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09/18/2023
Survey of Consciousness Theory from Computational Perspective
Human consciousness has been a long-lasting mystery for centuries, while...
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04/10/2023
Learning a Universal Human Prior for Dexterous Manipulation from Human Preference
Generating human-like behavior on robots is a great challenge especially...
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03/10/2023
Object-Aware Distillation Pyramid for Open-Vocabulary Object Detection
Open-vocabulary object detection aims to provide object detectors traine...
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01/06/2023
Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane Detection
Monocular 3D lane detection is a challenging task due to its lack of dep...
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08/11/2022
PPMN: Pixel-Phrase Matching Network for One-Stage Panoptic Narrative Grounding
Panoptic Narrative Grounding (PNG) is an emerging task whose goal is to ...
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07/18/2022
A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games
This paper proposes novel, end-to-end deep reinforcement learning algori...
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06/08/2022
Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation
Referring video object segmentation aims to predict foreground labels fo...
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06/03/2022
Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game
This paper investigates the network load balancing problem in data cente...
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01/27/2022
Multi-Agent Reinforcement Learning for Network Load Balancing in Data Center
This paper presents the network load balancing problem, a challenging re...
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10/29/2021
Reinforced Workload Distribution Fairness
Network load balancers are central components in data centers, that dist...
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09/28/2021
Not Only Domain Randomization: Universal Policy with Embedding System Identification
Domain randomization (DR) cannot provide optimal policies for adapting t...
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05/14/2021
Collaborative Spatial-Temporal Modeling for Language-Queried Video Actor Segmentation
Language-queried video actor segmentation aims to predict the pixel-leve...
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04/19/2021
Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning
Deep reinforcement learning (DRL) has successfully solved various proble...
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03/07/2021
Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos
Learning an accurate model of the environment is essential for model-bas...
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02/28/2021
Sim-to-Real Transfer for Robotic Manipulation with Tactile Sensory
Reinforcement Learning (RL) methods have been widely applied for robotic...
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02/22/2021
DROID: Minimizing the Reality Gap using Single-Shot Human Demonstration
Reinforcement learning (RL) has demonstrated great success in the past s...
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11/15/2020
CDT: Cascading Decision Trees for Explainable Reinforcement Learning
Deep Reinforcement Learning (DRL) has recently achieved significant adva...
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09/18/2020
RLzoo: A Comprehensive and Adaptive Reinforcement Learning Library
Recently, we have seen a rapidly growing adoption of Deep Reinforcement ...
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08/15/2020
Crossing The Gap: A Deep Dive into Zero-Shot Sim-to-Real Transfer for Dynamics
Zero-shot sim-to-real transfer of tasks with complex dynamics is a highl...
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03/31/2020
Sim-to-Real Transfer for Optical Tactile Sensing
Deep learning and reinforcement learning methods have been shown to enab...
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05/17/2019
Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence
Learning agents that are not only capable of taking tests but also innov...
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01/28/2019
TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation
Deep generative models have been successfully applied to many applicatio...
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12/03/2018
