Search Results for author: Min Chen

Found 71 papers, 24 papers with code

SoK: Dataset Copyright Auditing in Machine Learning Systems

no code implementations22 Oct 2024 Linkang Du, Xuanru Zhou, Min Chen, Chusong Zhang, Zhou Su, Peng Cheng, Jiming Chen, Zhikun Zhang

As the implementation of machine learning (ML) systems becomes more widespread, especially with the introduction of larger ML models, we perceive a spring demand for massive data.

TA3: Testing Against Adversarial Attacks on Machine Learning Models

no code implementations6 Oct 2024 Yuanzhe Jin, Min Chen

Adversarial attacks are major threats to the deployment of machine learning (ML) models in many applications.

iGAiVA: Integrated Generative AI and Visual Analytics in a Machine Learning Workflow for Text Classification

1 code implementation24 Sep 2024 Yuanzhe Jin, Adrian Carrasco-Revilla, Min Chen

In developing machine learning (ML) models for text classification, one common challenge is that the collected data is often not ideally distributed, especially when new classes are introduced in response to changes of data and tasks.

text-classification Text Classification

STAA: Spatio-Temporal Alignment Attention for Short-Term Precipitation Forecasting

no code implementations6 Sep 2024 Min Chen, Hao Yang, Shaohan Li, Xiaolin Qin

There is a great need to accurately predict short-term precipitation, which has socioeconomic effects such as agriculture and disaster prevention.

Precipitation Forecasting

More Text, Less Point: Towards 3D Data-Efficient Point-Language Understanding

1 code implementation28 Aug 2024 Yuan Tang, Xu Han, Xianzhi Li, Qiao Yu, Jinfeng Xu, Yixue Hao, Long Hu, Min Chen

To address this task, we introduce GreenPLM, which leverages more text data to compensate for the lack of 3D data.

Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations

no code implementations12 Aug 2024 Jian Xu, Zhiqi Lin, Min Chen, Junmei Yang, Delu Zeng, John Paisley

Traditional deep Gaussian processes model the data evolution using a discrete hierarchy, whereas differential Gaussian processes (DIFFGPs) represent the evolution as an infinitely deep Gaussian process.

Bayesian Inference Gaussian Processes

Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling

no code implementations7 Aug 2024 Jian Xu, Zhiqi Lin, Shigui Li, Min Chen, Junmei Yang, Delu Zeng, John Paisley

Bayesian Last Layer (BLL) models focus solely on uncertainty in the output layer of neural networks, demonstrating comparable performance to more complex Bayesian models.

Computational Efficiency Out-of-Distribution Detection +1

DACB-Net: Dual Attention Guided Compact Bilinear Convolution Neural Network for Skin Disease Classification

no code implementations3 Jul 2024 Belal Ahmad, Mohd Usama, Tanvir Ahmad, Adnan Saeed, Shabnam Khatoon, Min Chen

This paper introduces the three-branch Dual Attention-Guided Compact Bilinear CNN (DACB-Net) by focusing on learning from disease-specific regions to enhance accuracy and alignment.

Data Augmentation Transfer Learning

Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition

no code implementations22 Jun 2024 Kai Shao, Rui Wang, Yixue Hao, Long Hu, Min Chen, Hans Arno Jacobsen

Furthermore, to enhance the learning of semantic representation associated with stimulation tasks, a semantic consistency contrast module is proposed, aiming to maximize the semantic similarity of fNIRS and EEG.

Data Augmentation EEG +3

PointDreamer: Zero-shot 3D Textured Mesh Reconstruction from Colored Point Cloud by 2D Inpainting

1 code implementation22 Jun 2024 Qiao Yu, Xianzhi Li, Yuan Tang, Jinfeng Xu, Long Hu, Yixue Hao, Min Chen

Addressing this, we propose PointDreamer, a novel framework for textured mesh reconstruction from colored point cloud.

Image Inpainting

Graph External Attention Enhanced Transformer

1 code implementation31 May 2024 Jianqing Liang, Min Chen, Jiye Liang

The Transformer architecture has recently gained considerable attention in the field of graph representation learning, as it naturally overcomes several limitations of Graph Neural Networks (GNNs) with customized attention mechanisms or positional and structural encodings.

