Bo Dai

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Google ∙ Georgia Institute of Technology ∙ The Chinese University of Hong Kong

Research Assistant, Ph.D. Candidate at Georgia Institute of Technology

Off-Policy Evaluation via the Regularized Lagrangian

The recently proposed distribution correction estimation (DICE) family o...
07/07/2020 ∙ by Mengjiao Yang, et al. ∙ 4 ∙ share

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Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach

Structural equation models (SEMs) are widely used in sciences, ranging f...
07/02/2020 ∙ by Luofeng Liao, et al. ∙ 13 ∙ share

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Unsupervised Landmark Learning from Unpaired Data

Recent attempts for unsupervised landmark learning leverage synthesized ...
06/29/2020 ∙ by Yinghao Xu, et al. ∙ 14 ∙ share

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Scalable Deep Generative Modeling for Sparse Graphs

Learning graph generative models is a challenging task for deep learning...
06/28/2020 ∙ by Hanjun Dai, et al. ∙ 8 ∙ share

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Video Representation Learning with Visual Tempo Consistency

Visual tempo, which describes how fast an action goes, has shown its pot...
06/28/2020 ∙ by Ceyuan Yang, et al. ∙ 3 ∙ share

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Novel Policy Seeking with Constrained Optimization

In this work, we address the problem of learning to seek novel policies ...
05/21/2020 ∙ by Hao Sun, et al. ∙ 6 ∙ share

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Evolutionary Stochastic Policy Distillation

Solving the Goal-Conditioned Reward Sparse (GCRS) task is a challenging ...
04/27/2020 ∙ by Hao Sun, et al. ∙ 9 ∙ share

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Temporal Pyramid Network for Action Recognition

Visual tempo characterizes the dynamics and the temporal scale of an act...
04/07/2020 ∙ by Ceyuan Yang, et al. ∙ 21 ∙ share

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Self-Supervised Scene De-occlusion

Natural scene understanding is a challenging task, particularly when enc...
04/06/2020 ∙ by Xiaohang Zhan, et al. ∙ 37 ∙ share

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Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations

Model-free deep reinforcement learning (RL) has demonstrated its superio...
04/01/2020 ∙ by Zhuangdi Zhu, et al. ∙ 5 ∙ share

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Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation

Learning a good image prior is a long-term goal for image restoration an...
03/30/2020 ∙ by Xingang Pan, et al. ∙ 0 ∙ share

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Energy-Based Processes for Exchangeable Data

Recently there has been growing interest in modeling sets with exchangea...
03/17/2020 ∙ by Mengjiao Yang, et al. ∙ 0 ∙ share

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Batch Stationary Distribution Estimation

We consider the problem of approximating the stationary distribution of ...
03/02/2020 ∙ by Junfeng Wen, et al. ∙ 7 ∙ share

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GenDICE: Generalized Offline Estimation of Stationary Values

An important problem that arises in reinforcement learning and Monte Car...
02/21/2020 ∙ by Ruiyi Zhang, et al. ∙ 11 ∙ share

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Differentiable Top-k Operator with Optimal Transport

The top-k operation, i.e., finding the k largest or smallest elements fr...
02/16/2020 ∙ by Yujia Xie, et al. ∙ 6 ∙ share

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Real or Not Real, that is the Question

While generative adversarial networks (GAN) have been widely adopted in ...
02/12/2020 ∙ by Yuanbo Xiangli, et al. ∙ 15 ∙ share

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Reinforcement Learning via Fenchel-Rockafellar Duality

We review basic concepts of convex duality, focusing on the very general...
01/07/2020 ∙ by Ofir Nachum, et al. ∙ 0 ∙ share

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Retrosynthesis Prediction with Conditional Graph Logic Network

Retrosynthesis is one of the fundamental problems in organic chemistry. ...
01/06/2020 ∙ by Hanjun Dai, et al. ∙ 6 ∙ share

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AlgaeDICE: Policy Gradient from Arbitrary Experience

In many real-world applications of reinforcement learning (RL), interact...
12/04/2019 ∙ by Ofir Nachum, et al. ∙ 0 ∙ share

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Overcoming Catastrophic Forgetting by Generative Regularization

In this paper, we propose a new method to overcome catastrophic forgetti...
12/03/2019 ∙ by Patrick H. Chen, et al. ∙ 0 ∙ share

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Energy-Inspired Models: Learning with Sampler-Induced Distributions

Energy-based models (EBMs) are powerful probabilistic models, but suffer...
10/31/2019 ∙ by Dieterich Lawson, et al. ∙ 18 ∙ share

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Recursive Visual Sound Separation Using Minus-Plus Net

