AI Agent - arXivDaily 专题

2304.01725 2023-04-05 cs.SE 57%

A Static Analysis Platform for Investigating Security Trends in Repositories

Tim Sonnekalb, Christopher-Tobias Knaust, Bernd Gruner, Clemens-Alexander Brust, Lynn von Kurnatowski, Andreas Schreiber, Thomas S. Heinze, Patrick Mäder

专题命中工作流自动化：workflow(abstract)；分类 cs.SE

2304.01701 2023-04-05 cs.LG cs.SY eess.SY 57%

Optimal Transport for Correctional Learning

Rebecka Winqvist, Inês Lourenco, Francesco Quinzan, Cristian R. Rojas, Bo Wahlberg

专题命中工作流自动化：agent(abstract)；分类 cs.LG

2212.12207 2023-04-05 cs.CE cs.LG math.OC 57%

Investigation of reinforcement learning for shape optimization of profile extrusion dies

Clemens Fricke, Daniel Wolff, Marco Kemmerling, Stefanie Elgeti

专题命中工作流自动化：agent(abstract)；分类 cs.LG

Comments 35 pages, 21 figures, submitted to Advances in Computational Science and Engineering (ACSE)

2304.01086 2023-04-04 cs.NE cs.LG 57%

Self-building Neural Networks

Andrea Ferigo, Giovanni Iacca

专题命中工作流自动化：agent(abstract)；分类 cs.LG

Comments To appear in the Genetic and Evolutionary Computation Conference Companion (GECCO '23 Companion) Proceedings, July 15--19, 2023, Lisbon, Portugal

2206.14649 2023-03-30 cs.IR cs.LG 57%

Cooperative Retriever and Ranker in Deep Recommenders

Xu Huang, Defu Lian, Jin Chen, Zheng Liu, Xing Xie, Enhong Chen

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

Comments 12pages, 4 figures, WWW'23

2303.13531 2023-03-27 cs.AI 57%

Discovering Hierarchical Process Models: an Approach Based on Events Clustering

Antonina K. Begicheva, Irina A. Lomazova, Roman A. Nesterov

专题命中工作流自动化：workflow(abstract)；分类 cs.AI

2302.01574 2023-03-27 cs.LG 57%

An Operational Perspective to Fairness Interventions: Where and How to Intervene

Brian Hsu, Xiaotong Chen, Ying Han, Hongseok Namkoong, Kinjal Basu

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

2303.11191 2023-03-21 cs.LG 57%

A Survey of Demonstration Learning

André Correia, Luís A. Alexandre

专题命中工作流自动化：agent(abstract)；分类 cs.LG

Comments 35 pages, 9 figures

2303.10732 2023-03-21 cs.LG 57%

AutoEn: An AutoML method based on ensembles of predefined Machine Learning pipelines for supervised Traffic Forecasting

Juan S. Angarita-Zapata, Antonio D. Masegosa, Isaac Triguero

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

2302.05738 2023-03-21 cs.LG 57%

Cross-Modal Fine-Tuning: Align then Refine

Junhong Shen, Liam Li, Lucio M. Dery, Corey Staten, Mikhail Khodak, Graham Neubig, Ameet Talwalkar

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

2210.14287 2023-03-21 cs.LG 57%

Combined Data and Deep Learning Model Uncertainties: An Application to the Measurement of Solid Fuel Regression Rate

Georgios Georgalis, Kolos Retfalvi, Paul E. DesJardin, Abani Patra

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

2303.09438 2023-03-17 cs.CL cs.SD eess.AS 57%

Trustera: A Live Conversation Redaction System

Evandro Gouvêa, Ali Dadgar, Shahab Jalalvand, Rathi Chengalvarayan, Badrinath Jayakumar, Ryan Price, Nicholas Ruiz, Jennifer McGovern, Srinivas Bangalore, Ben Stern

