Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Chudak, Fabian A."'
Autor:
Han, Fred X., Mills, Keith G., Chudak, Fabian, Riahi, Parsa, Salameh, Mohammad, Zhang, Jialin, Lu, Wei, Jui, Shangling, Niu, Di
Understanding and modelling the performance of neural architectures is key to Neural Architecture Search (NAS). Performance predictors have seen widespread use in low-cost NAS and achieve high ranking correlations between predicted and ground truth p
Externí odkaz:
http://arxiv.org/abs/2302.10835
Autor:
Mills, Keith G., Han, Fred X., Zhang, Jialin, Chudak, Fabian, Mamaghani, Ali Safari, Salameh, Mohammad, Lu, Wei, Jui, Shangling, Niu, Di
Predicting neural architecture performance is a challenging task and is crucial to neural architecture design and search. Existing approaches either rely on neural performance predictors which are limited to modeling architectures in a predefined des
Externí odkaz:
http://arxiv.org/abs/2211.17226
Autor:
Mills, Keith G., Han, Fred X., Zhang, Jialin, Rezaei, Seyed Saeed Changiz, Chudak, Fabian, Lu, Wei, Lian, Shuo, Jui, Shangling, Niu, Di
Neural architecture search automates neural network design and has achieved state-of-the-art results in many deep learning applications. While recent literature has focused on designing networks to maximize accuracy, little work has been conducted to
Externí odkaz:
http://arxiv.org/abs/2109.12426
Autor:
Bian, Zhengbing, Chudak, Fabian, Macready, William, Roy, Aidan, Sebastiani, Roberto, Varotti, Stefano
Quantum annealers (QAs) are specialized quantum computers that minimize objective functions over discrete variables by physically exploiting quantum effects. Current QA platforms allow for the optimization of quadratic objectives defined over binary
Externí odkaz:
http://arxiv.org/abs/1811.02524
Autor:
Korenkevych, Dmytro, Xue, Yanbo, Bian, Zhengbing, Chudak, Fabian, Macready, William G., Rolfe, Jason, Andriyash, Evgeny
Quantum annealing (QA) is a hardware-based heuristic optimization and sampling method applicable to discrete undirected graphical models. While similar to simulated annealing, QA relies on quantum, rather than thermal, effects to explore complex sear
Externí odkaz:
http://arxiv.org/abs/1611.04528
Autor:
Bian, Zhengbing, Chudak, Fabian, Israel, Robert, Lackey, Brad, Macready, William G., Roy, Aidan
Current quantum annealing (QA) hardware suffers from practical limitations such as finite temperature, sparse connectivity, small qubit numbers, and control error. We propose new algorithms for mapping boolean constraint satisfaction problems (CSPs)
Externí odkaz:
http://arxiv.org/abs/1603.03111
Autor:
Bian, Zhengbing, Chudak, Fabian, Macready, William, Roy, Aidan, Sebastiani, Roberto, Varotti, Stefano
Publikováno v:
In Information and Computation December 2020 275
Publikováno v:
Phys. Rev. Lett. vol. 111, 130505 (2013)
Ramsey theory is a highly active research area in mathematics that studies the emergence of order in large disordered structures. Ramsey numbers mark the threshold at which order first appears and are extremely difficult to calculate due to their exp
Externí odkaz:
http://arxiv.org/abs/1201.1842
Autor:
Karimi, Kamran, Dickson, Neil G., Hamze, Firas, Amin, M. H. S., Drew-Brook, Marshall, Chudak, Fabian A., Bunyk, Paul I., Macready, William G., Rose, Geordie
Adiabatic quantum optimization offers a new method for solving hard optimization problems. In this paper we calculate median adiabatic times (in seconds) determined by the minimum gap during the adiabatic quantum optimization for an NP-hard Ising spi
Externí odkaz:
http://arxiv.org/abs/1006.4147
Publikováno v:
IEEE/ACM Trans. Networking 12 (3) 2004: 539-548
Conventional optical networks are based on SONET rings, but since rings are known to use bandwidth inefficiently, there has been much research into shared mesh protection, which promises significant bandwidth savings. Unfortunately, most shared mesh
Externí odkaz:
http://arxiv.org/abs/cs/0209006