1. Multimodal multisensor activity annotation tool
2. James Bergstra , Rémi Bardenet , Yoshua Bengio , and Balázs Kégl . 2011. Algorithms for Hyper-Parameter Optimization . In Advances in Neural Information Processing Systems, J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K .Q. Weinberger (Eds.). Vol. 24. Curran Associates, Inc .https://proceedings.neurips.cc/paper/ 2011 /file/86e8f7ab32cfd12577bc2619bc635690-Paper.pdf James Bergstra, Rémi Bardenet, Yoshua Bengio, and Balázs Kégl. 2011. Algorithms for Hyper-Parameter Optimization. In Advances in Neural Information Processing Systems, J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K.Q. Weinberger (Eds.). Vol. 24. Curran Associates, Inc.https://proceedings.neurips.cc/paper/2011/file/86e8f7ab32cfd12577bc2619bc635690-Paper.pdf
3. A Bayesian model of plan recognition
4. D. Balabka . 2019. Semi-Supervised Learning for Human Activity Recognition Using Adversarial Autoencoders . In Adjunct Proc. 2019 ACM Int Joint Conf On Pervasive and Ubiquitous Computing and Int Symp on Wearable Computers (London, United Kingdom) . Association for Computing Machinery , New York, NY, USA , 685–688. https://doi.org/10.1145/3341162.3344854 10.1145/3341162.3344854 D. Balabka. 2019. Semi-Supervised Learning for Human Activity Recognition Using Adversarial Autoencoders. In Adjunct Proc. 2019 ACM Int Joint Conf On Pervasive and Ubiquitous Computing and Int Symp on Wearable Computers (London, United Kingdom). Association for Computing Machinery, New York, NY, USA, 685–688. https://doi.org/10.1145/3341162.3344854
5. Exploring Semi-Supervised Methods for Labeling Support in Multimodal Datasets