专题命中工作流自动化：agent(abstract)；分类 cs.CL

Comments 5

2002.12435 2023-03-16 cs.LG math.OC stat.ML 57%

Learning in Markov Decision Processes under Constraints

Rahul Singh, Abhishek Gupta, Ness B. Shroff

专题命中工作流自动化：agent(abstract)；分类 cs.LG

Journal ref IEEE Transactions on Control of Network Systems, 31 August 2022

1907.01932 2023-03-15 cs.RO cs.AI 57%

Action Prediction in Humans and Robots

Florentin Wörgötter, Fatemeh Ziaeetabar, Stefan Pfeiffer, Osman Kaya, Tomas Kulvicius, Minija Tamosiunaite

专题命中工作流自动化：workflow(abstract)；分类 cs.AI

Journal ref Scientific Reports, 2020

2303.06269 2023-03-14 cs.LG 57%

DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record

Conor K. Corbin, Rob Maclay, Aakash Acharya, Sreedevi Mony, Soumya Punnathanam, Rahul Thapa, Nikesh Kotecha, Nigam H. Shah, Jonathan H. Chen

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

2302.12862 2023-03-14 cs.LG cs.DC 57%

FLINT: A Platform for Federated Learning Integration

Ewen Wang, Ajay Kannan, Yuefeng Liang, Boyi Chen, Mosharaf Chowdhury

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

Comments Preprint for MLSys 2023

2302.07160 2023-03-14 cs.LG 57%

Learning a model is paramount for sample efficiency in reinforcement learning control of PDEs

Stefan Werner, Sebastian Peitz

专题命中工作流自动化：agent(abstract)；分类 cs.LG

2303.05545 2023-03-13 cs.LG 57%

Position Paper on Dataset Engineering to Accelerate Science

Emilio Vital Brazil, Eduardo Soares, Lucas Villa Real, Leonardo Azevedo, Vinicius Segura, Luiz Zerkowski, Renato Cerqueira

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

Comments Published at 2nd Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE) https://ai-2-ase.github.io/papers/16%5cSubmission%5cAAAI_Dataset_Engineering-8.pdf

2303.04084 2023-03-08 cs.SE 57%

Developers' Perception of GitHub Actions: A Survey Analysis

Sk Golam Saroar, Maleknaz Nayebi

专题命中工作流自动化：workflow(abstract)；分类 cs.SE

Comments Authors preprint version

Journal ref EASE 2023

2303.03511 2023-03-08 cs.HC cs.AI 57%

Applying Artificial Intelligence to Clinical Decision Support in Mental Health: What Have We Learned?

Grace Golden, Christina Popescu, Sonia Israel, Kelly Perlman, Caitrin Armstrong, Robert Fratila, Myriam Tanguay-Sela, David Benrimoh

专题命中工作流自动化：workflow(abstract)；分类 cs.AI

2211.06822 2023-03-07 physics.med-ph cs.CV cs.LG 57%

Deep Learning-enabled Virtual Histological Staining of Biological Samples

Bijie Bai, Xilin Yang, Yuzhu Li, Yijie Zhang, Nir Pillar, Aydogan Ozcan

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

Comments 35 Pages, 7 Figures, 2 Tables

Journal ref Light: Science & Applications (2023)

2201.06093 2023-03-07 cs.CR cs.LG 57%

Adversarial Machine Learning Threat Analysis and Remediation in Open Radio Access Network (O-RAN)

Edan Habler, Ron Bitton, Dan Avraham, Dudu Mimran, Eitan Klevansky, Oleg Brodt, Heiko Lehmann, Yuval Elovici, Asaf Shabtai

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

2303.01429 2023-03-03 cs.LG 57%

Optimal transfer protocol by incremental layer defrosting

Federica Gerace, Diego Doimo, Stefano Sarao Mannelli, Luca Saglietti, Alessandro Laio

