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Akash Kumar Dhaka
Akash Kumar Dhaka
Doctoral Student, Aalto University
Email verificata su aalto.fi
Titolo
Citata da
Citata da
Anno
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
512021
Robust, accurate stochastic optimization for variational inference
AK Dhaka, A Catalina, MR Andersen, M Magnusson, JH Huggins, ...
NeurIPS 2020, 2020
392020
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
272021
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
82017
Semi-supervised learning with sparse autoencoders in phone classification
AK Dhaka, G Salvi
arXiv preprint arXiv:1610.00520, 2016
72016
Semi-supervised learning with sparse autoencoders in automatic speech recognition
AK Dhaka
22016
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
12020
Robust and Automated Variational Inference
AK Dhaka
Aalto University, 2022
2022
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
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 …, 0
Semi-Övervakad inlärning med glesa Autoencoders i Automatisk taligenkänning
AK Dhaka
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–11