Zobrazeno 1 - 10
of 715
pro vyhledávání: '"Wenliang, Li"'
We propose a new algorithm for model-based distributional reinforcement learning (RL), and prove that it is minimax-optimal for approximating return distributions with a generative model (up to logarithmic factors), resolving an open question of Zhan
Externí odkaz:
http://arxiv.org/abs/2402.07598
Autor:
Ruoss, Anian, Delétang, Grégoire, Medapati, Sourabh, Grau-Moya, Jordi, Wenliang, Li Kevin, Catt, Elliot, Reid, John, Lewis, Cannada A., Veness, Joel, Genewein, Tim
This paper uses chess, a landmark planning problem in AI, to assess transformers' performance on a planning task where memorization is futile $\unicode{x2013}$ even at a large scale. To this end, we release ChessBench, a large-scale benchmark dataset
Externí odkaz:
http://arxiv.org/abs/2402.04494
Autor:
Grau-Moya, Jordi, Genewein, Tim, Hutter, Marcus, Orseau, Laurent, Delétang, Grégoire, Catt, Elliot, Ruoss, Anian, Wenliang, Li Kevin, Mattern, Christopher, Aitchison, Matthew, Veness, Joel
Meta-learning has emerged as a powerful approach to train neural networks to learn new tasks quickly from limited data. Broad exposure to different tasks leads to versatile representations enabling general problem solving. But, what are the limits of
Externí odkaz:
http://arxiv.org/abs/2401.14953
Autor:
Wenliang, Li Kevin, Delétang, Grégoire, Aitchison, Matthew, Hutter, Marcus, Ruoss, Anian, Gretton, Arthur, Rowland, Mark
We propose a novel algorithmic framework for distributional reinforcement learning, based on learning finite-dimensional mean embeddings of return distributions. We derive several new algorithms for dynamic programming and temporal-difference learnin
Externí odkaz:
http://arxiv.org/abs/2312.07358
Autor:
Wenliang, Li Kevin, Moran, Ben
How do score-based generative models (SBMs) learn the data distribution supported on a low-dimensional manifold? We investigate the score model of a trained SBM through its linear approximations and subspaces spanned by local feature vectors. During
Externí odkaz:
http://arxiv.org/abs/2311.09952
Autor:
Wang, Zhe, Veličković, Petar, Hennes, Daniel, Tomašev, Nenad, Prince, Laurel, Kaisers, Michael, Bachrach, Yoram, Elie, Romuald, Wenliang, Li Kevin, Piccinini, Federico, Spearman, William, Graham, Ian, Connor, Jerome, Yang, Yi, Recasens, Adrià, Khan, Mina, Beauguerlange, Nathalie, Sprechmann, Pablo, Moreno, Pol, Heess, Nicolas, Bowling, Michael, Hassabis, Demis, Tuyls, Karl
Identifying key patterns of tactics implemented by rival teams, and developing effective responses, lies at the heart of modern football. However, doing so algorithmically remains an open research challenge. To address this unmet need, we propose Tac
Externí odkaz:
http://arxiv.org/abs/2310.10553
Association of Perioperative Skeletal Muscle Index Change With Outcome in Colorectal Cancer Patients
Autor:
Zhenhui Li, Guanghong Yan, Mengmei Liu, Yanli Li, Lizhu Liu, Ruimin You, Xianshuo Cheng, Caixia Zhang, Qingwan Li, Zhaojuan Jiang, Jinqiu Ruan, Yingying Ding, Wenliang Li, Dingyun You, Zaiyi Liu
Publikováno v:
Journal of Cachexia, Sarcopenia and Muscle, Vol 15, Iss 6, Pp 2519-2535 (2024)
ABSTRACT Background The association between perioperative changes in the skeletal muscle index (SMI) and colorectal cancer (CRC) outcomes remains unclear. We aim to explore perioperative change patterns of SMI and evaluate their effects on long‐ter
Externí odkaz:
https://doaj.org/article/3870bc724e7349c8ab75ef9f92a0a18d
Autor:
Delétang, Grégoire, Ruoss, Anian, Duquenne, Paul-Ambroise, Catt, Elliot, Genewein, Tim, Mattern, Christopher, Grau-Moya, Jordi, Wenliang, Li Kevin, Aitchison, Matthew, Orseau, Laurent, Hutter, Marcus, Veness, Joel
It has long been established that predictive models can be transformed into lossless compressors and vice versa. Incidentally, in recent years, the machine learning community has focused on training increasingly large and powerful self-supervised (la
Externí odkaz:
http://arxiv.org/abs/2309.10668
Publikováno v:
Deutsche Entomologische Zeitschrift, Vol 71, Iss 2, Pp 241-254 (2024)
The subgenus Homoneura Wulp, 1891 (Diptera, Lauxaniidae, Homoneurinae) is highly diverse with more than 220 species known from China, representing more than 80% of the Chinese genus Homoneura Wulp, 1891. These species were assigned into 21 species gr
Externí odkaz:
https://doaj.org/article/d94933b9d1104fc7b273dbe4f0d6453e
Autor:
Wenliang Li
Publikováno v:
Journal of High Energy Physics, Vol 2024, Iss 7, Pp 1-21 (2024)
Abstract As a simple lattice model that exhibits a phase transition, the Ising model plays a fundamental role in statistical and condensed matter physics. The Ising transition is realized by physical systems, such as the liquid-vapor transition. Its
Externí odkaz:
https://doaj.org/article/d0566eed28334eb49deda301a2c51d0b