Risultati della ricerca - distributed evolution (algorithm OR (algorithmics OR Algorithmssicics))

A Unifying View of Coverage in Linear Off-Policy Evaluation di Amortila, Philip, Huang, Audrey, Krishnamurthy, Akshay, Jiang, Nan

Sommario: “... distribution. While such guarantees are well-understood for several popular algorithms under stronger...”
Testo

FastBUS: A Fast Bayesian Framework for Unified Weakly-Supervised Learning di Wang, Ziquan, Wang, Haobo, Chen, Ke, Feng, Lei, Chen, Gang

Sommario: “... framework that efficiently infers latent true label distributions across various weak supervisions. Our key...”
Testo

Learning interacting particle systems from unlabeled data di Wei, Viska, Lu, Fei

Sommario: “... evolution equation of the empirical distribution. The loss function is quadratic in potentials, supporting...”
Testo

Adiabatic Error Cancellation in Berry Phase Estimation di Kiumi, Chusei

Sommario: “... tolerance. Combining finite-runtime evolutions under $\pm H$ along the loop cancels the leading $O(T^{-1...”
Testo

Improved sampling via learned diffusions di Richter, Lorenz, Berner, Julius

Sommario: “... generalized Schrödinger bridge problem, seeking a stochastic evolution between a given prior distribution...”
Testo

Robust off-policy Reinforcement Learning via Soft Constrained Adversary di Nakanishi, Kosuke, Kubo, Akihiro, Yasui, Yuji, Ishii, Shin

Sommario: “... significant attention and undergone rapid evolution due to RL's potential vulnerability. Although...”
Testo

Avalanches in Magnetohydrodynamical simulations di Lamarre, Henri, Charbonneau, Paul, Noraz, Quentin, Strugarek, Antoine, Blaise, Alexis, Brun, Allan Sacha, Carlsson, Mats, Gudiksen, Boris Vilhelm

Sommario: “... release spans a vast range of scales. Recent computational advances, at the level of both algorithmics...”
Testo

Concentration Within Distribution: Unmasking Bitcoin's Structural Centralization Through Network Science di Nonaka, Myriam, Marín-Rodríguez, F. Javier, Jiricny, Alexander, Romance, Miguel, Criado, Regino, Iglesias-Pérez, Sergio, Partida, Alberto

Sommario: “..., which allows us to explore its mesoscopic properties and trace its temporal evolution. In particular, we...”
Testo

Stacked Intelligent Metasurfaces for 6G Wireless Networks: Principles, Applications, and Research Directions di Shi, Enyu, Zhang, Jiayi, Liu, Zhilong, Liu, Ziheng, Nallanathan, Arumugam, Debbah, Merouane, Jin, Shi, Ai, Bo

Sommario: “..., distributed wireless architectures such as cell-free massive multiple-input multiple-output (MIMO) have...”
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

High‐Fidelity Modeling of Stochastic RVE Based on Learning Strategies for Unidirectional Fiber Reinforced Composite Material di Chenhao Ji, Yunong Zhai, Dongsheng Li, Hao Qu

Sommario: “... distribution and combined with particle swarm optimization algorithm to develop a method that can help generate...”
Testo

Diffusion Model-based Reinforcement Learning for Version Age of Information Scheduling: Average and Tail-Risk-Sensitive Control di Pan, Haoyuan, Chen, Sizhao, Wang, Zhaorui, Chan, Tse-Tin

Sommario: “... algorithm. RS-D3SAC integrates a diffusion-based actor with a quantile-based distributional critic...”
Testo

Listening to the Noise: Blind Denoising with Gibbs Diffusion di Heurtel-Depeiges, David, Margossian, Charles C., Ohana, Ruben, Blancard, Bruno Régaldo-Saint

Sommario: “... models. In particular, diffusion models are trained like denoisers, and the distribution they model...”
Testo

Structure, Positivity and Classical Simulability of Kirkwood-Dirac Distributions di Burkat, Jędrzej, Strelchuk, Sergii

Sommario: “...The Kirkwood-Dirac (KD) quasiprobability distribution is known for its role in quantum metrology...”
Testo

Generalised Time-Series Analysis of Fault Mechanics Using Explainable AI di King, Thomas, Vinciguerra, Sergio

Sommario: “..., with occurrence-based metrics such as time distributions, Gutenberg-Richter b-values, and spatial fractal...”
Testo

IBCB: Efficient Inverse Batched Contextual Bandit for Behavioral Evolution History di Xu, Yi, Shen, Weiran, Zhang, Xiao, Xu, Jun

Sommario: “...-makers includes their behavioral evolution from novice expert to experienced expert. This poses a new...”
Testo

Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach di Li, Yicong, Yang, Yu, Cao, Jiannong, Liu, Shuaiqi, Tang, Haoran, Xu, Guandong

Sommario: “... slightly changed vertices in the long-tail part of the power-law distribution. We first identify biased...”
Testo

Bures-Wasserstein Flow Matching for Graph Generation di Jiang, Keyue, Cui, Jiahao, Dong, Xiaowen, Toni, Laura

Sommario: “... distributions. However, these methods typically model the evolution of individual nodes and edges independently...”
Testo

ECo-MoE: Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots di Wang, Yibin, Li, Muhan, Guo, Zihan, Kriegman, Sam

Sommario: “...In this paper, we introduce a model of evolution and learning in robots that co-optimizes a...”
Testo