no code implementations • 9 Mar 2024 • Yang Peng, Liangyu Zhang, Zhihua Zhang
In the tabular case, \citet{rowland2018analysis} and \citet{rowland2023analysis} proved the asymptotic convergence of two instances of distributional TD, namely categorical temporal difference algorithm (CTD) and quantile temporal difference algorithm (QTD), respectively.
no code implementations • 10 Nov 2023 • Yang Peng
Object detection and tracking are vital and fundamental tasks for autonomous driving, aiming at identifying and locating objects from those predefined categories in a scene.
1 code implementation • 29 Sep 2023 • Liangyu Zhang, Yang Peng, Jiadong Liang, Wenhao Yang, Zhihua Zhang
This implies the distributional policy evaluation problem can be solved with sample efficiency.
Distributional Reinforcement Learning reinforcement-learning
no code implementations • 14 Sep 2023 • Syed Sha Qutub, Neslihan Kose, Rafael Rosales, Michael Paulitsch, Korbinian Hagn, Florian Geissler, Yang Peng, Gereon Hinz, Alois Knoll
The proposed loss functions in BEA improve the confidence score calibration and lower the uncertainty error, which results in a better distinction of true and false positives and, eventually, higher accuracy of the object detection models.
1 code implementation • 29 Apr 2023 • Liangyu Zhang, Yang Peng, Wenhao Yang, Zhihua Zhang
To the best of our knowledge, we are the first to apply tools from semi-infinitely programming (SIP) to solve constrained reinforcement learning problems.
no code implementations • 9 Jan 2023 • Yang Peng, Changzheng Liu, Wei Shen
Customer-centric marketing campaigns generate a large portion of e-commerce website traffic for Walmart.
no code implementations • 4 Dec 2022 • Yang Peng, Daisy Zhe Wang
Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge.
1 code implementation • 28 Nov 2022 • Xue Fu, Yang Peng, Yuchao Liu, Yun Lin, Guan Gui, Haris Gacanin, Fumiyuki Adachi
Specifically, pseudo labels are innovatively introduced into metric learning to enable semi-supervised metric learning (SSML), and an objective function alternatively regularized by SSML and virtual adversarial training (VAT) is designed to extract discriminative and generalized semantic features of radio signals.
no code implementations • 14 Nov 2022 • Yang Peng, Daisy Zhe Wang
Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge.
1 code implementation • 7 Sep 2022 • Syed Qutub, Florian Geissler, Yang Peng, Ralf Grafe, Michael Paulitsch, Gereon Hinz, Alois Knoll
The evaluation of several representative object detection models shows that even a single bit flip can lead to a severe silent data corruption event with potentially critical safety implications, with e. g., up to (much greater than) 100 FPs generated, or up to approx.
1 code implementation • 6 Apr 2022 • Hao Jin, Yang Peng, Wenhao Yang, Shusen Wang, Zhihua Zhang
We study a Federated Reinforcement Learning (FedRL) problem in which $n$ agents collaboratively learn a single policy without sharing the trajectories they collected during agent-environment interaction.
no code implementations • 28 Nov 2021 • Yang Peng, Ping Liu, Yawei Luo, Pan Zhou, Zichuan Xu, Jingen Liu
Unsupervised domain adaptive person re-identification has received significant attention due to its high practical value.
Domain Adaptive Person Re-Identification Person Re-Identification
no code implementations • 16 Aug 2021 • Florian Geissler, Syed Qutub, Sayanta Roychowdhury, Ali Asgari, Yang Peng, Akash Dhamasia, Ralf Graefe, Karthik Pattabiraman, Michael Paulitsch
Convolutional neural networks (CNNs) have become an established part of numerous safety-critical computer vision applications, including human robot interactions and automated driving.
no code implementations • 9 Oct 2020 • Jingan Yang, Yang Peng
To construct a robot that can walk as efficiently and steadily as humans or other legged animals, we develop an enhanced elitist-mutated ant colony optimization~(EACO) algorithm with genetic and crossover operators in real-time applications to humanoid robotics or other legged robots.
no code implementations • 11 Sep 2020 • Jingan Yang, Yang Peng
One of the ambitions of artificial intelligence is to root artificial intelligence deeply in basic science while developing brain-inspired artificial intelligence platforms that will promote new scientific discoveries.