6 accepted papers
Dealing with language heterogeneity has always been one of the challenges in neural machine translation (NMT).The idea of using mixture-of-experts (MoE) naturally excels in addressing this issue by employing different experts to take responsibility for different problems.However, the parameter-ineff…
To improve the performance of Automatic Speech Recognition (ASR), it is common to deploy an error correction module at the post-processing stage to correct recognition errors. In this paper, we propose 1) an error correction model, which takes account of both contextual information and phonetic info…
Large model size and high computational complexity prevent the neural machine translation (NMT) models from being deployed to low resource devices (e.g. mobile phones). Due to the large vocabulary, a large storage memory is required for the word embedding matrix in NMT models, in the meantime, high…
Conversion rate (CVR) prediction is becoming increasingly important in the multi-billion dollar online display advertising industry. It has two major challenges: firstly, the scarce user history data is very complicated and non-linear; secondly, the time delay between the clicks and the correspondin…
Calcium imaging permits optical measurement of neural activity. Since intracellular calcium concentration is an indirect measurement of neural activity, computational tools are necessary to infer the true underlying spiking activity from fluorescence measurements. Bayesian model inversion can be use…
Population activity measurement by calcium imaging can be combined with cellular resolution optogenetic activity perturbations to enable the mapping of neural connectivity in vivo. This requires accurate inference of perturbed and unperturbed neural activity from calcium imaging measurements, which…