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05/25/2023
Asking Before Action: Gather Information in Embodied Decision Making with Language Models
With strong capabilities of reasoning and a generic understanding of the...
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03/26/2023
Dynamic Game of the Dual-Channel Supply Chain Under a Carbon Subsidy Policy
This study investigates the dynamic game behaviors of dual-channel suppl...
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02/17/2023
Deep Implicit Distribution Alignment Networks for Cross-Corpus Speech Emotion Recognition
In this paper, we propose a novel deep transfer learning method called d...
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12/24/2022
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context
One of the key challenges in deploying RL to real-world applications is ...
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08/18/2022
An Improved Multi-Stage Preconditioner on GPUs for Compositional Reservoir Simulation
The compositional model is often used to describe multicomponent multiph...
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07/18/2022
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation
Deep reinforcement learning (DRL) has attracted much attention in automa...
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05/25/2022
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
We propose a new learning framework that captures the tiered structure o...
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02/14/2022
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
Deployment efficiency is an important criterion for many real-world appl...
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01/06/2022
Parallel Multi-Stage Preconditioners with Adaptive Setup for the Black Oil Model
The black oil model is widely used to describe multiphase porous media f...
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12/23/2021
ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
Pre-trained language models have achieved state-of-the-art results in va...
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11/03/2021
Curriculum Offline Imitation Learning
Offline reinforcement learning (RL) tasks require the agent to learn fro...
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10/27/2021
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning
Behavioral cloning has proven to be effective for learning sequential de...
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10/26/2021
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions
A growing trend for value-based reinforcement learning (RL) algorithms i...
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02/22/2021
Return-Based Contrastive Representation Learning for Reinforcement Learning
Recently, various auxiliary tasks have been proposed to accelerate repre...
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11/07/2020
A Multi-stream Convolutional Neural Network for Micro-expression Recognition Using Optical Flow and EVM
Micro-expression (ME) recognition plays a crucial role in a wide range o...
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09/30/2020
Transfer Learning from Speech Synthesis to Voice Conversion with Non-Parallel Training Data
This paper presents a novel framework to build a voice conversion (VC) s...
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07/04/2020
Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge
To better understand early brain growth patterns in health and disorder,...
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03/30/2020
Suphx: Mastering Mahjong with Deep Reinforcement Learning
Artificial Intelligence (AI) has achieved great success in many domains,...
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02/20/2020
A Vision of C-V2X: Technologies, Field Testing and Challenges with Chinese Development
C-V2X (Cellular Vehicle-to-Everything) is the important enabling technol...
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11/06/2019
Distributional Reward Decomposition for Reinforcement Learning
Many reinforcement learning (RL) tasks have specific properties that can...
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11/05/2019
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Distributional Reinforcement Learning (RL) differs from traditional RL i...
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08/24/2018
Reinforcement Learning for Relation Classification from Noisy Data
Existing relation classification methods that rely on distant supervisio...
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04/20/2017
Adversarial Neural Machine Translation
In this paper, we study a new learning paradigm for Neural Machine Trans...
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05/07/2013
Somoclu: An Efficient Parallel Library for Self-Organizing Maps
Somoclu is a massively parallel tool for training self-organizing maps o...
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06/04/2009