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12/07/2021
A Unified Framework for Multi-distribution Density Ratio Estimation
Binary density ratio estimation (DRE), the problem of estimating the rat...
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07/31/2021
Manifold-Inspired Single Image Interpolation
Manifold models consider natural-image patches to be on a low-dimensiona...
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07/10/2021
Multi-Agent Imitation Learning with Copulas
Multi-agent imitation learning aims to train multiple agents to perform ...
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03/17/2021
Fast and High-Quality Blind Multi-Spectral Image Pansharpening
Blind pansharpening addresses the problem of generating a high spatial-r...
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01/20/2021
Quarter Laplacian Filter for Edge Aware Image Processing
This paper presents a quarter Laplacian filter that can preserve corners...
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01/20/2021
A Discrete Scheme for Computing Image's Weighted Gaussian Curvature
Weighted Gaussian Curvature is an important measurement for images. Howe...
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10/01/2020
Understanding Self-supervised Learning with Dual Deep Networks
We propose a novel theoretical framework to understand self-supervised l...
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07/12/2020
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation
Auto-regressive sequence generative models trained by Maximum Likelihood...
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05/27/2020
MOPO: Model-based Offline Policy Optimization
Offline reinforcement learning (RL) refers to the problem of learning po...
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04/03/2020
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip
Although Shannon theory states that it is asymptotically optimal to sepa...
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03/06/2020
Training Deep Energy-Based Models with f-Divergence Minimization
Deep energy-based models (EBMs) are very flexible in distribution parame...
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11/21/2019
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck
Domain adaptation aims to leverage the supervision signal of source doma...
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09/20/2019
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables
Providing a suitable reward function to reinforcement learning can be di...
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07/30/2019
Multi-Agent Adversarial Inverse Reinforcement Learning
Reinforcement learning agents are prone to undesired behaviors due to re...
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02/15/2019
Lipschitz Generative Adversarial Nets
In this paper we study the convergence of generative adversarial network...
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11/06/2018
Deep Reinforcement Learning for Green Security Games with Real-Time Information
Green Security Games (GSGs) have been proposed and applied to optimize p...
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07/02/2018
Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis
This paper aims to bring a new perspective for understanding GANs, by de...
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05/14/2018
Exploiting Data and Human Knowledge for Predicting Wildlife Poaching
Poaching continues to be a significant threat to the conservation of wil...
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04/11/2018
CoT: Cooperative Training for Generative Modeling
We propose Cooperative Training (CoT) for training generative models tha...
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09/13/2017
A Study of AI Population Dynamics with Million-agent Reinforcement Learning
We conduct an empirical study on discovering the ordered collective dyna...
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09/13/2017
An Empirical Study of AI Population Dynamics with Million-agent Reinforcement Learning
In this paper, we conduct an empirical study on discovering the ordered ...
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09/18/2016