Zobrazeno 1 - 10
of 26 061
pro vyhledávání: '"Jabbour, A. A."'
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:
Jabbour, Jason, Reddi, Vijay Janapa
The integration of Generative Artificial Intelligence (AI) into autonomous machines represents a major paradigm shift in how these systems operate and unlocks new solutions to problems once deemed intractable. Although generative AI agents provide un
Externí odkaz:
http://arxiv.org/abs/2410.15489
Chess involves extensive study and requires players to keep manual records of their matches, a process which is time-consuming and distracting. The lack of high-quality labeled photographs of chess boards, and the tediousness of manual labeling, have
Externí odkaz:
http://arxiv.org/abs/2410.15206
Using techniques proposed in [Sason, IEEE Trans. Inf. Th. 59, 7118 (2013)] and [Becker, Datta and Jabbour, IEEE Trans. Inf. Th. 69, 4128 (2023)], and building on results from the latter, we construct a globally optimal continuity bound for the von Ne
Externí odkaz:
http://arxiv.org/abs/2410.02686
Autor:
Audenaert, Koenraad, Bergh, Bjarne, Datta, Nilanjana, Jabbour, Michael G., Capel, Ángela, Gondolf, Paul
We establish a tight upper bound for the difference in von Neumann entropies between two quantum states, $\rho_1$ and $\rho_2$. This bound is expressed in terms of the von Neumann entropies of the mutually orthogonal states derived from the Jordan-Ha
Externí odkaz:
http://arxiv.org/abs/2408.15306
Autor:
Jabbour, Sarah, Kondas, Gregory, Kazerooni, Ella, Sjoding, Michael, Fouhey, David, Wiens, Jenna
We propose a permutation-based explanation method for image classifiers. Current image-model explanations like activation maps are limited to instance-based explanations in the pixel space, making it difficult to understand global model behavior. In
Externí odkaz:
http://arxiv.org/abs/2407.14509
Autor:
Jurenka, Irina, Kunesch, Markus, McKee, Kevin R., Gillick, Daniel, Zhu, Shaojian, Wiltberger, Sara, Phal, Shubham Milind, Hermann, Katherine, Kasenberg, Daniel, Bhoopchand, Avishkar, Anand, Ankit, Pîslar, Miruna, Chan, Stephanie, Wang, Lisa, She, Jennifer, Mahmoudieh, Parsa, Rysbek, Aliya, Ko, Wei-Jen, Huber, Andrea, Wiltshire, Brett, Elidan, Gal, Rabin, Roni, Rubinovitz, Jasmin, Pitaru, Amit, McAllister, Mac, Wilkowski, Julia, Choi, David, Engelberg, Roee, Hackmon, Lidan, Levin, Adva, Griffin, Rachel, Sears, Michael, Bar, Filip, Mesar, Mia, Jabbour, Mana, Chaudhry, Arslan, Cohan, James, Thiagarajan, Sridhar, Levine, Nir, Brown, Ben, Gorur, Dilan, Grant, Svetlana, Hashimshoni, Rachel, Weidinger, Laura, Hu, Jieru, Chen, Dawn, Dolecki, Kuba, Akbulut, Canfer, Bileschi, Maxwell, Culp, Laura, Dong, Wen-Xin, Marchal, Nahema, Van Deman, Kelsie, Misra, Hema Bajaj, Duah, Michael, Ambar, Moran, Caciularu, Avi, Lefdal, Sandra, Summerfield, Chris, An, James, Kamienny, Pierre-Alexandre, Mohdi, Abhinit, Strinopoulous, Theofilos, Hale, Annie, Anderson, Wayne, Cobo, Luis C., Efron, Niv, Ananda, Muktha, Mohamed, Shakir, Heymans, Maureen, Ghahramani, Zoubin, Matias, Yossi, Gomes, Ben, Ibrahim, Lila
A major challenge facing the world is the provision of equitable and universal access to quality education. Recent advances in generative AI (gen AI) have created excitement about the potential of new technologies to offer a personal tutor for every
Externí odkaz:
http://arxiv.org/abs/2407.12687
The quantum central limit theorem derived by Cushen and Hudson provides the foundations for understanding how subsystems of large bosonic systems evolving unitarily do reach equilibrium. It finds important applications in the context of quantum inter
Externí odkaz:
http://arxiv.org/abs/2404.11518
Autor:
Jeong, Hyewon, Jabbour, Sarah, Yang, Yuzhe, Thapta, Rahul, Mozannar, Hussein, Han, William Jongwon, Mehandru, Nikita, Wornow, Michael, Lialin, Vladislav, Liu, Xin, Lozano, Alejandro, Zhu, Jiacheng, Kocielnik, Rafal Dariusz, Harrigian, Keith, Zhang, Haoran, Lee, Edward, Vukadinovic, Milos, Balagopalan, Aparna, Jeanselme, Vincent, Matton, Katherine, Demirel, Ilker, Fries, Jason, Rashidi, Parisa, Beaulieu-Jones, Brett, Xu, Xuhai Orson, McDermott, Matthew, Naumann, Tristan, Agrawal, Monica, Zitnik, Marinka, Ustun, Berk, Choi, Edward, Yeom, Kristen, Gursoy, Gamze, Ghassemi, Marzyeh, Pierson, Emma, Chen, George, Kanjilal, Sanjat, Oberst, Michael, Zhang, Linying, Singh, Harvineet, Hartvigsen, Tom, Zhou, Helen, Okolo, Chinasa T.
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between participants and senior researchers on timely and relevant topics for
Externí odkaz:
http://arxiv.org/abs/2403.01628
Autor:
Ralambomihanta, Tokiniaina Raharison, Mohammadzadeh, Shahrad, Islam, Mohammad Sami Nur, Jabbour, Wassim, Liang, Laurence
The rapid evolution of Large Language Models (LLMs), epitomized by architectures like GPT-4, has reshaped the landscape of natural language processing. This paper introduces a pioneering approach to address the efficiency concerns associated with LLM
Externí odkaz:
http://arxiv.org/abs/2401.17574