b'Bo Dai'

Scene-aware Generative Network for Human Motion Synthesis

We revisit human motion synthesis, a task useful in various real world a...
05/31/2021 ∙ by Jingbo Wang, et al. ∙ 0 ∙ share

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Leveraging Non-uniformity in First-order Non-convex Optimization

Classical global convergence results for first-order methods rely on uni...
05/13/2021 ∙ by Jincheng Mei, et al. ∙ 14 ∙ share

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Unsupervised 3D Shape Completion through GAN Inversion

Most 3D shape completion approaches rely heavily on partial-complete sha...
04/27/2021 ∙ by Junzhe Zhang, et al. ∙ 12 ∙ share

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Visually Informed Binaural Audio Generation without Binaural Audios

Stereophonic audio, especially binaural audio, plays an essential role i...
04/13/2021 ∙ by Xudong Xu, et al. ∙ 0 ∙ share

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On the Optimality of Batch Policy Optimization Algorithms

Batch policy optimization considers leveraging existing data for policy ...
04/06/2021 ∙ by Chenjun Xiao, et al. ∙ 0 ∙ share

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Nearly Horizon-Free Offline Reinforcement Learning

We revisit offline reinforcement learning on episodic time-homogeneous t...
03/25/2021 ∙ by Tongzheng Ren, et al. ∙ 0 ∙ share

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Off-Policy Imitation Learning from Observations

Learning from Observations (LfO) is a practical reinforcement learning s...
02/25/2021 ∙ by Zhuangdi Zhu, et al. ∙ 0 ∙ share

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Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach

Reliable automatic evaluation of dialogue systems under an interactive e...
02/20/2021 ∙ by Haoming Jiang, et al. ∙ 8 ∙ share

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Focal Frequency Loss for Generative Models

Despite the remarkable success of generative models in creating photorea...
12/23/2020 ∙ by Liming Jiang, et al. ∙ 23 ∙ share

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Offline Policy Selection under Uncertainty

The presence of uncertainty in policy evaluation significantly complicat...
12/12/2020 ∙ by Mengjiao Yang, et al. ∙ 0 ∙ share

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Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration

Discrete structures play an important role in applications like program ...
11/10/2020 ∙ by Hanjun Dai, et al. ∙ 14 ∙ share

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Do 2D GANs Know 3D Shape? Unsupervised 3D shape reconstruction from 2D Image GANs

Natural images are projections of 3D objects on a 2D image plane. While ...
11/02/2020 ∙ by Xingang Pan, et al. ∙ 31 ∙ share

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Named Entity Recognition for Social Media Texts with Semantic Augmentation

Existing approaches for named entity recognition suffer from data sparsi...
10/29/2020 ∙ by Yuyang Nie, et al. ∙ 0 ∙ share

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CoinDICE: Off-Policy Confidence Interval Estimation

We study high-confidence behavior-agnostic off-policy evaluation in rein...
10/22/2020 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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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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Bo Dai

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