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Learning Effective Embeddings for Machine Generated Emails with Applications to Email Category Prediction.

, , , , and . IEEE BigData, page 1846-1855. IEEE, (2018)

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Learning Effective Embeddings for Machine Generated Emails with Applications to Email Category Prediction., , , , and . IEEE BigData, page 1846-1855. IEEE, (2018)Email Category Prediction., , , , and . WWW (Companion Volume), page 495-503. ACM, (2017)RiSER: Learning Better Representations for Richly Structured Emails., , , , , , and . WWW, page 886-895. ACM, (2019)FieldSwap: Data Augmentation for Effective Form-Like Document Extraction., , , , and . ICDE, page 4722-4732. IEEE, (2024)The bidirectional polyomino partitioned PPUF as a hardware security primitive., and . GlobalSIP, page 257-260. IEEE, (2013)Hardware obfuscation using PUF-based logic., and . ICCAD, page 270-277. IEEE, (2014)Reverse Engineering and Prevention Techniques for Physical Unclonable Functions Using Side Channels., , , and . DAC, page 90:1-90:6. ACM, (2014)Migrating a Privacy-Safe Information Extraction System to a Software 2.0 Design., , , , and . CIDR, www.cidrdb.org, (2020)Multiple constant multiplication implementations in near-threshold computing systems., , and . ICASSP, page 1071-1075. IEEE, (2015)Quo vadis, PUF?: Trends and challenges of emerging physical-disorder based security., , , and . DATE, page 1-6. European Design and Automation Association, (2014)