Risultati della ricerca - distributed evolution (algorithm OR Algorithmssics)

AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems di Xue, Zhenghai, Cai, Qingpeng, Yang, Bin, Hu, Lantao, Jiang, Peng, Gai, Kun, An, Bo

Sommario: “... is the environment non-stationarity stemming from the continual and complex evolution of user behavior patterns over...”
Testo

A hybrid quantum walk model unifying discrete and continuous quantum walks di Chen, Tianen, Shang, Yun

Sommario: “... the coin mechanism of discrete walks with the Hamiltonian-driven time evolution of continuous walks...”
Testo

Backtracking Bipolar Magnetic Regions to their emergence: Two groups and their implication in the tilt measurements di Sreedevi, Anu, Karak, Bidya Binay, Jha, Bibhuti Kumar, Gupta, Rambahadur, Banerjee, Dipankar

Sommario: “... substantial growth during their evolution, the instances where our algorithm fails to capture the initial...”
Testo

Adaptive Data Selection for Multi-Layer Perceptron Training: A Sub-linear Value-Driven Method di Zhang, Xiyang, Liang, Chen, Qiu, Haoxuan, Wang, Hongzhi

Sommario: “... and selecting data for MLP training that accounts for the dynamic evolution of network parameters during...”
Testo

Detect and Act: Automated Dynamic Optimizer through Meta-Black-Box Optimization di Gao, Zijian, Zhong, Yuanting, Ma, Zeyuan, Gong, Yue-Jiao, Guo, Hongshu

Sommario: “... since they resemble dynamic biological evolution. However, existing evolutionary dynamic optimization...”
Testo

Euclid preparation. XXXI. The effect of the variations in photometric passbands on photometric-redshift accuracy di Euclid Collaboration, Paltani, Stéphane, Coupon, J., Hartley, W. G., Alvarez-Ayllon, A., Dubath, F., Mohr, J. J., Schirmer, M., Cuillandre, J. -C., Desprez, G., Ilbert, O., Kuijken, K., Aghanim, N., Altieri, B., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Douspis, M., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Haugan, S. V., Hoekstra, H., Hornstrup, A., Hudelot, P., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Masters, D. C., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J., Padilla, C., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespí, P., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Aussel, H., Bardelli, S., Bolzonella, M., Boucaud, A., Di Ferdinando, D., Farina, M., Graciá-Carpio, J., Lindholm, V., Maino, D., Mauri, N., Neissner, C., Scottez, V., Zucca, E., Baccigalupi, C., Ballardini, M., Biviano, A., Blanchard, A., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Chambers, K., Cooray, A. R., Courtois, H. M., Cucciati, O., Davini, S., De Lucia, G., Dole, H., Escartin, J. A., Escoffier, S., Finelli, F., Fotopoulou, S., Ganga, K., George, K., Gozaliasl, G., Hildebrandt, H., Hook, I., Muñoz, A. Jimenez, Joachimi, B., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Pollack, J. E., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pozzetti, L., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Sefusatti, E., Sereno, M., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Teyssier, R., Valieri, C., Valiviita, J., van Mierlo, S. E., Veropalumbo, A., Viel, M., Weaver, J. R.

Sommario: “... extragalactic surveys. While the requirements on photo-zs for the study of galaxy evolution mostly pertain...”
Testo

Accelerating FRB Search: Dataset and Methods di Guo, Xuerong, Wang, Han, Xiao, Yifan, Chen, Huaxi, Ke, Yinan, Miao, ChenChen, Wang, Pei, Li, Di, Jin, Chenwu, He, Ling, Feng, Yi, Zhang, Yongkun, Xu, Jiaying, Chen, Guangyong

Sommario: “... in studying the distribution and evolution of matter in the universe. FRBs can only be observed through radio...”
Testo

Invariance principle and McKean-Vlasov limit for randomized load balancing in heavy traffic di Atar, Rami, Wolansky, Gershon

Sommario: “... servers whose service time distribution possesses a finite second moment. A small fraction of arrivals...”
Testo

Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training di Hu, Pihe, Li, Shaolong, Li, Zhuoran, Pan, Ling, Huang, Longbo

Sommario: “... at simultaneously enhancing the reliability of learning targets and the rationality of sample distribution...”
Testo

Enhancing Accuracy and Efficiency in Calibration of Drinking Water Distribution Networks Through Evolutionary Artificial Neural Networks and Expert Systems di Gomez, Cristian, Solon, Kimberly, Haest, Pieter-Jan, Morley, Mark, Nopens, Ingmar, Torfs, Elena

Sommario: “...The importance of drinking water distribution networks (DWDNs) as critical urban infrastructures...”
Testo

Beyond fixed thresholds: optimizing summaries of wearable device data via piecewise linearization of quantile functions di Park, Junyoung, Kok, Neo, Gaynanova, Irina

Sommario: “... that quantify discrepancies between the full empirical distributions of wearable device measurements...”
Testo

Microgrids Coalitions for Energy Market Balancing di Chifu, Viorica, Pop, Cristina Bianca, Cioara, Tudor, Anghel, Ionut

Sommario: “...With the integration of renewable sources in electricity distribution networks, the need to develop...”
Testo

Uncertainty Guided Online Ensemble for Non-stationary Data Streams in Fusion Science di Rajput, Kishansingh, Schram, Malachi, Sammuli, Brian, Lin, Sen

Sommario: “... by both experimental evolution and machine wear-and-tear. ML models assume stationary distribution...”
Testo

Robustness Analysis of USmorph: I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification di Zhu, Shiwei, Fang, Guanwen, Dai, Yao, Zhou, Chichun, Zheng, Yirui, Song, Jie, Lu, Shiying, Kong, Xu

Sommario: “... independent tests: (1) the t-distributed stochastic neighbor embedding (t-SNE) visualization reveals clear...”
Testo

Federated Continual Learning for Privacy-Preserving Hospital Imaging Classification di Sinhal, Anay, Sinhal, Arpana, Sinhal, Amit

Sommario: “... algorithms typically assume a static data distribution. In practice, hospitals experience continual evolution...”
Testo

Robustness Analysis of USmorph: II. Optimizing Feature Extraction, Dimensionality Reduction, and Clustering for Unsupervised Galaxy Morphology Classification di Fang, Guanwen, Yin, Xiaolei, Zheng, Yirui, Lin, Zesen, Zhu, Shiwei, Song, Jie, Zhou, Chichun, Kong, Xu

Sommario: “... evolution theory, showing physically plausible distributions of different types in parameter space...”
Testo

A Generative Adversarial Graph Neural Network for Synthetic Time Series Data di Gregnanin, Marco, De Smedt, Johannes, Gnecco, Giorgio, Parton, Maurizio

Sommario: “... distributions. GANs employ a generator-discriminator framework, where the generator creates data samples, while...”
Testo

A NISQ-Aware Hybrid Quantum-Classical Framework for Scalable Combinatorial Optimization di Ding, Haolong, Wu, Mohan, Xu, Yin, Xu, Hua

Sommario: “... optimization as a resource-bounded distribution evolution process. Instead of directly optimizing individual...”
Testo

Generalized Reputation Computation Ontology and Temporal Graph Architecture di Kolonin, Anton

Sommario: “...-agent AI framework, so the evolution of distributed multi-agent AI architecture and dynamics...”
Testo

Learning topological defects formation with neural networks in a quantum phase transition di Shi, Han-Qing, Zhang, Hai-Qing

Sommario: “... for neural networks. To address this, we utilize neural networks and machine learning algorithms...”
Testo