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  1. Sanjeev Arora - Princeton University. Research Interest: Developing mathematical and conceptual. understanding to enable better and safer AI. Charles C. Fitzmorris Professor of Computer Science. Director, Princeton Language and Intelligence. PhD, UC Berkeley 1994. Teaching Research Group Bio/CV Google Scholar Page.

  2. A simple but tough-to-beat baseline for sentence embeddings. S Arora, Y Liang, T Ma. International conference on learning representations. , 2017. 1619. 2017. Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems. S Arora. Journal of the ACM (JACM) 45 (5), 753-782.

  3. Sanjeev Arora (born January 1968) is an Indian American theoretical computer scientist who works in AI and Machine learning. Life. Sanjeev scored the IIT JEE number 1 rank in 1986. He was a visiting scholar at the Institute for Advanced Study in 2002–03. [2] In 2008 he was inducted as a Fellow of the Association for Computing Machinery. [3] .

  4. Sanjeev Arora is a renowned computer scientist and mathematician who works on machine learning, natural language processing, and theory. He is a member of several academic societies and has won several awards, including the ACM Prize in Computing and the Gödel Prize.

  5. Packard Fellowship for Science and Engineering (1997) Empregador (a) Universidade de Princeton. Campo (s) ciência da computação. [ edite no Wikidata] Sanjeev Arora ( Jodhpur, Índia, janeiro de 1968 [ 1]) é um cientista da computação estadunidense nascido na Índia. [ 1]

  6. Sanjeev Arora is a renowned theoretical computer scientist who works on computational complexity, algorithms, and machine learning. He is a member of the National Academy of Sciences, a Simons Investigator, and the author of Computational Complexity: A Modern Approach.

  7. Sanjeev Arora, Anirudh Goyal: A Theory for Emergence of Complex Skills in Language Models. CoRR abs/2307.15936 ( 2023) [i75] Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang: A Quadratic Synchronization Rule for Distributed Deep Learning. CoRR abs/2310.14423 ( 2023)