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cs.IR2023★ 1 cited
Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach
Tao Yang, Cuize Han, Chen Luo +3
Ranking is at the core of many artificial intelligence (AI) applications, including search engines, recommender systems, etc. Modern ranking systems are often constructed with lear…
cs.IR2014
Squeezing bottlenecks: exploring the limits of autoencoder semantic representation capabilities
Parth Gupta, Rafael E. Banchs, Paolo Rosso
We present a comprehensive study on the use of autoencoders for modelling text data, in which (differently from previous studies) we focus our attention on the following issues: i)…