… baskets with softmaxbased losses, … Basket-based Softmax (BBS) to effectively train models
on multiple baskets in an end-to-end fashion. We first provide a unified perspective for softmax…

… Specifically, empowered by Gumbel Softmax, we devise a denoising generator to adap…
Then, we derive the representation of each sub-basket based on its constituent items through a …

… Basket-based recommendation has been well investigated in recent years. In this section,
we divide the major basketbased … with the softmax function, where the softmax function is …

… We first make a personalized representation for a basket based on its constituent items …
In within-baskets scenario, we can take softmax as the dividing function and sigmoid as the …

… Session-based recommendation focuses on recommending a next-item/basket based
only on first-order transition (eg, by Markov chain) from the last basket to the current one but …

… To determine the intention behind each user choice, we employ a softmax function to compute
the the probability associated with each intention. Specifically, the probability gi,k of item …

… With ℎ𝑢 𝑘 , we can calculate the item probability distri- bution via softmax. To find the most
… Note that we adopt top-𝐾 ranked items as next basket based on the user’s historical item …

… masking (the cloze task) to train the model, since basket-level masking (the basket
recommendation task) is designed to respect the sequential order and predict the future basket …

… A simple prediction model for the next basket is to perform the softmax operation over all the
… : (i) “Concat” predicts the next basket based on the concatenation of the last hidden states of …

… approach to deal with the softmax layer, namely noise-… the normalization constant of
the softmax to avoid the high … First, a shopping-basket-based transaction table is extracted …