303 citations · 697 across the 37 of their papers we have counts for
3 papers · 1 filter
Analyzing Upper Bounds on Mean Absolute Errors for Deep Neural Network Based Vector-to-Vector Regression
Jun Qi, Jun Du, Sabato Marco Siniscalchi +2
In this paper, we show that, in vector-to-vector regression utilizing deep neural networks (DNNs), a generalized loss of mean absolute error (MAE) between the predicted and expecte…
Enhanced Adversarial Strategically-Timed Attacks against Deep Reinforcement Learning
Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen +4
Recent deep neural networks based techniques, especially those equipped with the ability of self-adaptation in the system level such as deep reinforcement learning (DRL), are shown…
Maximum a Posteriori Adaptation of Network Parameters in Deep Models
Zhen Huang, Sabato Marco Siniscalchi, I-Fan Chen +2
We present a Bayesian approach to adapting parameters of a well-trained context-dependent, deep-neural-network, hidden Markov model (CD-DNN-HMM) to improve automatic speech recogni…