5 citations · 9 across the 5 of their papers we have counts for
6 papers
Multi-modal Affect Analysis using standardized data within subjects in the Wild
Sachihiro Youoku, Takahisa Yamamoto, Junya Saito +7
Human affective recognition is an important factor in human-computer interaction. However, the method development with in-the-wild data is not yet accurate enough for practical usa…
SingCubic: Cyclic Incremental Newton-type Gradient Descent with Cubic Regularization for Non-Convex Optimization
Ziqiang Shi
In this work, we generalized and unified two recent completely different works of~\cite{shi2015large} and~\cite{cartis2012adaptive} respectively into one by proposing the cyclic in…
Hodge and Podge: Hybrid Supervised Sound Event Detection with Multi-Hot MixMatch and Composition Consistence Training
Ziqiang Shi, Liu Liu, Huibin Lin +1
In this paper, we propose a method called Hodge and Podge for sound event detection. We demonstrate Hodge and Podge on the dataset of Detection and Classification of Acoustic Scene…
HODGEPODGE: Sound event detection based on ensemble of semi-supervised learning methods
Ziqiang Shi, Liu Liu, Huibin Lin +2
In this paper, we present a method called HODGEPODGE\footnotemark[1] for large-scale detection of sound events using weakly labeled, synthetic, and unlabeled data proposed in the D…
A Double Joint Bayesian Approach for J-Vector Based Text-dependent Speaker Verification
Ziqiang Shi, Mengjiao Wang, Liu Liu +2
J-vector has been proved to be very effective in text-dependent speaker verification with short-duration speech. However, the current state-of-the-art back-end classifiers, e.g. jo…
Empirical study of PROXTONE and PROXTONE for Fast Learning of Large Scale Sparse Models
Ziqiang Shi, Rujie Liu
PROXTONE is a novel and fast method for optimization of large scale non-smooth convex problem \cite{shi2015large}. In this work, we try to use PROXTONE method in solving large scal…