Risultati della ricerca - coding (algorithmics OR (algorithmics OR (algorithm OR Algorithmsssssics)))

NTIRE 2025 Challenge on UGC Video Enhancement: Methods and Results di Safonov, Nikolay, Bryncev, Alexey, Moskalenko, Andrey, Kulikov, Dmitry, Vatolin, Dmitry, Timofte, Radu, Lei, Haibo, Gao, Qifan, Luo, Qing, Li, Yaqing, Song, Jie, Hao, Shaozhe, Zheng, Meisong, Xu, Jingyi, Wu, Chengbin, Liu, Jiahui, Chen, Ying, Deng, Xin, Xu, Mai, Liang, Peipei, Ma, Jie, Jin, Junjie, Pang, Yingxue, Luo, Fangzhou, Chen, Kai, Zhao, Shijie, Wu, Mingyang, Li, Renjie, Zuo, Yushen, Zhong, Shengyun, Tu, Zhengzhong

Sommario: “... of the participants was to develop an algorithm capable of improving the visual quality of such videos. Given...”
Testo

An Optimization Framework for Wide-Field Small Aperture Telescope Arrays Used in Sky Surveys di Xiang, Wennan, Jia, Peng, Li, Zhengyang, Liu, Jifeng, Ying, Zhenyu, Bai, Zeyu

Sommario: “..., and an optimization algorithm, to balance the observation capabilities and the cost of optical telescope arrays...”
Testo

HyGenar: An LLM-Driven Hybrid Genetic Algorithm for Few-Shot Grammar Generation di Tang, Weizhi, Li, Yixuan, Sypherd, Chris, Polgreen, Elizabeth, Belle, Vaishak

Sommario: “...Grammar plays a critical role in natural language processing and text/code generation by enabling...”
Testo

Rethinking Direct Preference Optimization in Diffusion Models di Kang, Junyong, Lim, Seohyun, Baek, Kyungjune, Shim, Hyunjung

Sommario: “... problem across timesteps. Our method can be integrated into various preference optimization algorithms...”
Testo

BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL di Hung, Yu-Heng, Lin, Kai-Jie, Lin, Yu-Heng, Wang, Chien-Yi, Sun, Cheng, Hsieh, Ping-Chun

Sommario: “... algorithms in various synthetic MOBO and real-world multi-objective hyperparameter optimization problems. We...”
Testo

Joint Data Hiding and Partial Encryption of Compressive Sensed Streams di Popa, Cristina-Elena, Damian, Cristian, Coltuc, Daniela

Sommario: “... in protecting part of the measurements by a secret key and inserting the code into the rest. The secret key...”
Testo

To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers di Plaud, Roman, Perez-Lebel, Alexandre, Labeau, Matthieu, Saillenfest, Antoine, Bonald, Thomas

Sommario: “... algorithms when candidates are limited to the set of nodes. In the most general case of predicting a subset...”
Testo

The Impact of Feature Scaling In Machine Learning: Effects on Regression and Classification Tasks di Pinheiro, João Manoel Herrera, de Oliveira, Suzana Vilas Boas, Silva, Thiago Henrique Segreto, Saraiva, Pedro Antonio Rabelo, de Souza, Enzo Ferreira, Godoy, Ricardo V., Ambrosio, Leonardo André, Becker, Marcelo

Sommario: “... different Machine Learning algorithms and 16 datasets for classification and regression tasks. We...”
Testo

The Diffusion Duality di Sahoo, Subham Sekhar, Deschenaux, Justin, Gokaslan, Aaron, Wang, Guanghan, Chiu, Justin, Kuleshov, Volodymyr

Sommario: “... distillation from the continuous to the discrete setting. This algorithm unlocks few-step generation...”
Testo

An efficient construction of Raz's two-source randomness extractor with improved parameters di Foreman, Cameron, Wooltorton, Lewis, Milner, Kevin, Curchod, Florian J.

Sommario: “...Randomness extractors are algorithms that distill weak random sources into near-perfect random...”
Testo

Structured First-Layer Initialization Pre-Training Techniques to Accelerate Training Process Based on $\varepsilon$-Rank di Tang, Tao, Yang, Jiang, Zhao, Yuxiang, Zhu, Quanhui

Sommario: “... only need to add one line of code to conventional existing algorithms. ...”
Testo

An open dataset of neural networks for hypernetwork research di Kurtenbach, David, Shamir, Lior

Sommario: “... by supervised machine learning algorithms. The ultimate purpose of the dataset is to enable hypernetworks...”
Testo

FAST-Calib: LiDAR-Camera Extrinsic Calibration in One Second di Zheng, Chunran, Zhang, Fu

Sommario: “... by leveraging an efficient and reliable edge extraction algorithm that is agnostic to LiDAR scan patterns...”
Testo

Semi-Implicit Continuum Kinetic Modeling of Weakly Collisional Parallel Transport in a Magnetic Mirror di Dorf, M., Dorr, M., Geyko, V., Ghosh, D., Umansky, M., Angus, J.

Sommario: “... transport in magnetic mirror configurations using the continuum code \textsc{COGENT}. The numerical scheme...”
Testo

Quantum Semi-Random Forests for Qubit-Efficient Recommender Systems di Alavi, Azadeh, Kouchmeshki, Fatemeh, Alavi, Abdolrahman, Ren, Yongli, Niu, Jiayang

Sommario: “... close this gap with a three-stage hybrid machine learning algorithm that compresses tag profiles...”
Testo

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks di Noel, Molly, Mancino-Ball, Gabriel, Xu, Yangyang

Sommario: “... of theoretical guarantees or are missing important practical elements from modern deep learning algorithms...”
Testo

InqEduAgent: Adaptive AI Learning Partners with Gaussian Process Augmentation di Yang, Wen-Xi, Zhao, Tian-Fang, Liu, Guan, Yang, Liang, Liu, Zi-Tao, Chen, Wei-Neng

Sommario: “... and evaluative features of learners in real-world scenarios. Then, an adaptive matching algorithm with Gaussian...”
Testo

Mixed-Precision Performance Portability of FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices di Venkat, Sreeram, Swirydowicz, Kasia, Wolfe, Noah, Ghattas, Omar

Sommario: “... to adopt mixed-precision algorithms and performance portability models. We present an on-the-fly framework...”
Testo

Importance-Aware Robust Semantic Transmission for LEO Satellite-Ground Communication di Cao, Hui, Meng, Rui, Xu, Xiaodong, Han, Shujun, Zhang, Ping

Sommario: “... model enhancement algorithm to improve the granularity and accuracy of semantic segmentation...”
Testo

UniSino: Physics-Driven Foundational Model for Universal CT Sinogram Standardization di Ai, Xingyu, Wang, Shaoyu, Jia, Zhiyuan, Xu, Ao, Shan, Hongming, Ma, Jianhua, Liu, Qiegen

Sommario: “... diagnostic accuracy. Conventional correction methods rely on manually designed algorithms or fixed empirical...”
Testo