/ Recent content on Frank Portman Hugo -- gohugo.io /something/ Wed, 12 Sep 2018 20:12:55 -0700 /something/ Something is afoot! /home/ Wed, 12 Sep 2018 20:03:55 -0700 /home/ First a skier, second a Statistician + Machine Learning Engineer. Currently doing Machine Learning @Twitter Cortex. Previously working on competitive intelligence @Uber and self-driving @UberATG. I also write code that others use. /license/ Mon, 01 Jan 0001 00:00:00 +0000 /license/ The MIT License (MIT) Copyright (c) 2018 Frank Portman Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: /software/ Mon, 01 Jan 0001 00:00:00 +0000 /software/ bayesAB Github: https://github.com/FrankPortman/bayesAB/ Website: https://frankportman.github.io/bayesAB/ bayesAB is an R package which provides a suite of functions to conduct and interpret the results of an A/B test in a Bayesian way. The package is meant to be used at all steps of the process - from choosing a prior, to interpreting final results, and then calculating lifts based on certain thresholds. bayesAB currently supports 8 common probability distributions. Currently used for inference at: Uber, Netflix, Microsoft, Blizzard, and others. /writing/ Mon, 01 Jan 0001 00:00:00 +0000 /writing/ Research arXiv:2211.00550 (2022) GLINKX: A Scalable Unified Framework For Homophilous and Heterophilous Graphs Marios Papachristou, Rishab Goel, Frank Portman, Matthew Miller, Rong Jin arXiv:2210.16271 (2022) MiCRO: Multi-interest Candidate Retrieval Online Frank Portman, Stephen Ragain, Ahmed El-Kishky arXiv:2205.06205 (2022) kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval Ahmed El-Kishky, Thomas Markovich, Kenny Leung, Frank Portman, Aria Haghighi, Ying Xiao arXiv:2202.05387 (2022) TwHIN: Embedding the Twitter Heterogeneous Information Network for Personalized Recommendation Ahmed El-Kishky, Thomas Markovich, Serim Park, Chetan Verma, Baekjin Kim, Ramy Eskander, Yury Malkov, Frank Portman, Sofía Samaniego, Ying Xiao, Aria Haghighi