Robust, accurate stochastic optimization for variational inference AK Dhaka, A Catalina, MR Andersen, M Magnusson, JH Huggins, ... NeurIPS 2020, 2020 | 33 | 2020 |
Challenges and opportunities in high dimensional variational inference AK Dhaka, A Catalina, M Welandawe, MR Andersen, J Huggins, A Vehtari Advances in Neural Information Processing Systems 34, 7787-7798, 2021 | 32 | 2021 |
Preferential batch Bayesian optimization E Siivola, AK Dhaka, MR Andersen, J González, PG Moreno, A Vehtari 2021 IEEE 31st International Workshop on Machine Learning for Signal …, 2021 | 20 | 2021 |
Sparse autoencoder based semi-supervised learning for phone classification with limited annotations AK Dhaka, G Salvi International workshop on grounding language understanding, 22-26, 2017 | 7 | 2017 |
Semi-supervised learning with sparse autoencoders in phone classification AK Dhaka, G Salvi arXiv preprint arXiv:1610.00520, 2016 | 7 | 2016 |
Semi-supervised learning with sparse autoencoders in automatic speech recognition AK Dhaka | 2 | 2016 |
Scalable Gaussian process for extreme classification AK Dhaka, MR Andersen, PG Moreno, A Vehtari 2020 IEEE 30th International Workshop on Machine Learning for Signal …, 2020 | 1 | 2020 |
Robust and Automated Variational Inference AK Dhaka Aalto University, 2022 | | 2022 |
Challenges for BBVI with Normalizing Flows AK Dhaka, A Catalina, M Welandawe, MR Andersen, JH Huggins, ... ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit …, 2021 | | 2021 |
Optimising The Input Window Alignment in CD-DNN Based Phoneme Recognition for Low Latency Processing AK Dhaka, G Salvi arXiv preprint arXiv:1606.09163, 2016 | | 2016 |
Semi-Övervakad inlärning med glesa Autoencoders i Automatisk taligenkänning AK Dhaka | | |