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09/13/2023
On the Local Quadratic Stability of T-S Fuzzy Systems in the Vicinity of the Origin
The main goal of this paper is to introduce new local stability conditio...
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07/31/2023
Distributed Dynamic Programming forNetworked Multi-Agent Markov Decision Processes
The main goal of this paper is to investigate distributed dynamic progra...
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06/16/2023
Temporal Difference Learning with Experience Replay
Temporal-difference (TD) learning is widely regarded as one of the most ...
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06/09/2023
Finite-Time Analysis of Minimax Q-Learning for Two-Player Zero-Sum Markov Games: Switching System Approach
The objective of this paper is to investigate the finite-time analysis o...
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03/27/2023
TMO: Textured Mesh Acquisition of Objects with a Mobile Device by using Differentiable Rendering
We present a new pipeline for acquiring a textured mesh in the wild with...
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02/20/2023
Backstepping Temporal Difference Learning
Off-policy learning ability is an important feature of reinforcement lea...
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08/10/2022
Block Double-Submission Attack: Block Withholding Can Be Self-Destructive
Proof-of-Work (PoW) is a Sybil control mechanism adopted in blockchain-b...
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07/25/2022
Finite-Time Analysis of Asynchronous Q-learning under Diminishing Step-Size from Control-Theoretic View
Q-learning has long been one of the most popular reinforcement learning ...
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05/31/2022
Investigating the Role of Image Retrieval for Visual Localization – An exhaustive benchmark
Visual localization, i.e., camera pose estimation in a known scene, is a...
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04/22/2022
Analysis of Temporal Difference Learning: Linear System Approach
The goal of this technical note is to introduce a new finite-time conver...
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03/13/2022
A Single Correspondence Is Enough: Robust Global Registration to Avoid Degeneracy in Urban Environments
Global registration using 3D point clouds is a crucial technology for mo...
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03/10/2022
SelfTune: Metrically Scaled Monocular Depth Estimation through Self-Supervised Learning
Monocular depth estimation in the wild inherently predicts depth up to a...
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02/11/2022
Regularized Q-learning
Q-learning is widely used algorithm in reinforcement learning community....
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12/29/2021
Control Theoretic Analysis of Temporal Difference Learning
The goal of this paper is to investigate a control theoretic analysis of...
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09/09/2021
Versions of Gradient Temporal Difference Learning
Sutton, Szepesvári and Maei introduced the first gradient temporal-diffe...
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08/12/2021
DnD: Dense Depth Estimation in Crowded Dynamic Indoor Scenes
We present a novel approach for estimating depth from a monocular camera...
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05/19/2021
Large-scale Localization Datasets in Crowded Indoor Spaces
Estimating the precise location of a camera using visual localization en...
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03/14/2021
Simulation Studies on Deep Reinforcement Learning for Building Control with Human Interaction
The building sector consumes the largest energy in the world, and there ...
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02/17/2021
Finite-Time Error Analysis of Asynchronous Q-Learning with Discrete-Time Switching System Models
This paper develops a novel framework to analyze the convergence of Q-le...
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11/10/2020
SelfDeco: Self-Supervised Monocular Depth Completion in Challenging Indoor Environments
We present a novel algorithm for self-supervised monocular depth complet...
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10/06/2020
SAFENet: Self-Supervised Monocular Depth Estimation with Semantic-Aware Feature Extraction
Self-supervised monocular depth estimation has emerged as a promising me...
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06/25/2020
HARMer: Cyber-attacks Automation and Evaluation
With the increasing growth of cyber-attack incidences, it is important t...
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02/23/2020
Periodic Q-Learning
The use of target networks is a common practice in deep reinforcement le...
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12/04/2019
A Unified Switching System Perspective and O.D.E. Analysis of Q-Learning Algorithms
In this paper, we introduce a unified framework for analyzing a large fa...
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12/01/2019
Optimization for Reinforcement Learning: From Single Agent to Cooperative Agents
This article reviews recent advances in multi-agent reinforcement learni...
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04/24/2019
Target-Based Temporal Difference Learning
The use of target networks has been a popular and key component of recen...
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12/13/2018
Learning to Communicate: A Machine Learning Framework for Heterogeneous Multi-Agent Robotic Systems
We present a machine learning framework for multi-agent systems to learn...
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09/17/2018
