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ORCIDAkash Kumar Dhaka
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2020 – today
- 2022
[b1]Akash Kumar Dhaka:
Robust and Automated Variational Inference. Aalto University, Espoo, Finland, 2022- 2021
- [c4]Eero Siivola
, Akash Kumar Dhaka, Michael Riis Andersen, Javier González, Pablo Garcia Moreno, Aki Vehtari:
Preferential Batch Bayesian Optimization. MLSP 2021: 1-6 - [c3]Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe, Michael Riis Andersen, Jonathan H. Huggins, Aki Vehtari:
Challenges and Opportunities in High Dimensional Variational Inference. NeurIPS 2021: 7787-7798 - [i5]Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe, Michael Riis Andersen, Jonathan H. Huggins, Aki Vehtari:
Challenges and Opportunities in High-dimensional Variational Inference. CoRR abs/2103.01085 (2021) - 2020
- [c2]Akash Kumar Dhaka, Michael Riis Andersen, Pablo Garcia Moreno, Aki Vehtari:
Scalable Gaussian Process for Extreme Classification. MLSP 2020: 1-6 - [c1]Akash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen, Måns Magnusson, Jonathan H. Huggins, Aki Vehtari:
Robust, Accurate Stochastic Optimization for Variational Inference. NeurIPS 2020 - [i4]Eero Siivola, Akash Kumar Dhaka, Michael Riis Andersen, Javier González, Pablo Garcia Moreno, Aki Vehtari:
Preferential Batch Bayesian Optimization. CoRR abs/2003.11435 (2020) - [i3]Akash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen, Måns Magnusson, Jonathan H. Huggins, Aki Vehtari:
Robust, Accurate Stochastic Optimization for Variational Inference. CoRR abs/2009.00666 (2020)
2010 – 2019
- 2016
- [i2]Akash Kumar Dhaka, Giampiero Salvi:
Optimising The Input Window Alignment in CD-DNN Based Phoneme Recognition for Low Latency Processing. CoRR abs/1606.09163 (2016) - [i1]Akash Kumar Dhaka, Giampiero Salvi:
Semi-supervised Learning with Sparse Autoencoders in Phone Classification. CoRR abs/1610.00520 (2016)
Coauthor Index
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