Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Azer, Erfan Sadeqi"'
Autor:
Khashabi, Daniel, Cohan, Arman, Shakeri, Siamak, Hosseini, Pedram, Pezeshkpour, Pouya, Alikhani, Malihe, Aminnaseri, Moin, Bitaab, Marzieh, Brahman, Faeze, Ghazarian, Sarik, Gheini, Mozhdeh, Kabiri, Arman, Mahabadi, Rabeeh Karimi, Memarrast, Omid, Mosallanezhad, Ahmadreza, Noury, Erfan, Raji, Shahab, Rasooli, Mohammad Sadegh, Sadeghi, Sepideh, Azer, Erfan Sadeqi, Samghabadi, Niloofar Safi, Shafaei, Mahsa, Sheybani, Saber, Tazarv, Ali, Yaghoobzadeh, Yadollah
Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language, one of t
Externí odkaz:
http://arxiv.org/abs/2012.06154
Autor:
Milutinovic, Veljko, Azer, Erfan Sadeqi, Yoshimoto, Kristy, Klimeck, Gerhard, Djordjevic, Miljan, Kotlar, Milos, Bojovic, Miroslav, Miladinovic, Bozidar, Korolija, Nenad, Stankovic, Stevan, Filipović, Nenad, Babovic, Zoran, Kosanic, Miroslav, Tsuda, Akira, Valero, Mateo, De Santo, Massimo, Neuhold, Erich, Skoručak, Jelena, Dipietro, Laura, Ratkovic, Ivan
This article starts from the assumption that near future 100BTransistor SuperComputers-on-a-Chip will include N big multi-core processors, 1000N small many-core processors, a TPU-like fixed-structure systolic array accelerator for the most frequently
Externí odkaz:
http://arxiv.org/abs/2009.10593
Empirical research in Natural Language Processing (NLP) has adopted a narrow set of principles for assessing hypotheses, relying mainly on p-value computation, which suffers from several known issues. While alternative proposals have been well-debate
Externí odkaz:
http://arxiv.org/abs/1911.03850
Systems for language understanding have become remarkably strong at overcoming linguistic imperfections in tasks involving phrase matching or simple reasoning. Yet, their accuracy drops dramatically as the number of reasoning steps increases. We pres
Externí odkaz:
http://arxiv.org/abs/1901.02522
We study the classic $k$-means/median clustering, which are fundamental problems in unsupervised learning, in the setting where data are partitioned across multiple sites, and where we are allowed to discard a small portion of the data by labeling th
Externí odkaz:
http://arxiv.org/abs/1805.09495
We investigate the problem of detecting periodic trends within a string $S$ of length $n$, arriving in the streaming model, containing at most $k$ wildcard characters, where $k=o(n)$. A wildcard character is a special character that can be assigned a
Externí odkaz:
http://arxiv.org/abs/1802.07375
Analyzing patterns in data streams generated by network traffic, sensor networks, or satellite feeds is a challenge for systems in which the available storage is limited. In addition, real data is noisy, which makes designing data stream algorithms e
Externí odkaz:
http://arxiv.org/abs/1711.04367
We study the problem of finding all $k$-periods of a length-$n$ string $S$, presented as a data stream. $S$ is said to have $k$-period $p$ if its prefix of length $n-p$ differs from its suffix of length $n-p$ in at most $k$ locations. We give a one-p
Externí odkaz:
http://arxiv.org/abs/1708.04381
High-dimensional representations, such as radial basis function networks or tile coding, are common choices for policy evaluation in reinforcement learning. Learning with such high-dimensional representations, however, can be expensive, particularly
Externí odkaz:
http://arxiv.org/abs/1708.01298
A palindrome is a string that reads the same as its reverse, such as "aibohphobia" (fear of palindromes). Given an integer $d>0$, a $d$-near-palindrome is a string of Hamming distance at most $d$ from its reverse. We study the natural problem of iden
Externí odkaz:
http://arxiv.org/abs/1705.01887