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

2203.05570 2023-03-01 physics.data-an cs.LG hep-ex hep-ph 57%

neos: End-to-End-Optimised Summary Statistics for High Energy Physics

Nathan Simpson, Lukas Heinrich

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

Comments 6 pages, 3 figures, Proceedings of the 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021)

2302.13198 2023-02-28 cs.SE 57%

Automated and Systematic Digital Twins Testing for Industrial Processes

Yunpeng Ma, Khalil Younis, Bestoun S. Ahmed, Andreas Kassler, Pavel Krakhmalev, Andreas Thore, Hans Lindback

专题命中工作流自动化：agent(abstract)；分类 cs.SE

Comments The paper accepted for publication in The 7th International Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems (ITEQS)

2206.14506 2023-02-27 cs.AI 57%

An extension of process calculus for asynchronous communications between agents with epistemic states

Huili Xing

专题命中工作流自动化：agent(abstract)；分类 cs.AI

Comments 22 pages and 2 figures

2302.11703 2023-02-24 cs.LG cs.CV cs.HC 57%

fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks

Steven Moore, Q. Vera Liao, Hariharan Subramonyam

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

2210.07278 2023-02-22 stat.ML cs.LG 57%

Meta-Uncertainty in Bayesian Model Comparison

Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner

专题命中工作流自动化：workflow(abstract)；分类 cs.LG

Comments accepted at AISTATS 2023

2302.08738 2023-02-20 cs.RO cs.AI 57%

Exploiting Unlabeled Data for Feedback Efficient Human Preference based Reinforcement Learning

Mudit Verma, Siddhant Bhambri, Subbarao Kambhampati

专题命中工作流自动化：agent(abstract)；分类 cs.AI

Comments R2HCAI, AAAI 2023

2104.08196 2023-02-16 cs.LG 57%

Towards Standardising Reinforcement Learning Approaches for Production Scheduling Problems

Alexandru Rinciog, Anne Meyer

专题命中工作流自动化：agent(abstract)；分类 cs.LG

Journal ref Procedia CIRP 107 (2022): 1112-1119

1. 工作流自动化 10514 篇

A Static Analysis Platform for Investigating Security Trends in Repositories

Optimal Transport for Correctional Learning

Investigation of reinforcement learning for shape optimization of profile extrusion dies

Self-building Neural Networks

Cooperative Retriever and Ranker in Deep Recommenders

Discovering Hierarchical Process Models: an Approach Based on Events Clustering

An Operational Perspective to Fairness Interventions: Where and How to Intervene

A Survey of Demonstration Learning

AutoEn: An AutoML method based on ensembles of predefined Machine Learning pipelines for supervised Traffic Forecasting

Cross-Modal Fine-Tuning: Align then Refine

Combined Data and Deep Learning Model Uncertainties: An Application to the Measurement of Solid Fuel Regression Rate

Trustera: A Live Conversation Redaction System

Learning in Markov Decision Processes under Constraints

Action Prediction in Humans and Robots

DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record

FLINT: A Platform for Federated Learning Integration

Learning a model is paramount for sample efficiency in reinforcement learning control of PDEs

Position Paper on Dataset Engineering to Accelerate Science

Developers' Perception of GitHub Actions: A Survey Analysis

Applying Artificial Intelligence to Clinical Decision Support in Mental Health: What Have We Learned?

Deep Learning-enabled Virtual Histological Staining of Biological Samples

Adversarial Machine Learning Threat Analysis and Remediation in Open Radio Access Network (O-RAN)

Optimal transfer protocol by incremental layer defrosting

neos: End-to-End-Optimised Summary Statistics for High Energy Physics

Automated and Systematic Digital Twins Testing for Industrial Processes

An extension of process calculus for asynchronous communications between agents with epistemic states

fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks

Meta-Uncertainty in Bayesian Model Comparison

Exploiting Unlabeled Data for Feedback Efficient Human Preference based Reinforcement Learning

Towards Standardising Reinforcement Learning Approaches for Production Scheduling Problems