Target-Based Temporal-Difference Learning »
Donghwan Lee · Niao He -
2019 Poster: Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling »
Shanshan Wu · Alexandros Dimakis · Sujay Sanghavi · Felix Xinnan Yu · Daniel Holtmann-Rice · Dmitry Storcheus · Afshin Rostamizadeh · Sanjiv Kumar -
2019 Oral: Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling »
Shanshan Wu · Alexandros Dimakis · Sujay Sanghavi · Felix Xinnan Yu · Daniel Holtmann-Rice · Dmitry Storcheus · Afshin Rostamizadeh · Sanjiv Kumar -
2019 Poster: Particle Flow Bayes' Rule »
Xinshi Chen · Hanjun Dai · Le Song -
2019 Poster: Generative Adversarial User Model for Reinforcement Learning Based Recommendation System »
Xinshi Chen · Shuang Li · Hui Li · Shaohua Jiang · Yuan Qi · Le Song -
2019 Oral: Generative Adversarial User Model for Reinforcement Learning Based Recommendation System »
Xinshi Chen · Shuang Li · Hui Li · Shaohua Jiang · Yuan Qi · Le Song -
2019 Oral: Particle Flow Bayes' Rule »
Xinshi Chen · Hanjun Dai · Le Song -
2018 Poster: Adversarial Attack on Graph Structured Data »
Hanjun Dai · Hui Li · Tian Tian · Xin Huang · Lin Wang · Jun Zhu · Le Song -
2018 Poster: Loss Decomposition for Fast Learning in Large Output Spaces »
En-Hsu Yen · Satyen Kale · Felix Xinnan Yu · Daniel Holtmann-Rice · Sanjiv Kumar · Pradeep Ravikumar -
2018 Poster: Towards Black-box Iterative Machine Teaching »
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song -
2018 Poster: SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation »
Bo Dai · Albert Shaw · Lihong Li · Lin Xiao · Niao He · Zhen Liu · Jianshu Chen · Le Song -
2018 Oral: Towards Black-box Iterative Machine Teaching »
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song -
2018 Oral: Adversarial Attack on Graph Structured Data »
Hanjun Dai · Hui Li · Tian Tian · Xin Huang · Lin Wang · Jun Zhu · Le Song -
2018 Oral: Loss Decomposition for Fast Learning in Large Output Spaces »
En-Hsu Yen · Satyen Kale · Felix Xinnan Yu · Daniel Holtmann-Rice · Sanjiv Kumar · Pradeep Ravikumar -
2018 Oral: SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation »
Bo Dai · Albert Shaw · Lihong Li · Lin Xiao · Niao He · Zhen Liu · Jianshu Chen · Le Song -
2018 Poster: Learning to Explain: An Information-Theoretic Perspective on Model Interpretation »
Jianbo Chen · Le Song · Martin Wainwright · Michael Jordan -
2018 Poster: Stochastic Training of Graph Convolutional Networks with Variance Reduction »
Jianfei Chen · Jun Zhu · Le Song -
2018 Poster: Learning Steady-States of Iterative Algorithms over Graphs »
Hanjun Dai · Zornitsa Kozareva · Bo Dai · Alex Smola · Le Song -
2018 Oral: Stochastic Training of Graph Convolutional Networks with Variance Reduction »
Jianfei Chen · Jun Zhu · Le Song -
2018 Oral: Learning Steady-States of Iterative Algorithms over Graphs »
Hanjun Dai · Zornitsa Kozareva · Bo Dai · Alex Smola · Le Song -
2018 Oral: Learning to Explain: An Information-Theoretic Perspective on Model Interpretation »
Jianbo Chen · Le Song · Martin Wainwright · Michael Jordan -
2017 Poster: Variational Policy for Guiding Point Processes »
Yichen Wang · Grady Williams · Evangelos Theodorou · Le Song -
2017 Talk: Variational Policy for Guiding Point Processes »
Yichen Wang · Grady Williams · Evangelos Theodorou · Le Song -
2017 Poster: Distributed Mean Estimation with Limited Communication »
Ananda Theertha Suresh · Felix Xinnan Yu · Sanjiv Kumar · Brendan McMahan -
2017 Poster: Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs »
Rakshit Trivedi · Hanjun Dai · Yichen Wang · Le Song -
2017 Talk: Distributed Mean Estimation with Limited Communication »
Ananda Theertha Suresh · Felix Xinnan Yu · Sanjiv Kumar · Brendan McMahan -
2017 Talk: Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs »
Rakshit Trivedi · Hanjun Dai · Yichen Wang · Le Song -
2017 Poster: Fake News Mitigation via Point Process Based Intervention »
Mehrdad Farajtabar · Jiachen Yang · Xiaojing Ye · Huan Xu · Rakshit Trivedi · Elias Khalil · Shuang Li · Le Song · Hongyuan Zha -
2017 Poster: Iterative Machine Teaching »
Weiyang Liu · Bo Dai · Ahmad Humayun · Charlene Tay · Chen Yu · Linda Smith · James Rehg · Le Song -
2017 Talk: Iterative Machine Teaching »
Weiyang Liu · Bo Dai · Ahmad Humayun · Charlene Tay · Chen Yu · Linda Smith · James Rehg · Le Song -
2017 Talk: Fake News Mitigation via Point Process Based Intervention »
Mehrdad Farajtabar · Jiachen Yang · Xiaojing Ye · Huan Xu · Rakshit Trivedi · Elias Khalil · Shuang Li · Le Song · Hongyuan Zha