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Found 4 papers, 0 papers with code
STEC: See-Through Transformer-based Encoder for CTR Prediction
Most CTR prediction models have relied on a single fusion and interaction learning strategy.
Ranked #1 on
Click-Through Rate Prediction
on MovieLens 1M
MMBAttn: Max-Mean and Bit-wise Attention for CTR Prediction
In this paper, we propose an attention-based approach that leverages max and mean pooling operations, along with a bit-wise attention mechanism, to enhance feature importance estimation in CTR prediction.
Ranked #1 on
Click-Through Rate Prediction
on Frappe
Deep Simplex Classifier for Maximizing the Margin in Both Euclidean and Angular Spaces
This paper introduces a novel classification loss that maximizes the margin in both the Euclidean and angular spaces at the same time.
TRAT: Tracking by Attention Using Spatio-Temporal Features
Although motion provides distinctive and complementary information especially for fast moving objects, most of the recent tracking architectures primarily focus on the objects' appearance information.
