Zobrazeno 1 - 10
of 12 398
pro vyhledávání: '"McNamee A"'
Associative memory models, such as Hopfield networks and their modern variants, have garnered renewed interest due to advancements in memory capacity and connections with self-attention in transformers. In this work, we introduce a unified framework-
Externí odkaz:
http://arxiv.org/abs/2411.08590
Autor:
Scisciò, M., Petringa, G., Zhu, Z., Rodrigues, M. R. D., Alonzo, M., Andreoli, P. L., Filippi, F., Consoli, Fe., Huault, M., Raffestin, D., Molloy, D., Larreur, H., Singappuli, D., Carriere, T., Verona, C., Nicolai, P., McNamee, A., Ehret, M., Filippov, E., Lera, R., Pérez-Hernández, J. A., Agarwal, S., Krupka, M., Singh, S., Istokskaia, V., Lattuada, D., La Cognata, M., Guardo, G. L., Palmerini, S., Rapisarda, G., Batani, K., Cipriani, M., Cristofari, G., Di Ferdinando, E., Di Giorgio, G., De Angelis, R., Giulietti, D., Xu, J., Volpe, L., Rodríguez-Frías, M. D., Giuffrida, L., Margarone, D., Batani, D., Cirrone, G. A. P., Bonasera, A., Consoli, Fa.
Driving the nuclear fusion reaction p+11B -> 3 alpha + 8.7 MeV in laboratory conditions, by interaction between high-power laser pulses and matter, has become a popular field of research, due to numerous applications that it can potentially allow: an
Externí odkaz:
http://arxiv.org/abs/2411.04577
Extremum Seeking Control (ESC) is a well-known set of continuous time algorithms for model-free optimization of a cost function. One issue for ESCs is the convergence rates of parameters to extrema of unknown cost functions. The local convergence rat
Externí odkaz:
http://arxiv.org/abs/2409.12290
For a map that is strictly but not strongly convex, model-based gradient extremum seeking has an eigenvalue of zero at the extremum, i.e., it fails at exponential convergence. Interestingly, perturbation-based model-free extremum seeking has a negati
Externí odkaz:
http://arxiv.org/abs/2405.12908
Autor:
Mayfield, James, Yang, Eugene, Lawrie, Dawn, MacAvaney, Sean, McNamee, Paul, Oard, Douglas W., Soldaini, Luca, Soboroff, Ian, Weller, Orion, Kayi, Efsun, Sanders, Kate, Mason, Marc, Hibbler, Noah
Large Language Models (LLMs) have enabled new ways to satisfy information needs. Although great strides have been made in applying them to settings like document ranking and short-form text generation, they still struggle to compose complete, accurat
Externí odkaz:
http://arxiv.org/abs/2405.00982
This paper describes the submission runs from the HLTCOE team at the CIRAL CLIR tasks for African languages at FIRE 2023. Our submissions use machine translation models to translate the documents and the training passages, and ColBERT-X as the retrie
Externí odkaz:
http://arxiv.org/abs/2404.08134
Autor:
Lawrie, Dawn, MacAvaney, Sean, Mayfield, James, McNamee, Paul, Oard, Douglas W., Soldaini, Luca, Yang, Eugene
The principal goal of the TREC Neural Cross-Language Information Retrieval (NeuCLIR) track is to study the impact of neural approaches to cross-language information retrieval. The track has created four collections, large collections of Chinese, Pers
Externí odkaz:
http://arxiv.org/abs/2404.08071
Modern Hopfield networks have enjoyed recent interest due to their connection to attention in transformers. Our paper provides a unified framework for sparse Hopfield networks by establishing a link with Fenchel-Young losses. The result is a new fami
Externí odkaz:
http://arxiv.org/abs/2402.13725
Autor:
Rodrigues, M. R. D., Bonasera, A., Scisciò, M., Pérez-Hernández, J. A., Ehret, M., Filippi, F., Andreoli, P. L., Huault, M., Larreur, H., Singappuli, D., Molloy, D., Raffestin, D., Alonzo, M., Rapisarda, G. G., Lattuada, D., Guardo, G. L., Verona, C., Consoli, Fe., Petringa, G., McNamee, A., La Cognata, M., Palmerini, S., Carriere, T., Cipriani, M., Di Giorgio, G., Cristofari, G., De Angelis, R., Cirrone, G. A. P., Margarone, D., Giuffrida, L., Batani, D., Nicolai, P., Batani, K., Lera, R., Volpe, L., Giulietti, D., Agarwal, S., Krupka, M., Singh, S., Consoli, Fa.
Laser technologies improved after the understanding of the Chirped Pulse Amplification (CPA) which allows energetic laser beams to be compressed to tens of femtosecond (fs) pulse durations and focused to few $\mu$m. Protons of tens of MeV can be acce
Externí odkaz:
http://arxiv.org/abs/2312.09145
This study addresses the application of deep learning techniques in joint sound signal classification and localization networks. Current state-of-the-art sound source localization deep learning networks lack feature aggregation within their architect
Externí odkaz:
http://arxiv.org/abs/2310.19063