Graph Representation Learning

Enhancing Interaction Modeling with Agent Selection and Physical Coefficient for Trajectory Prediction

1 code implementation21 May 2024 Shiji Huang, Lei Ye, Min Chen, Wenhai Luo, Dihong Wang, Chenqi Xu, Deyuan Liang

A thorough understanding of the interaction between the target agent and surrounding agents is a prerequisite for accurate trajectory prediction.

Autonomous Driving Trajectory Prediction

MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors

1 code implementation2 May 2024 Yuan Tang, Xu Han, Xianzhi Li, Qiao Yu, Yixue Hao, Long Hu, Min Chen

Notably, MiniGPT-3D gains an 8. 12 increase on GPT-4 evaluation score for the challenging object captioning task compared to ShapeLLM-13B, while the latter costs 160 total GPU-hours on 8 A800.

3D Object Captioning Generative 3D Object Classification +1

Efficient Multi-Task Reinforcement Learning via Task-Specific Action Correction

no code implementations9 Apr 2024 Jinyuan Feng, Min Chen, Zhiqiang Pu, Tenghai Qiu, Jianqiang Yi

Multi-task reinforcement learning (MTRL) demonstrate potential for enhancing the generalization of a robot, enabling it to perform multiple tasks concurrently.

reinforcement-learning Reinforcement Learning

PDF: A Probability-Driven Framework for Open World 3D Point Cloud Semantic Segmentation

1 code implementation CVPR 2024 Jinfeng Xu, Siyuan Yang, Xianzhi Li, Yuan Tang, Yixue Hao, Long Hu, Min Chen

Existing point cloud semantic segmentation networks cannot identify unknown classes and update their knowledge, due to a closed-set and static perspective of the real world, which would induce the intelligent agent to make bad decisions.

Decoder Knowledge Distillation +2

Prioritized League Reinforcement Learning for Large-Scale Heterogeneous Multiagent Systems

no code implementations26 Mar 2024 Qingxu Fu, Zhiqiang Pu, Min Chen, Tenghai Qiu, Jianqiang Yi

Furthermore, we design a prioritized policy gradient approach to compensate for the gap caused by differences in the number of different types of agents.

reinforcement-learning Reinforcement Learning

Feature-Action Design Patterns for Storytelling Visualizations with Time Series Data

no code implementations5 Feb 2024 Saiful Khan, Scott Jones, Benjamin Bach, Jaehoon Cha, Min Chen, Julie Meikle, Jonathan C Roberts, Jeyan Thiyagalingam, Jo Wood, Panagiotis D. Ritsos

Motivated initially by the need to communicate time series data during the COVID-19 pandemic, we developed a novel computer-assisted method for meta-authoring of stories, which enables the design of storyboards that include feature-action patterns in anticipation of potential features that may appear in dynamically arrived or selected data.

Time Series

Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys

1 code implementation18 Jan 2024 Yong Cao, Min Chen, Daniel Hershcovich

The cultural landscape of interactions with dialogue agents is a compelling yet relatively unexplored territory.

Dialogue Generation

Image Similarity using An Ensemble of Context-Sensitive Models

1 code implementation15 Jan 2024 Zukang Liao, Min Chen

In this work, we present a more intuitive approach to build and compare image similarity models based on labelled data in the form of A:R vs B:R, i. e., determining if an image A is closer to a reference image R than another image B.

Dimensionality Reduction Semantic Similarity +1

Multi-task deep learning for large-scale building detail extraction from high-resolution satellite imagery

1 code implementation29 Oct 2023 Zhen Qian, Min Chen, Zhuo Sun, Fan Zhang, Qingsong Xu, Jinzhao Guo, Zhiwei Xie, Zhixin Zhang

Understanding urban dynamics and promoting sustainable development requires comprehensive insights about buildings.

ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning

1 code implementation6 Sep 2023 Linkang Du, Min Chen, Mingyang Sun, Shouling Ji, Peng Cheng, Jiming Chen, Zhikun Zhang

In safety-critical domains such as autonomous vehicles, offline deep reinforcement learning (offline DRL) is frequently used to train models on pre-collected datasets, as opposed to training these models by interacting with the real-world environment as the online DRL.

Autonomous Vehicles Deep Reinforcement Learning +2

Geo-Encoder: A Chunk-Argument Bi-Encoder Framework for Chinese Geographic Re-Ranking

1 code implementation4 Sep 2023 Yong Cao, Ruixue Ding, Boli Chen, Xianzhi Li, Min Chen, Daniel Hershcovich, Pengjun Xie, Fei Huang

Chinese geographic re-ranking task aims to find the most relevant addresses among retrieved candidates, which is crucial for location-related services such as navigation maps.

