Application Proficiency
Application proficiency focuses on optimizing the performance and efficiency of algorithms and models across diverse applications, aiming to improve accuracy, speed, and resource utilization. Current research emphasizes developing robust methods for handling model uncertainties and constraints, often employing Bayesian optimization, metaheuristics, and deep learning architectures like convolutional neural networks and transformers. This field is crucial for advancing various domains, from real-time control systems and fraud detection to personalized medicine and environmental monitoring, by enabling the effective deployment of sophisticated computational tools.
Papers
Contrastive Perplexity for Controlled Generation: An Application in Detoxifying Large Language Models
Tassilo Klein, Moin Nabi
Application of LLM Agents in Recruitment: A Novel Framework for Resume Screening
Chengguang Gan, Qinghao Zhang, Tatsunori Mori
Modeling Spoof Noise by De-spoofing Diffusion and its Application in Face Anti-spoofing
Bin Zhang, Xiangyu Zhu, Xiaoyu Zhang, Zhen Lei
No-Clean-Reference Image Super-Resolution: Application to Electron Microscopy
Mohammad Khateri, Morteza Ghahremani, Alejandra Sierra, Jussi Tohka
Block Majorization Minimization with Extrapolation and Application to $\beta$-NMF
Le Thi Khanh Hien, Valentin Leplat, Nicolas Gillis
Application Of Vision-Language Models For Assessing Osteoarthritis Disease Severity
Banafshe Felfeliyan, Yuyue Zhou, Shrimanti Ghosh, Jessica Kupper, Shaobo Liu, Abhilash Hareendranathan, Jacob L. Jaremko
Phase discovery with active learning: Application to structural phase transitions in equiatomic NiTi
Jonathan Vandermause, Anders Johansson, Yucong Miao, Joost J. Vlassak, Boris Kozinsky
Deep learning in motion deblurring: current status, benchmarks and future prospects
Yawen Xiang, Heng Zhou, Chengyang Li, Fangwei Sun, Zhongbo Li, Yongqiang Xie
Rethinking Test-time Likelihood: The Likelihood Path Principle and Its Application to OOD Detection
Sicong Huang, Jiawei He, Kry Yik Chau Lui
Optimal Real-Weighted Beamforming With Application to Linear and Spherical Arrays
V. Tourbabin, M. Agmon, B. Rafaely, J. Tabrikian
Two-Stage Surrogate Modeling for Data-Driven Design Optimization with Application to Composite Microstructure Generation
Farhad Pourkamali-Anaraki, Jamal F. Husseini, Evan J. Pineda, Brett A. Bednarcyk, Scott E. Stapleton