Sounds provide rich semantics, complementary to visual data, for many ta...
08/30/2019 ∙ by Xudong Xu, et al. ∙ 3 ∙ share

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DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections

In many real-world reinforcement learning applications, access to the en...
06/10/2019 ∙ by Ofir Nachum, et al. ∙ 0 ∙ share

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Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification

We propose a new approach, called cooperative neural networks (CoNN), wh...
06/01/2019 ∙ by Harsh Shrivastava, et al. ∙ 0 ∙ share

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Exponential Family Estimation via Adversarial Dynamics Embedding

We present an efficient algorithm for maximum likelihood estimation (MLE...
04/27/2019 ∙ by Bo Dai, et al. ∙ 28 ∙ share

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Feature Intertwiner for Object Detection

A well-trained model should classify objects with a unanimous score for ...
03/28/2019 ∙ by Hongyang Li, et al. ∙ 0 ∙ share

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Learning to Plan via Neural Exploration-Exploitation Trees

Sampling-based algorithms such as RRT and its variants are powerful tool...
02/28/2019 ∙ by Binghong Chen, et al. ∙ 0 ∙ share

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Bayesian Meta-network Architecture Learning

For deep neural networks, the particular structure often plays a vital r...
12/22/2018 ∙ by Albert Shaw, et al. ∙ 0 ∙ share

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Kernel Exponential Family Estimation via Doubly Dual Embedding

We investigate penalized maximum log-likelihood estimation for exponenti...
11/06/2018 ∙ by Bo Dai, et al. ∙ 4 ∙ share

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Learning to Defense by Learning to Attack

Adversarial training provides a principled approach for training robust ...
11/03/2018 ∙ by Zhehui Chen, et al. ∙ 0 ∙ share

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A Neural Compositional Paradigm for Image Captioning

Mainstream captioning models often follow a sequential structure to gene...
10/23/2018 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Neural Network Encapsulation

A capsule is a collection of neurons which represents different variants...
08/11/2018 ∙ by Hongyang Li, et al. ∙ 0 ∙ share

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Move Forward and Tell: A Progressive Generator of Video Descriptions

We present an efficient framework that can generate a coherent paragraph...
07/26/2018 ∙ by Yilei Xiong, et al. ∙ 2 ∙ share

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Rethinking the Form of Latent States in Image Captioning

RNNs and their variants have been widely adopted for image captioning. I...
07/26/2018 ∙ by Bo Dai, et al. ∙ 10 ∙ share

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Learning Deep Hidden Nonlinear Dynamics from Aggregate Data

Learning nonlinear dynamics from diffusion data is a challenging problem...
07/22/2018 ∙ by Yisen Wang, et al. ∙ 0 ∙ share

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Learning towards Minimum Hyperspherical Energy

Neural networks are a powerful class of nonlinear functions that can be ...
05/23/2018 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Decoupled Networks

Inner product-based convolution has been a central component of convolut...
04/22/2018 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Syntax-Directed Variational Autoencoder for Structured Data

Deep generative models have been enjoying success in modeling continuous...
02/24/2018 ∙ by Hanjun Dai, et al. ∙ 0 ∙ share

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Smoothed Dual Embedding Control

We revisit the Bellman optimality equation with Nesterov's smoothing tec...
12/29/2017 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Boosting the Actor with Dual Critic

This paper proposes a new actor-critic-style algorithm called Dual Actor...
12/29/2017 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Deep Hyperspherical Learning

Convolution as inner product has been the founding basis of convolutiona...
11/08/2017 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Towards Black-box Iterative Machine Teaching

In this paper, we make an important step towards the black-box machine t...
10/21/2017 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Contrastive Learning for Image Captioning

Image captioning, a popular topic in computer vision, has achieved subst...
10/06/2017 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Iterative Machine Teaching

In this paper, we consider the problem of machine teaching, the inverse ...
05/30/2017 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Detecting Visual Relationships with Deep Relational Networks

Relationships among objects play a crucial role in image understanding. ...
04/11/2017 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Towards Diverse and Natural Image Descriptions via a Conditional GAN

Despite the substantial progress in recent years, the image captioning t...
03/17/2017 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Stochastic Generative Hashing

Learning-based binary hashing has become a powerful paradigm for fast se...
01/11/2017 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Learning from Conditional Distributions via Dual Embeddings

Many machine learning tasks, such as learning with invariance and policy...
07/15/2016 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Provable Bayesian Inference via Particle Mirror Descent

Bayesian methods are appealing in their flexibility in modeling complex ...
06/09/2015 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Scalable Kernel Methods via Doubly Stochastic Gradients

The general perception is that kernel methods are not scalable, and neur...
07/21/2014 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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Bo Dai

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