Chunking Multi-Task Learning +1

LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors

1 code implementation26 Aug 2023 Chengkun Wei, Wenlong Meng, Zhikun Zhang, Min Chen, Minghu Zhao, Wenjing Fang, Lei Wang, Zihui Zhang, Wenzhi Chen

Instead of directly inverting the triggers, LMSanitator aims to invert the predefined attack vectors (pretrained models' output when the input is embedded with triggers) of the task-agnostic backdoors, which achieves much better convergence performance and backdoor detection accuracy.

Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio Masking

1 code implementation IEEE Transactions on Multimedia 2023 Yuan Tang, Xianzhi Li, Jinfeng Xu, Qiao Yu, Long Hu, Yixue Hao, Min Chen

In our work, we present Point-LGMask, a novel method to embed both local and global contexts with multi-ratio masking, which is quite effective for self-supervised feature learning of point clouds but is unfortunately ignored by existing pre-training works.

3D Object Detection 3D Semantic Segmentation +3

DPMLBench: Holistic Evaluation of Differentially Private Machine Learning

1 code implementation10 May 2023 Chengkun Wei, Minghu Zhao, Zhikun Zhang, Min Chen, Wenlong Meng, Bo Liu, Yuan Fan, Wenzhi Chen

We also explore some improvements that can maintain model utility and defend against MIAs more effectively.

Image Classification

Pay More Attention to Relation Exploration for Knowledge Base Question Answering

no code implementations3 May 2023 Yong Cao, Xianzhi Li, Huiwen Liu, Wen Dai, Shuai Chen, Bin Wang, Min Chen, Daniel Hershcovich

In this study, we propose a novel framework, RE-KBQA, that utilizes relations in the knowledge base to enhance entity representation and introduce additional supervision.

Knowledge Base Question Answering Relation +1

FACE-AUDITOR: Data Auditing in Facial Recognition Systems

2 code implementations5 Apr 2023 Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Yang Zhang

Few-shot-based facial recognition systems have gained increasing attention due to their scalability and ability to work with a few face images during the model deployment phase.

Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study

1 code implementation30 Mar 2023 Yong Cao, Li Zhou, Seolhwa Lee, Laura Cabello, Min Chen, Daniel Hershcovich

The recent release of ChatGPT has garnered widespread recognition for its exceptional ability to generate human-like responses in dialogue.

Cultural Vocal Bursts Intensity Prediction Diversity

Boundary Unlearning

no code implementations21 Mar 2023 Min Chen, Weizhuo Gao, Gaoyang Liu, Kai Peng, Chen Wang

In this paper, we refocus our attention from the parameter space to the decision space of the DNN model, and propose Boundary Unlearning, a rapid yet effective way to unlearn an entire class from a trained DNN model.

Face Recognition Image Classification +1

Enhancing Vital Sign Estimation Performance of FMCW MIMO Radar by Prior Human Shape Recognition

no code implementations16 Mar 2023 Hadi Alidoustaghdam, Min Chen, Ben Willetts, Kai Mao, André Kokkeler, Yang Miao

Additionally, human's random body movements deteriorate the estimation of breathing and heart rates, therefore the information of the chest location and a narrow radar beam toward the chest are demanded for more accurate vital sign estimation.

Urban Visual Intelligence: Studying Cities with AI and Street-level Imagery

no code implementations2 Jan 2023 Fan Zhang, Arianna Salazar Miranda, Fábio Duarte, Lawrence Vale, Gary Hack, Min Chen, Yu Liu, Michael Batty, Carlo Ratti

The visual dimension of cities has been a fundamental subject in urban studies, since the pioneering work of scholars such as Sitte, Lynch, Arnheim, and Jacobs.

Boundary Unlearning: Rapid Forgetting of Deep Networks via Shifting the Decision Boundary

no code implementations CVPR 2023 Min Chen, Weizhuo Gao, Gaoyang Liu, Kai Peng, Chen Wang

In this paper, we refocus our attention from the parameter space to the decision space of the DNN model, and propose Boundary Unlearning, a rapid yet effective way to unlearn an entire class from a trained DNN model.

