Zobrazeno 1 - 10
of 13 355
pro vyhledávání: '"P A, Coates"'
The randomized power method has gained significant interest due to its simplicity and efficient handling of large-scale spectral analysis and recommendation tasks. As modern datasets contain sensitive private information, we need to give formal guara
Externí odkaz:
http://arxiv.org/abs/2411.01931
Autor:
Wang, Yuening, Chen, Man, Hu, Yaochen, Guo, Wei, Zhang, Yingxue, Guo, Huifeng, Liu, Yong, Coates, Mark
Publikováno v:
CIKM (2024) 2462-2471
Many platforms, such as e-commerce websites, offer both search and recommendation services simultaneously to better meet users' diverse needs. Recommendation services suggest items based on user preferences, while search services allow users to searc
Externí odkaz:
http://arxiv.org/abs/2410.21487
Autor:
Glavas, Theodore, Chataoui, Joud, Regol, Florence, Jabbour, Wassim, Valkanas, Antonios, Oreshkin, Boris N., Coates, Mark
The vast size of Large Language Models (LLMs) has prompted a search to optimize inference. One effective approach is dynamic inference, which adapts the architecture to the sample-at-hand to reduce the overall computational cost. We empirically exami
Externí odkaz:
http://arxiv.org/abs/2410.20022
Autor:
Hu, Yaochen, Zeng, Mai, Zhang, Ge, Rumiantsev, Pavel, Ma, Liheng, Zhang, Yingxue, Coates, Mark
Graph Neural Networks (GNN) exhibit superior performance in graph representation learning, but their inference cost can be high, due to an aggregation operation that can require a memory fetch for a very large number of nodes. This inference cost is
Externí odkaz:
http://arxiv.org/abs/2410.19723
Efficiently determining the satisfiability of a boolean equation -- known as the SAT problem for brevity -- is crucial in various industrial problems. Recently, the advent of deep learning methods has introduced significant potential for enhancing SA
Externí odkaz:
http://arxiv.org/abs/2409.18778
Autor:
Zhou, Jiaming, Ghaddar, Abbas, Zhang, Ge, Ma, Liheng, Hu, Yaochen, Pal, Soumyasundar, Coates, Mark, Wang, Bin, Zhang, Yingxue, Hao, Jianye
Despite recent advances in training and prompting strategies for Large Language Models (LLMs), these models continue to face challenges with complex logical reasoning tasks that involve long reasoning chains. In this work, we explore the potential an
Externí odkaz:
http://arxiv.org/abs/2409.12437
Autor:
Verbas, Omer, Cokyasar, Taner, Joyce-Johnson, Seamus, Wainwright, Scott, Coates, Maeve, Rousseau, Aymeric, Aloisi, Jim, Stewart, Anson, Auld, Joshua
Transit is essential for urban transportation and achieving net-zero targets. In urban areas like the Chicago Metropolitan Region, transit enhances mobility and connects people, fostering a dynamic economy. To quantify the mobility and selected econo
Externí odkaz:
http://arxiv.org/abs/2409.04568
Autor:
Pynn-Coates, Nigel
This paper concerns pairs of models of the theory of the differential field of logarithmic-exponential transseries that are tame as a pair of real closed fields. That is, the smaller model is bounded inside the larger model and there exists a standar
Externí odkaz:
http://arxiv.org/abs/2408.07033
Inspired by transformation optics and photonic crystals, this paper presents a computational investigation into the interaction between water surface waves and array waveguides of cylinders with multiple previously unexplored lattice geometries, incl
Externí odkaz:
http://arxiv.org/abs/2407.17141
Autor:
Regol, Florence, Chataoui, Joud, Charpentier, Bertrand, Coates, Mark, Piantanida, Pablo, Gunnemann, Stephan
Machine learning models can solve complex tasks but often require significant computational resources during inference. This has led to the development of various post-training computation reduction methods that tackle this issue in different ways, s
Externí odkaz:
http://arxiv.org/abs/2406.14404