Dropout in psychotherapy

Understanding Prior Dropout in Psychotherapy

Little is known about clients who, although in need of a treatment and having the opportunity to take treatment, do not start it. To explore this topic, we conducted a retrospective study comparing 37 prior dropouts with 28 clients who underwent treatment (family therapy). Results showed that prior dropout clients presented symptoms for a longer period, attended previous family therapy and prev...

Psychotherapy dropout : the influence of ethnic identity and stigma on early termination

Understanding Dropout

Dropout is a relatively new algorithm for training neural networks which relies on stochastically “dropping out” neurons during training in order to avoid the co-adaptation of feature detectors. We introduce a general formalism for studying dropout on either units or connections, with arbitrary probability values, and use it to analyze the averaging and regularizing properties of dropout in bot...

Concrete Dropout

• Gal and Gharamani (2015) reinterpreted dropout regularisation as approximate inference in BNNs •Dropout probabilities pl are variational parameters of the approximate posterior qθ(ω) = ∏ k qMk,pk(Wk), where Wk = Mk · diag (zk) and zkl iid ∼Bernoulli(1− pk) • Concrete distribution (Maddison et al., Jang et al.) relaxes Categorical distribution to obtain gradients wrt the probability vector – E...

Fraternal Dropout

Recurrent neural networks (RNNs) form an important class of architectures among neural networks useful for language modeling and sequential prediction. However, optimizing RNNs is known to be harder compared to feed-forward neural networks. A number of techniques have been proposed in literature to address this problem. In this paper we propose a simple technique called fraternal dropout that t...