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- research-articleAugust 2017
Small Batch or Large Batch?: Gaussian Walk with Rebound Can Teach
KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data MiningPages 1275–1284https://doi.org/10.1145/3097983.3098147Efficiency of large-scale learning is a hot topic in both academic and industry. The stochastic gradient descent (SGD) algorithm, and its extension mini-batch SGD, allow the model to be updated without scanning the whole data set. However, the use of ...
- ArticleAugust 2012
Efficient Dissection of Composite Problems, with Applications to Cryptanalysis, Knapsacks, and Combinatorial Search Problems
Proceedings of the 32nd Annual Cryptology Conference on Advances in Cryptology --- CRYPTO 2012 - Volume 7417Pages 719–740https://doi.org/10.1007/978-3-642-32009-5_42In this paper we show that a large class of diverse problems have a bicomposite structure which makes it possible to solve them with a new type of algorithm called dissection, which has much better time/memory tradeoffs than previously known algorithms. ...
- ArticleJuly 2012
Improved known-key distinguishers on Feistel-SP ciphers and application to camellia
ACISP'12: Proceedings of the 17th Australasian conference on Information Security and PrivacyPages 87–100https://doi.org/10.1007/978-3-642-31448-3_7This paper revisits previous known-key distinguishers on generic Feistel-SP ciphers based on rebound attacks. In this paper first we propose a new 5-round inbound phase that requires 2c computations, while the previous work requires 22c computations (c ...