Face Recognition Image Classification +1

CasFusionNet: A Cascaded Network for Point Cloud Semantic Scene Completion by Dense Feature Fusion

2 code implementations24 Nov 2022 Jinfeng Xu, Xianzhi Li, Yuan Tang, Qiao Yu, Yixue Hao, Long Hu, Min Chen

In our work, we present CasFusionNet, a novel cascaded network for point cloud semantic scene completion by dense feature fusion.

Segmentation Semantic Segmentation

Background Invariance Testing According to Semantic Proximity

no code implementations19 Aug 2022 Zukang Liao, Pengfei Zhang, Min Chen

This ontology enables (i) efficient and meaningful search for background scenes of different semantic distances to a target image, (ii) quantitative control of the distribution and sparsity of the sampled background scenes, and (iii) quality assurance using visual representations of invariance testing results (referred to as variance matrices).

Object Recognition

Finding MNEMON: Reviving Memories of Node Embeddings

no code implementations14 Apr 2022 Yun Shen, Yufei Han, Zhikun Zhang, Min Chen, Ting Yu, Michael Backes, Yang Zhang, Gianluca Stringhini

Previous security research efforts orbiting around graphs have been exclusively focusing on either (de-)anonymizing the graphs or understanding the security and privacy issues of graph neural networks.

Graph Embedding

Explore More Guidance: A Task-aware Instruction Network for Sign Language Translation Enhanced with Data Augmentation

1 code implementation Findings (NAACL) 2022 Yong Cao, Wei Li, Xianzhi Li, Min Chen, Guangyong Chen, Long Hu, Zhengdao Li, Hwang Kai

Sign language recognition and translation first uses a recognition module to generate glosses from sign language videos and then employs a translation module to translate glosses into spoken sentences.

Data Augmentation Sign Language Recognition +2

Semi-Supervised Adversarial Recognition of Refined Window Structures for Inverse Procedural Façade Modeling

no code implementations22 Jan 2022 Han Hu, Xinrong Liang, Yulin Ding, Qisen Shang, Bo Xu, Xuming Ge, Min Chen, Ruofei Zhong, Qing Zhu

Unfortunately, the large amount of interactive sample labeling efforts has dramatically hindered the application of deep learning methods, especially for 3D modeling tasks, which require heterogeneous samples.

Generative Adversarial Network

Visualizing Ensemble Predictions of Music Mood

no code implementations14 Dec 2021 Zelin Ye, Min Chen

Music mood classification has been a challenging problem in comparison with other music classification problems (e. g., genre, composer, or period).

Music Classification

Inference Attacks Against Graph Neural Networks

1 code implementation6 Oct 2021 Zhikun Zhang, Min Chen, Michael Backes, Yun Shen, Yang Zhang

Second, given a subgraph of interest and the graph embedding, we can determine with high confidence that whether the subgraph is contained in the target graph.

Graph Classification Graph Embedding +2

Deep Fraud Detection on Non-attributed Graph

no code implementations4 Oct 2021 Chen Wang, Yingtong Dou, Min Chen, Jia Chen, Zhiwei Liu, Philip S. Yu

The successes of most previous methods heavily rely on rich node features and high-fidelity labels.

Contrastive Learning Fraud Detection

ML4ML: Automated Invariance Testing for Machine Learning Models

1 code implementation27 Sep 2021 Zukang Liao, Pengfei Zhang, Min Chen

In this paper, we show that testing the invariance qualities of ML models may result in complex visual patterns that cannot be classified using simple formulas.

BIG-bench Machine Learning

A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things

no code implementations21 Apr 2021 Jiehan Zhou, Shouhua Zhang, Qinghua Lu, Wenbin Dai, Min Chen, Xin Liu, Susanna Pirttikangas, Yang Shi, Weishan Zhang, Enrique Herrera-Viedma

Federated learning (FL) brings collaborative intelligence into industries without centralized training data to accelerate the process of Industry 4. 0 on the edge computing level.

Edge-computing Federated Learning +1

Simulation-Based Optimization of User Interfaces for Quality-Assuring Machine Learning Model Predictions

no code implementations2 Apr 2021 Yu Zhang, Martijn Tennekes, Tim De Jong, Lyana Curier, Bob Coecke, Min Chen

QA for ML (QA4ML) interfaces require users to view a large amount of data and perform many interactions to correct errors made by the ML model.

