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Latest cs.AI papers
Johannes Schneider, Michalis Vlachos
#DeepLearning has made huge strides in the last decade! From attention & normalization to skip connection & self-supervised learning, we provide an overview of the most influential & recent works. #ConnectingTheDots #DataScience #AI
Sing-Yuan Yeh, Fu-Chieh Chang, Chang-Wei Yueh, Pei-Yuan Wu, Alberto Bernacchia, Sattar Vakili
Discover how to derive sample complexities for kernel based #Qlearning when a generative model exists. We propose a nonparametric Q-learning algorithm for an arbitrarily large scale discounted MDP with order optimal sample complexity! #ReinforcementLearning #MachineLearning #AI
Nicholas Matsumoto, Anil Kumar Saini, Pedro Ribeiro, Hyunjun Choi, Alena Orlenko, Leo-Pekka Lyytikäinen, Jari O Laurikka, Terho Lehtimäki, Sandra Batista, Jason H. Moore
#Lexicase selection leads to faster convergence in TPOT automated ML system, compared to NSGA-II. We explore search space using trie data structure to compare these methods! #ML #DataScience #Automation
Theodor Westny, Joel Oskarsson, Björn Olofsson, Erik Frisk
Introducing MTP-GO: a model that uses temporal graph neural networks & neural ODEs to generate robust predictions of road users' future behavior. Results show it outperforms existing methods & provides multi-modal probabilistic predictions. #MotionPlanning #AutonomousMotion
Train future software developers to write secure source code with our proposed learning modules & hands on labs! Leverage ML & NLP to predict & identify vulnerabilities & improve student skills & awareness on source code vulnerabilities detection & mitigation. #SecureCodingEducation
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