Résultats de la recherche - distributed evolution (algorithm OR ((algorithmics OR Algorithmssics) OR Algorithmssics))

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

Table des matières: “… distribution. While such guarantees are well-understood for several popular algorithms under stronger…”
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FastBUS: A Fast Bayesian Framework for Unified Weakly-Supervised Learning par Wang, Ziquan, Wang, Haobo, Chen, Ke, Feng, Lei, Chen, Gang

Table des matières: “… framework that efficiently infers latent true label distributions across various weak supervisions. Our key…”
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Learning interacting particle systems from unlabeled data par Wei, Viska, Lu, Fei

Table des matières: “… evolution equation of the empirical distribution. The loss function is quadratic in potentials, supporting…”
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Adiabatic Error Cancellation in Berry Phase Estimation par Kiumi, Chusei

Table des matières: “… tolerance. Combining finite-runtime evolutions under $\pm H$ along the loop cancels the leading $O(T^{-1…”
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Improved sampling via learned diffusions par Richter, Lorenz, Berner, Julius

Table des matières: “… generalized Schrödinger bridge problem, seeking a stochastic evolution between a given prior distribution…”
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Robust off-policy Reinforcement Learning via Soft Constrained Adversary par Nakanishi, Kosuke, Kubo, Akihiro, Yasui, Yuji, Ishii, Shin

Table des matières: “… significant attention and undergone rapid evolution due to RL's potential vulnerability. Although…”
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Avalanches in Magnetohydrodynamical simulations par Lamarre, Henri, Charbonneau, Paul, Noraz, Quentin, Strugarek, Antoine, Blaise, Alexis, Brun, Allan Sacha, Carlsson, Mats, Gudiksen, Boris Vilhelm

Table des matières: “… release spans a vast range of scales. Recent computational advances, at the level of both algorithmics…”
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Concentration Within Distribution: Unmasking Bitcoin's Structural Centralization Through Network Science par Nonaka, Myriam, Marín-Rodríguez, F. Javier, Jiricny, Alexander, Romance, Miguel, Criado, Regino, Iglesias-Pérez, Sergio, Partida, Alberto

Table des matières: “…, which allows us to explore its mesoscopic properties and trace its temporal evolution. In particular, we…”
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Stacked Intelligent Metasurfaces for 6G Wireless Networks: Principles, Applications, and Research Directions par Shi, Enyu, Zhang, Jiayi, Liu, Zhilong, Liu, Ziheng, Nallanathan, Arumugam, Debbah, Merouane, Jin, Shi, Ai, Bo

Table des matières: “…, distributed wireless architectures such as cell-free massive multiple-input multiple-output (MIMO) have…”
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Euclid preparation. XXXI. The effect of the variations in photometric passbands on photometric-redshift accuracy par 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.

Table des matières: “… extragalactic surveys. While the requirements on photo-zs for the study of galaxy evolution mostly pertain…”
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Accelerating FRB Search: Dataset and Methods par 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

Table des matières: “… in studying the distribution and evolution of matter in the universe. FRBs can only be observed through radio…”
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High‐Fidelity Modeling of Stochastic RVE Based on Learning Strategies for Unidirectional Fiber Reinforced Composite Material par Chenhao Ji, Yunong Zhai, Dongsheng Li, Hao Qu

Table des matières: “… distribution and combined with particle swarm optimization algorithm to develop a method that can help generate…”
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Diffusion Model-based Reinforcement Learning for Version Age of Information Scheduling: Average and Tail-Risk-Sensitive Control par Pan, Haoyuan, Chen, Sizhao, Wang, Zhaorui, Chan, Tse-Tin

Table des matières: “… algorithm. RS-D3SAC integrates a diffusion-based actor with a quantile-based distributional critic…”
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Listening to the Noise: Blind Denoising with Gibbs Diffusion par Heurtel-Depeiges, David, Margossian, Charles C., Ohana, Ruben, Blancard, Bruno Régaldo-Saint

Table des matières: “… models. In particular, diffusion models are trained like denoisers, and the distribution they model…”
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Structure, Positivity and Classical Simulability of Kirkwood-Dirac Distributions par Burkat, Jędrzej, Strelchuk, Sergii

Table des matières: “…The Kirkwood-Dirac (KD) quasiprobability distribution is known for its role in quantum metrology…”
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Generalised Time-Series Analysis of Fault Mechanics Using Explainable AI par King, Thomas, Vinciguerra, Sergio

Table des matières: “…, with occurrence-based metrics such as time distributions, Gutenberg-Richter b-values, and spatial fractal…”
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IBCB: Efficient Inverse Batched Contextual Bandit for Behavioral Evolution History par Xu, Yi, Shen, Weiran, Zhang, Xiao, Xu, Jun

Table des matières: “…-makers includes their behavioral evolution from novice expert to experienced expert. This poses a new…”
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Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach par Li, Yicong, Yang, Yu, Cao, Jiannong, Liu, Shuaiqi, Tang, Haoran, Xu, Guandong

Table des matières: “… slightly changed vertices in the long-tail part of the power-law distribution. We first identify biased…”
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Bures-Wasserstein Flow Matching for Graph Generation par Jiang, Keyue, Cui, Jiahao, Dong, Xiaowen, Toni, Laura

Table des matières: “… distributions. However, these methods typically model the evolution of individual nodes and edges independently…”
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ECo-MoE: Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots par Wang, Yibin, Li, Muhan, Guo, Zihan, Kriegman, Sam

Table des matières: “…In this paper, we introduce a model of evolution and learning in robots that co-optimizes a…”
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