Graph Unlearning

1 code implementation27 Mar 2021 Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang

In this paper, we propose GraphEraser, a novel machine unlearning framework tailored to graph data.

Machine Unlearning

A Bounded Measure for Estimating the Benefit of Visualization: Case Studies and Empirical Evaluation

no code implementations3 Mar 2021 Min Chen, Alfie Abdul-Rahman, Deborah Silver, Mateu Sbert

The recently-proposed information-theoretic measure for analyzing the cost-benefit ratio of visualization processes can explain such usefulness experienced in practice, and postulate that the viewers' knowledge can reduce the potential distortion (e. g., misinterpretation) due to information loss.

Human-Computer Interaction Graphics Information Theory Information Theory

A Bounded Measure for Estimating the Benefit of Visualization: Theoretical Discourse and Conceptual Evaluation

no code implementations3 Mar 2021 Min Chen, Mateu Sbert

We examine a number of bounded measures that include the Jenson-Shannon divergence and a new divergence measure formulated as part of this work.

Information Theory Graphics Human-Computer Interaction Information Theory

NeRF--: Neural Radiance Fields Without Known Camera Parameters

5 code implementations14 Feb 2021 ZiRui Wang, Shangzhe Wu, Weidi Xie, Min Chen, Victor Adrian Prisacariu

Considering the problem of novel view synthesis (NVS) from only a set of 2D images, we simplify the training process of Neural Radiance Field (NeRF) on forward-facing scenes by removing the requirement of known or pre-computed camera parameters, including both intrinsics and 6DoF poses.

Novel View Synthesis

Study on multi-fold bunch splitting in a high-intensity medium-energy proton synchrotron

no code implementations3 Feb 2021 Linhao Zhang, Min Chen, Jingyu Tang

Bunch splitting is an RF manipulation method of changing the bunch structure, bunch numbers and bunch intensity in the high-intensity synchrotrons that serve as the injector for a particle collider.

Accelerator Physics

Depth-Enhanced Feature Pyramid Network for Occlusion-Aware Verification of Buildings from Oblique Images

no code implementations26 Nov 2020 Qing Zhu, Shengzhi Huang, Han Hu, Haifeng Li, Min Chen, Ruofei Zhong

Finally, multi-view information from both the nadir and oblique images is used in a robust voting procedure to label changes in existing buildings.

DeepNetQoE: Self-adaptive QoE Optimization Framework of Deep Networks

no code implementations17 Jul 2020 Rui Wang, Min Chen, Nadra Guizani, Yong Li, Hamid Gharavi, Kai Hwang

A self-adaptive QoE model is set up that relates the model's accuracy with the computing resources required for training which will allow the experience value of the model to improve.

Crowd Counting

When Machine Unlearning Jeopardizes Privacy

1 code implementation5 May 2020 Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang

More importantly, we show that our attack in multiple cases outperforms the classical membership inference attack on the original ML model, which indicates that machine unlearning can have counterproductive effects on privacy.

Inference Attack Machine Unlearning +1

A Bounded Measure for Estimating the Benefit of Visualization

no code implementations12 Feb 2020 Min Chen, Mateu Sbert, Alfie Abdul-Rahman, Deborah Silver

Information theory can be used to analyze the cost-benefit of visualization processes.

HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models

no code implementations12 Feb 2020 Qianwen Wang, William Alexander, Jack Pegg, Huamin Qu, Min Chen

In this paper, we present a visual analytics tool for enabling hypothesis-based evaluation of machine learning (ML) models.

BIG-bench Machine Learning Logical Reasoning +1

Feature-level and Model-level Audiovisual Fusion for Emotion Recognition in the Wild

no code implementations6 Jun 2019 Jie Cai, Zibo Meng, Ahmed Shehab Khan, Zhiyuan Li, James O'Reilly, Shizhong Han, Ping Liu, Min Chen, Yan Tong

In this paper, we proposed two strategies to fuse information extracted from different modalities, i. e., audio and visual.

Emotion Recognition

Hierarchical Reinforcement Learning for Multi-agent MOBA Game

no code implementations23 Jan 2019 Zhijian Zhang, Haozheng Li, Luo Zhang, Tianyin Zheng, Ting Zhang, Xiong Hao, Xiaoxin Chen, Min Chen, Fangxu Xiao, Wei Zhou

Real Time Strategy (RTS) games require macro strategies as well as micro strategies to obtain satisfactory performance since it has large state space, action space, and hidden information.

