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cs.LG2026
DSL: Understanding and Improving Softmax Recommender Systems with Competition-Aware Scaling
Bucher Sahyouni, Matthew Vowels, Liqun Chen +1
Softmax Loss (SL) is being increasingly adopted for recommender systems (RS) as it has demonstrated better performance, robustness and fairness. Yet in implicit-feedback, a single…
cs.LG2025
Differential Adjusted Parity for Learning Fair Representations
Bucher Sahyouni, Matthew Vowels, Liqun Chen +1
The development of fair and unbiased machine learning models remains an ongoing objective for researchers in the field of artificial intelligence. We introduce the Differential Adj…