Feature selection, as a data preprocessing strategy, has been proven to be effective and
efficient in preparing data (especially high-dimensional data) for various data-mining and …

Abstract Multi-task learning (MTL), which optimizes multiple related learning tasks at the
same time, has been widely used in various applications, including natural language …

Intelligent reflecting surface (IRS) offers a cost-effective solution to link blockage problem in
mmWave communications, and the prerequisite of which is the accurate estimation of (1) the …

Sequence-to-sequence models are a powerful workhorse of NLP. Most variants employ a
softmax transformation in both their attention mechanism and output layer, leading to dense …

A new algorithm is proposed to project, exactly and in finite time, a vector of arbitrary size
onto a simplex or an l_1 l 1-norm ball. It can be viewed as a Gauss–Seidel-like variant of …

In this paper we propose efficient algorithms for solving constrained online convex
optimization problems. Our motivation stems from the observation that most algorithms …

Micro-expression recognition aims to infer genuine emotions that people try to conceal from
facial video clips. It is a very challenging task because micro-expressions have a very low …

Large-scale linear classification is widely used in many areas. The L1-regularized form can
be applied for feature selection; however, its non-differentiability causes more difficulties in …

Person re-identification, aiming to identify images of the same person from various cameras
configured in different places, has attracted much attention in the multimedia retrieval …

Background Temporal lobe surgical resection brings seizure remission in up to 80% of
patients, with long-term complete seizure freedom in 41%. However, it is unclear how …