Hierarchical Reinforcement Learning Imitation Learning +4

Wearable Affective Robot

no code implementations25 Oct 2018 Min Chen, Jun Zhou, Guangming Tao, Jun Yang, Long Hu

The learning algorithm for the life modeling embedded in Fitbot can achieve better user's experience of affective social interaction.

Electroencephalogram (EEG) Human-Computer Interaction

Background Subtraction using Compressed Low-resolution Images

no code implementations24 Oct 2018 Min Chen, Andy Song, Shivanthan A. C. Yhanandan, Jing Zhang

The essential first step involved in almost all the visual tasks is background subtraction with a static camera.

In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning

no code implementations19 Sep 2018 Xiaofei Wang, Yiwen Han, Chenyang Wang, Qiyang Zhao, Xu Chen, Min Chen

In order to bring more intelligence to the edge systems, compared to traditional optimization methodology, and driven by the current deep learning techniques, we propose to integrate the Deep Reinforcement Learning techniques and Federated Learning framework with the mobile edge systems, for optimizing the mobile edge computing, caching and communication.

Deep Reinforcement Learning Edge-computing +1

Collimated GeV attosecond electron-positron bunches from a plasma channel driven by 10 PW lasers

no code implementations1 Aug 2018 Xing-Long Zhu, Zheng-Ming Sheng, Min Chen, Tong-Pu Yu, Su-Ming Weng

High-energy positrons and bright {\gamma}-ray sources are unique both for fundamental research and practical applications.

Plasma Physics

Trust-Aware Decision Making for Human-Robot Collaboration: Model Learning and Planning

no code implementations12 Jan 2018 Min Chen, Stefanos Nikolaidis, Harold Soh, David Hsu, Siddhartha Srinivasa

The trust-POMDP model provides a principled approach for the robot to (i) infer the trust of a human teammate through interaction, (ii) reason about the effect of its own actions on human trust, and (iii) choose actions that maximize team performance over the long term.

Decision Making

Detecting Small Signs from Large Images

no code implementations26 Jun 2017 Zibo Meng, Xiaochuan Fan, Xin Chen, Min Chen, Yan Tong

Experimental results on a real-world conditioned traffic sign dataset have demonstrated the effectiveness of the proposed method in terms of detection accuracy and recall, especially for those with small sizes.

Object object-detection +1

Brain Intelligence: Go Beyond Artificial Intelligence

no code implementations4 Jun 2017 Huimin Lu, Yujie Li, Min Chen, Hyoungseop Kim, Seiichi Serikawa

Specifically, we plan to develop an intelligent learning model called Brain Intelligence (BI) that generates new ideas about events without having experienced them by using artificial life with an imagine function.

Artificial Life Industrial Robots

Underwater Optical Image Processing: A Comprehensive Review

no code implementations13 Feb 2017 Huimin Lu, Yujie Li, Yudong Zhang, Min Chen, Seiichi Serikawa, Hyoungseop Kim

This paper aims to review the state-of-the-art techniques in underwater image processing by highlighting the contributions and challenges presented in over 40 papers.

POMDP-lite for Robust Robot Planning under Uncertainty

no code implementations16 Feb 2016 Min Chen, Emilio Frazzoli, David Hsu, Wee Sun Lee

We show that a POMDP-lite is equivalent to a set of fully observable Markov decision processes indexed by a hidden parameter and is useful for modeling a variety of interesting robotic tasks.

Reinforcement Learning Reinforcement Learning (RL)

Service-Oriented Architectures and Web Services: Course Tutorial and Lab Notes

no code implementations17 Jul 2009 Serguei A. Mokhov, Shahriar Rostami, Hammad Ali, Min Chen, Yuhong Yan

This document presents a number of quick-step instructions to get started on writing mini-service-oriented web services-based applications using OpenESB 2. 31, Tomcat 6, GlassFish 2. x/3. 0. 1 with BPEL support, and Java 1. 6+ primarily in Scientific Linux 6. 6 with user quota restrictions.

Distributed, Parallel, and Cluster Computing Software Engineering 68N15, 68U35 H.3.5; C.2.4; D.1.3

Cannot find the paper you are looking for? You can Submit a new open access paper.