Zobrazeno 1 - 10
of 31 058
pro vyhledávání: '"Swamy A"'
Publikováno v:
Journal of Engineering Management and Competitiveness, Vol 13, Iss 2, Pp 127-139 (2023)
The present study uses the Analytic Hierarchy Process and Fuzzy Comprehensive method to evaluate the sustainable performance index with different sustainable dimensions on organisational performance measures. Limited integration methods available, in
Externí odkaz:
https://doaj.org/article/1c89575880fe44fe8bc0f7ad9e7e6c16
Autor:
Swamy, Vinitra, Romano, Davide, Desikan, Bhargav Srinivasa, Camburu, Oana-Maria, Käser, Tanja
Recent advances in eXplainable AI (XAI) for education have highlighted a critical challenge: ensuring that explanations for state-of-the-art AI models are understandable for non-technical users such as educators and students. In response, we introduc
Externí odkaz:
http://arxiv.org/abs/2409.08027
We consider the {\em correlated knapsack orienteering} (CSKO) problem: we are given a travel budget $B$, processing-time budget $W$, finite metric space $(V,d)$ with root $\rho\in V$, where each vertex is associated with a job with possibly correlate
Externí odkaz:
http://arxiv.org/abs/2408.16566
Autor:
Guan, Hong, Wang, Yancheng, Xie, Lulu, Nag, Soham, Goel, Rajeev, Swamy, Niranjan Erappa Narayana, Yang, Yingzhen, Xiao, Chaowei, Prisby, Jonathan, Maciejewski, Ross, Zou, Jia
Effective fraud detection and analysis of government-issued identity documents, such as passports, driver's licenses, and identity cards, are essential in thwarting identity theft and bolstering security on online platforms. The training of accurate
Externí odkaz:
http://arxiv.org/abs/2408.01690
Recent advancements in deep learning (DL) have significantly advanced medical image analysis. In the field of medical image processing, particularly in histopathology image analysis, the variation in staining protocols and differences in scanners pre
Externí odkaz:
http://arxiv.org/abs/2406.15685
Often times in imitation learning (IL), the environment we collect expert demonstrations in and the environment we want to deploy our learned policy in aren't exactly the same (e.g. demonstrations collected in simulation but deployment in the real wo
Externí odkaz:
http://arxiv.org/abs/2406.11905
Graph partitioning (GP) and vertex connectivity have traditionally been two distinct fields of study. This paper introduces the highly connected graph partitioning (HCGP) problem, which partitions a graph into compact, size balanced, and $Q$-(vertex)
Externí odkaz:
http://arxiv.org/abs/2406.08329
We study a multi-agent imitation learning (MAIL) problem where we take the perspective of a learner attempting to coordinate a group of agents based on demonstrations of an expert doing so. Most prior work in MAIL essentially reduces the problem to m
Externí odkaz:
http://arxiv.org/abs/2406.04219
Learning from human preference data has emerged as the dominant paradigm for fine-tuning large language models (LLMs). The two most common families of techniques -- online reinforcement learning (RL) such as Proximal Policy Optimization (PPO) and off
Externí odkaz:
http://arxiv.org/abs/2406.01462
Autor:
Gado, Elena Grazia, Martorella, Tommaso, Zunino, Luca, Mejia-Domenzain, Paola, Swamy, Vinitra, Frej, Jibril, Käser, Tanja
Intelligent Tutoring Systems (ITS) enhance personalized learning by predicting student answers to provide immediate and customized instruction. However, recent research has primarily focused on the correctness of the answer rather than the student's
Externí odkaz:
http://arxiv.org/abs/2405.20079